«Research Retrieval and Academic Letters» (December 11-12, 2025). Warsaw, Poland, 2025
Abstract
Publisher.agency: Proceedings of the 11th International Scientific Conference «Research Retrieval and Academic Letters» (December 11-12, 2025). Warsaw, Poland, 2025. 580p
Full text
December
,
2025
№ 11
Warsaw, Pola nd
11- 12.12.2025
Proceedings of the 11th International Scient ific Conference
2
UDC 001.1
P 9 7
Publisher .agency: Pr oce edings of the 11th
International Scientific
Conference «Research R etrieval and Academic Letters» (December 11-12
,
202 5). Warsaw, Poland, 2025. 596p
ISBN 9 78-3-11 62-3 417-0
DOI 1 0.5281/zenodo.1 801798 6
Editor: D agmara Wit kowska, Profess or, University of War saw
Internat ional Editorial Board:
Dorota Kołodziej
Professor, Jagiellonian University
Urs zula Kaźmierczak
Professor, Warsaw University o f Technology
Tomasz Sobczak
Professor, Wroclaw University of S cience &
Technology
Filip Chmie lewski
Professor, Warsaw University o f Life Sciences
Oliwia Szcz epańska
Professor, Medical Un ive rsity of Silesia,
Katowice
Arkadiusz Ziółkowski
Professor, Poznan University of Economics
Jan Kwiatkow ski
Professor, Warsaw S chool o f Economics
Daria Wróblewska
Professor, University of Ar ts of Poznan
Lena Kr upa
Professor, Adam Mickiewicz University
Dawid P awlak
Professor, Jan Kochanowski U niversity
Roksana Jankowska
Professor, Nicolaus Copernicus U niversity
Karol Chmielewski
Professor, University of Opole
Jędrzej Zawad zki
Professor, University of Warmia and M azury
in Olsztyn
Katar zyna Brzezińska
Professor, Marie Curi e-Sklodow ska University
editor @publisher. agency
https://publishe r.agency/
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
3
Table of Contents
Legal Sciences
CYBERBULLYING AMONG TEENAGERS: THEORETICAL AND LEGAL ASPECTS ...... ...... ... ....... ... ...... ... ...... ....... ... ...... ... ....... ...... ... ....... ... ..... 8
O RSAYEVA R AISS A A NUAROVNA
S ADUAKASOVA L AILA K UMARB EKOVNA
Pedagogic al Sciences
THE ROLE OF AI IN ENHANCING PRONUN CIATION TRAINING FO R ESL LEARNERS ...... ....... ... ...... ... ....... ... ...... ....... ... ...... ... ...... ....... ... ... 14
S HAKHZAD K HAI RULLAYEV D ILSHAT ULY
THE IMPACT OF DIGITAL TOOLS ON THE PROFE SSIONAL GROWTH OF FUT URE ENGLISH TEACHERS ...... ....... ... ...... ... ....... ... ...... ....... 24
Z AREMA B EISEN BAY
S EMBAYEVA Z H .K.
PRİMARY CLASS İN A MULTİ-LEVEL EDUCA TİONAL ENVİRONMENT APPROACH TO TEACHER TRAİNİNG......... ...... ... ....... ... ...... ... ...... 30
L ALA Z AHIR A LLAHVER DIYEVA
PREDICTIVE ANALYTICS FOR EARLY DE TECTION OF LEARNING D IFFICULTIES IN STUDENTS ...... ...... ... ....... ... ...... ... ....... ...... ... ...... .... ... 35
R USTEMBEK N. M.
S ULTAN A. S.
K UATBAYEVA A. A.
USING AUTHENTIC VIDEO CONTENT TO F OSTER LINGUACULTURAL COMPETENCE AT THE BASIC STA GE OF S ECONDARY SCHOOL
.. ... ... ...... .... ... ...... ... ....... ... ... ...... ... .... ...... ... ...... .... ... ...... ... ... ....... ... ...... ... ... ....... ... ... ...... .... ... ...... ... ...... .... ... ...... ... ... ....... ... ...... ... .... ...... ... ... .... 47
Z HUMABEKOV A G.B.
S ERIKBAI A.
DEVELOPING INTERCULTURAL COMMUNICATIVE CO MPETENCE THROUGH AI-GENERATED COMMUNICATION SCENARIOS IN
GRADE 10 ...... ... ...... ... ... ....... ... ... ...... .... ...... ... ... ....... ... ... ...... ... ....... ... ... ...... ... .... ...... ... ... ....... ... ...... ... ... ....... ... ... ...... ... ....... ... ... ...... .... ... ...... .. 54
Z HIYENBEK Z HAN EL M URATKY ZY
Z HUMABEKOV A G ALIYA B AISKANOV NA
PHYSICAL CULTURE AS A FACTOR IN E NHANCING ACADEMIC PERFORMANCE: A CORRELATION ANALYSIS BETWE EN MOTOR
ACTIVITY, COGNITIVE FUN CTIONS, AND GPA AMONG TECHNOLOGY AND BUSINESS S TUDENTS .......... ... ...... ....... ... ...... ... ...... .... ...... 61
Z HANAT K ENZHE BALIN
Y ERZHAN O MAROV
ADAPTİVE LEARNİNG METHODS: PERS ONALİZED EDUCATİON THROUGH INTELLİGENT SYSTEMS ..... ....... ...... ... ....... ... ...... ...... .... ...... 66
A HMADOVA G ONCH A V IDADI
THE ROLE OF AI IN WRITING ASSESSMENT: A COMPARISON WITH HUM AN EVALUATION ....... ... ...... ...... ... ....... ... ...... ... ....... ...... ... ..... 70
G. A. R IZ AKHODJAYEV A
M.B. Y ULDAS HEVA
THEORETICAL FOUNDATIONS OF CRITERION-BASED ASSESSMENT IN EVALUATING DIALOGUE AND CO NVERSATIONAL SKILLS .... 81
B ERKINGALI N AUR YZBEK B ERKINGA LIULY
Z HUMABEKOV A G ALIYA B AISK ANOVNA
CODE-SWITCHING AMONG ENGLISH MAJORS DURING GROUP D ISCUSSIONS ...... ...... ... ...... ....... ... ...... ... ....... ...... ... ...... .... ...... ...... ... ... 86
M ADENIYET A LUA K URALBEKKY ZY
Y ESSENOV A S HUGYLA Z HU MAHANKY ZY
Z AURBEK A LIYA M UHTARKYZY
K OSYMBAI A RUZH AN S HAIMER DENKYZY
U ZAKBAEVA S.A.
AZƏRBAYCAN VƏ FRANSIZ DİLLƏRİNDƏ CÜMLƏNİN MÜQAYİSƏLİ TƏHLİLİ ..... ...... ....... ... ...... ... ....... ... ...... ....... ... ...... ... ...... ....... ... ...... .. 93
R ƏFIYEVA X URA MAN Ə LI QIZI
PEDAGOGICAL CONDITIONS FOR E FFECTIVE INSTRUCTION IN OCCUPATIONAL HEALTH AND SAFE TY FUND AMENTALS WITH IN THE
SYSTEM OF HIGH ER EDUCA TION .......... ... ... ...... .... ...... ... ... ....... ... ... ...... ... ....... ... ... ...... ... .... ...... ... ...... .... ... ...... ... ... ....... ... ...... ... ... ....... ... ... .. 98
K ULDZHATAEV M UKHT AR M AULET KAZIEVICH
D ARMANKULOV K UAT O MIRS ERIKOVICH
LEARNING ENGLISH THROUGH FAIRY TALES: S TUDYING ENGLISH WITH THE HELP OF KAZAKH FAIRY TALE S AND AI IN PRIMARY
SCHOOL ..... ...... .... ... ...... ... ... ....... ... ...... ... .... ...... ... ... ...... .... ...... ... ... ....... ... ... ...... ... .... ...... ... ...... ... .... ...... ... ... ....... ... ...... ... ... ....... ... ... ...... .... ... 108
B AZARBAYEV A K UNARAY
K AIRZHAN G ULSAT
N ABIDULLIN S. A I BOLAT
INNOVATIVE APPROACHES TO TEACHING FOREIGN LANGUAGE S TO CHILDREN WITH HEARING IMP AIRMENTS THROUGH THE USE
OF AI-BASED TECHNOLOGIES ..... ...... .... ... ...... ... ....... ... ... ...... ... ... ....... ... ...... ... .... ...... ... ... ....... ... ...... ... ... ....... ... ... ...... ... ....... ... ... ...... .... ... .... 113
T AUBAI A LTYNAI O RA ZBEKKYZY
N ABIDULLIN S. A I BOLAT
ARTIFICIAL INTELLIGENCE AS A TOOL F OR DEVELOPING COMMUNICATIVE COMPETENCE IN F OREIGN LANGUAGE LEARNERS ... 119
T OLKYN D ILDABEK
N ABIDULLIN S. A I BOLAT
DEVELOPING SPEAKING SKILLS THR OUGH ARTIFICIAL INTELLIGENCE: EFFE CTIVE METHODS AND TOOLS ....... ...... ... ...... .... ...... ...... 125
Y ERZHIGIT A IZADA
N ABIDULLIN S. A I BOLAT
DEVELOPING FUNCTIONAL LITERACY IN PRIMARY SCHOOL STUD ENTS...... ...... ...... .... ...... ... ...... ....... ... ...... ... ....... ... ...... ...... .... ...... ... ... 129
A NUARBEK A K MARAL Y ERKAZYK YZY
N ABIDULLIN S. A I BOLAT
Proceedings of the 11th International Scient ific Conference
4
THE USE OF ARTIFICIAL INTELLIGE NCE AND D IGITAL TOOLS TO SUPPORT MULTILINGUAL PR IMARY EDUCA TION IN KAZAKHSTAN
.. ... ... ...... .... ... ...... ... ....... ... ... ...... ... .... ...... ... ...... .... ... ...... ... ... ....... ... ...... ... ... ....... ... ... ...... .... ... ...... ... ...... .... ... ...... ... ... ....... ... ...... ... .... ...... ... ... .. 134
E LMIRA I ZTELEUOV A
N ABIDULLIN S. A I BOLAT
CHATGPT FOR DEVELOPING PRIMARY STUD ENTS’ LANGUAGE SKILLS ...... ... ....... ...... ... ....... ... ...... ... ...... ....... ... ...... ... ....... ...... ... ....... ... 143
U SSEN Z HANN A B AURZHANK YZY
N ABIDULLIN S. A I BOLAT
Philolog ical Sciences
АБАЙДЫҢ `АҚЫЛ` СӨЗДЕРІ: ҰЛТТЫҢ О ЙЛАУ ЖҮЙЕСІ ........ ...... .... ...... ...... ... ....... ... ...... ... ....... ...... ... ...... .... ...... ...... ... ....... ... ...... ... ...... 148
С АЛҚЫНБАЙ А НАР Б ЕКМЫРЗАҚЫЗЫ
ТАҒАМ АТАУЛАРЫНЫҢ МЕНТАЛДЫ Қ БЕЙНЕСІ ЖӘНЕ ФРАЗЕОЛОГИЯЛЫҚ МАҒЫ НА ЖАСАУДАҒЫ ҚЫЗМЕТІ ..... ...... ... ....... ... .. 157
Б ӨШЕН А ЙЖАН Н ҰРЛАНҚЫЗЫ
PERSONALITY PHENOMENON: F ACTORS INFLUENCING PERSONALITY DEV ELOPMENT .. ...... ... ....... ...... ... ...... ... ....... ...... ... ....... ... ...... 162
D INAR K ERIMOVA
L` EMPRUNT LİN GUİSTİQUE DA NS LE FRANÇAİS .. ...... ... ... ....... ... ...... ... ... ....... ... ... ...... .... ...... ... ... ...... .... ... ...... ... ... ....... ... ...... ... .... ...... ... .. 168
Ə KBƏROVA Ə SMAY Ə B ƏXTIYAR QIZI
ҚАЗІРГІ ҚАЗАҚ ӘДЕБИЕ ТІНД ЕГІ ТҮС КӨРУ МОТИВІ (А.АЛ ТАЙ `ТҮСІК` ӘҢГІМЕСІ НЕГІЗІНДЕ) ..... ... ....... ... ...... ....... ... ...... ... ....... ...... 171
Ө ТЕБАЙ Л ЯЗЗАТ
С ЕРІКБАЙ Н АЗЕРКЕ
С ЫЗДЫКОВА Б.Е.
KAZAKH LITERATURE AND ECOCRI TICISM (BASED ON THE POEMS O F ABAI QUNANBAIULY) ... ... ...... ....... ... ...... ... ....... ... ...... ...... .... .. 176
T OKBOLAT M EREY
S ALYKBAY I NDIR A
B.E. S YZDYKOVA
ADVANTAGES AND LIMITATIONS O F USING ARTIFICIAL INTELLIGENCE IN TEACHING ENGLISH ... .... ...... ...... ... ....... ... ...... ... ....... ...... . 180
B ERDIKULOVA A KNIYET
B ERDEMBA YEVA N AZGUL
N ABIDULLIN S. A IBOLAT
COGNITIVE ASPECTS OF LEARNING A LANGUAGE WITH AI SUPPORT ..... ... ....... ... ...... ... ....... ...... ... ...... ... ....... ...... ... ....... ... ...... ... ....... ... 187
I MANALI A RUZH AN
S. A IBOLAT N ABI DULLIN
A NEW PARADIGM FOR FOREI GN LANGUAGE TEACHIN G IN A PED AGOGICAL UNIVERSITY IN KAZAKHSTAN: HOW TO USE AI TO
RESTORE DIALOGUE, E MPATHY , AND CRITICAL THINKING ..... ...... ... ....... ... ...... ...... .... ...... ... ...... .... ...... ...... ... ....... ... ...... ...... .... ...... ... ..... 191
T UGELBAYEVA A LMAGUL
AI-ASSISTED ENGLISH VOCABULAR Y LEARNING: A NEW APPROACH FO R DIGITAL-AGE STUDENTS ...... ... ....... ...... ... ...... ... ....... ...... .. 198
Z HIGER Z HOLD Y
N ABIDULLIN S. A I BOLAT
PERSONALIZED LANGUAGE LEARNING THROUGH ARTIFICIAL INTELLIGENCE ......... ...... ... ....... ... ...... ....... ... ...... ... ....... ...... ... ...... ... ...... 203
M USABAY A KZHAR KYN B EKBOLAT KYZY
N ABIDULLIN S. A I BOLAT
A BAI K AZAKH N ATION AL P EDAGO GICAL U NIVERSITY
Technic al Sciences
KORPORATİV ŞƏBƏKƏLƏRDƏ İDS/İPS SİSTEMLƏRİNİN SİYASƏT OPTİ MALLAŞDIRMASI ÜÇÜN ADAPTİV R İSK-YÖNÜMLÜ YANAŞMA
.. ... ... ...... .... ... ...... ... ....... ... ... ...... ... .... ...... ... ...... .... ... ...... ... ... ....... ... ...... ... ... ....... ... ... ...... .... ... ...... ... ...... .... ... ...... ... ... ....... ... ...... ... .... ...... ... ... .. 209
A IDƏ M ÜBARIZ QI ZI M USTAFAY EVA
T URAL E LÇIN OĞLU Y ARMƏ MMƏDOV
APPLICATION OF ARTIFICIAL NEURAL NETWORKS IN AUTOMATION S YSTEMS .. ...... ...... ... ....... ... ...... ...... .... ...... ... ...... ....... ... ...... ... ..... 218
B EKTEMІR A.T.
EVALUATING THE IMPACT OF CLOUD TECHNOLOGIES ON IT PROJECT MANAGEMENT EFF ICIENCY, COST-EFFECTIVENE SS AND
AGILE METH ODOLOGIES ...... ....... ... ... ...... .... ...... ... ... ...... .... ... ...... ... ....... ... ... ...... ... .... ...... ... ... ...... .... ...... ... ... ....... ... ... ...... ... ....... ... ... ...... ... . 222
K HANAFIYEV A E. U.
A ITUOV A. T.
СУЫТУ ЖҮЙЕ ЛЕРІН АВТОМАТТАНДЫРУ САЛАСЫНДАҒЫ ИННОВА ЦИЯЛАР МЕН ДАМУЫ ...... .... ...... ... ...... ....... ... ...... ... ....... ...... .. 234
Қ АБИЕВ С.C.
Ж ҰМАХАН Н.Б.
Д ЖУЛАЕВА Ж.Т.
ТЕМПЕРАТУРАНЫ АВТОМАТТЫ РЕТТЕУ Ж ҮЙЕСІНІҢ ТЕРМОСТАТ Қ ЫЗМЕТІ ЖӘНЕ ЖҰМЫС ПРИНЦИПТЕРІ ... ... ....... ...... ... ....... . 237
М УСАБЕК Д.Қ.
И ЛЬЯСОВ Е.С.
Ж ҰМАХАН Н.Б.
КОНДИЦИОНЕРДІҢ ЖҰМЫС ІСТЕУ ПРИНЦИПІ ЖӘНЕ ОНЫҢ НЕГІЗГІ Б ӨЛІКТЕРІ ..... ....... ...... ... ...... .... ...... ...... ... ....... ... ...... ... ....... ... 240
Ә УЕЛБЕК Е РТАРҒЫН
Ж АМБЫЛБЕК Е РХАН
И ЛЬЯСОВ Е.С.
Д ЖУЛАЕВА Ж.Т.
ХЛАДАГЕНТТЕРДІҢ ЭКОЛОГИЧЕСКИЯЛЫ Қ ӘСЕРІ ЖӘНЕ ОЗОН ҚАБАТЫН ҚОРҒАУ МӘСЕЛЕЛЕРІ ......... ... ....... ... ...... ....... ... ...... ... . 246
Б АҚБЕРГЕНОВ Е РЗ АТ
А МАНГЕЛДІҰЛЫ О ЛЖАС
И ЛЬЯСОВ Е.С.
Д ЖУЛАЕВА Ж.Т.
Ж ҰМАХАН Н ҰРЖАН Б ЕЙБІТҰЛЫ
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
5
СЫРТҚЫ АУАНЫҢ ТӨМЕН ТЕМПЕРАТУРАСЫНДА ЖҰМЫС ІСТЕЙТІН ЖЫЛУ СОРҒЫ ЛАРЫ ......... ...... ... ....... ... ...... ...... .... ...... ... ...... 251
Е СБОЛҒАНОВ Д ИДАР
Д ҮЙСЕН Қ УАНЫШ
И ЛЬЯСОВ Е.С.
Д ЖУЛАЕВА Ж.Т.
Ж ҰМАХАН Н ҰРЖАН Б ЕЙБІТҰЛЫ
КӨМІРҚЫШҚЫЛ ГАЗЫН САЛҚЫНДАТУ ЖҮЙЕЛЕРІ МЕН ТАҒАМДЫ К ЕПТІРУ ПРОЦЕСТЕРІН БІРІКТІРУ......... ... ...... .... ...... ...... ... ... 256
М УХАДЕС М.Ж.
О НГАРОВ Т.А.
Т ОЛЕГЕНОВ Б.Т.
Д ЖУЛАЕВА Ж.Т.
Ж ҰМАХАН Н.Б.
A MODEL FOR REQUI REMENTS ANALYSIS AND ARCHITECTURAL DESIGN OF SMART TECHNOLOGIES I N THE EDU CATIONAL
PROCESS ..... ...... .... ... ...... ... ... ....... ... ...... ... ... ....... ... ... ...... .... ...... ... ... ....... ... ... ...... ... ... ....... ... ...... ... .... ...... ... ... ....... ... ...... ... ... ....... ... ... ...... ... ... 263
T EN T ATYANA L EONI DOVNA
S PANOVA B AKYT Z H AMBYLOV NA
A BDRAKHMANOVA S VETLAN A V LADIMIROVNA
INTERNET OF THINGS EMPOWERE D BY ARTIFICIAL INTELLIGENCE OF THINGS .. ... ....... ... ...... ....... ... ...... ... ....... ... ...... ...... .... ...... ... ...... 269
A SKARBEK A SLAN
ХЛАДАГЕНТТЕРДІҢ ЭКОЛОГИЯЛЫҚ ӘСЕ РІ ЖӘНЕ ОЗОН ҚАБАТЫН ҚОРҒАУ МӘСЕЛЕЛЕРІ ..... ....... ... ...... ... ....... ...... ... ...... .... ...... ... 274
Т ҰРДАҚЫН Ж.Н.
И ЛЬЯСОВ Е.С.
Д ЖУЛАЕВА Ж.Т.
ӨНЕРКӘСІПТІК ТОҢАЗЫТҚЫШТАРДЫ Ң АВТОМАТТАНДЫРЫЛҒАН Б АСҚАРУ ЖҮЙЕСІНІҢ ТИІМДІЛІГІ .......... ... ...... ....... ... ...... ... .. 279
Д.М.С МАТ
VRF/V RV КОНДИЦИОНЕРЛЕУ ЖҮЙЕЛЕРІНДЕГІ АВТОМАТТ Ы Б АСҚАРУ ПРИНЦИПТЕРІ ЖӘНЕ ОЛАРДЫҢ А РТЫҚШЫЛЫҚТАРЫ
.. ... ... ...... .... ... ...... ... ....... ... ... ...... ... .... ...... ... ...... .... ... ...... ... ... ....... ... ...... ... ... ....... ... ... ...... .... ... ...... ... ...... .... ... ...... ... ... ....... ... ...... ... .... ...... ... ... .. 284
А БДУЛЛА Н.
Ә ДІЛХАН М.
И ЛЬЯСОВ Е.С.
Д ЖУЛАЕВА Ж.Т.
Ж ҰМАХАН Н ҰРЖАН Б ЕЙБІТҰЛЫ
СЫРА ЗАУЫТЫНА АРНАЛҒАН ЭНЕРГИЯ ҮНЕМДЕЙТІН ТОҢАЗЫТУ МАШИНАСЫН ЖАСАУ ......... ... ...... ... ....... ... ...... ...... .... ...... ... .... 292
Ж ҮСІПБЕК Е ЛД ОС
Б АЛТАБАЙ Р ОМАН
И ЛЬЯСОВ Е.С.
Д ЖУЛАЕВА Ж.Т.
SYSTEME MULTILINGUE D E TRADUCTION ET DE SYNTHESE VO CALE B ASE SUR NO DE-RED ET FLASK.. ....... ...... ... ...... .... ...... ... ...... ... 298
S AADIA ALBANE
T HIERRY VAL
A DRIEN VAN DE N BOSSCHE
L AURENCE REDO N
R EJANE DALCE
A NTONIO SERPA
MATHEMATICAL MODELING IN UNDE RSTANDI NG REAL-LIFE FINANCIAL PROCESSES ... ...... .... ...... ... ...... .... ...... ...... ... ....... ... ...... ...... . 307
Y ELENA B EDYCH
Economic Sciences
FEATURES O F THE BUDGETING PROCESS...... ... ... ...... ... .... ...... ... ...... .... ... ...... ... ... ....... ... ... ...... ... ....... ... ... ...... .... ... ...... ... ...... .... ... ...... ... ... . 316
G ULMIRA N URZHAN OVA
PLANNING AND FORECASTING THE R EDUCTION OF PRODUCTION COSTS........ ...... ... ...... .... ...... ... ...... ....... ... ...... ... ....... ...... ... ...... .... .. 320
G ULMIRA N URZHAN OVA
KASPI.KZ’S IPO AND ITS IMPACT O N KAZAKHSTAN’S STOCK MARKET .......... ... ...... ...... .... ...... ... ...... ....... ... ...... ... ....... ... ...... ....... ... ...... .. 324
S HIROCHENKO A RINA D MITRIEVN A
M IKHAILOVA M ARIY A O LEGOVNA
K ADIRBEKOVA B IN UR N URLANOV NA
T EMIRZHAN T E MIRLAN S ERIKULY
S ABIT A MIR B EIBIT ULY
AZƏRBAYCAN ÜZƏRİNDƏN KEÇƏN ORTA DƏHLİZİN GEOİQTİSADİ Ü STÜNLÜKLƏRİ VƏ BEYNƏLXALQ TİCARƏTƏ TƏSİRİ .......... ...... 334
D ƏYANƏT M ƏM MƏDZADƏ G ÜLH ƏSƏN
ФИНАНСОВАЯ УСТОЙЧИВОСТЬ БАНКОВ: СОВРЕ МЕННЫЕ ПОДХОДЫ И МЕЖДУНАРОДНЫЙ ОПЫТ ... .... ...... ...... ... ....... ... ...... ... 339
А КАНОВА А НЕЛЬ Д ЖУМАБЕКО ВНА
А ЛМАСБЕКҚЫЗЫ Е ҢЛІК
Е ЛУБАЕВА Ж УЛДЫ З М АРАТОВНА
Р УЗИЕВА Э ЛЬ ВИРА А БДУЛМ ИТОВНА
ВОПРОСЫ НАЛОГООБЛОЖЕНИЯ НА УГЛЕРОДНЫЕ ВЫБРОСЫ: МИРОВОЙ ОПЫТ ПРОВОДИМЫХ РЕФОРМ ........ ....... ... ...... ... . 352
С ӘРСЕНБЕК З АҢҒ АР
Т ӨЛЕПБАЙ Б АУЫРЖ АН Т ҰРСЫНБ АЙҰЛЫ
Т УЛЕЕВА Ф АРИДА М АР АТОВНА
Р УЗИЕВА Э ЛЬ ВИРА А БДУЛМ ИТОВНА
КАПИТАЛ НАРЫҚТАРЫНЫҢ Қ АЗАҚСТАН РЕСПУБЛИКАСЫНЫҢ ЭКОНОМИҚАЛЫҚ ДАМУМЕН ӨЗАРА БАЙЛАНЫСЫ .. ....... ... .. 364
Д ЖАКСЫЛЫКОВ А А КМАР АЛ Қ УАНДЫҚҚЫЗЫ
К УМАРХАНО ВА Н УРГУЛЬ Н ҰРМЫШОВН А
Е ЛУБАЕВА Ж УЛДЫ З М АРАТОВНА
Proceedings of the 11th International Scient ific Conference
6
БЮДЖ ЕТНЫЕ ОТНОШЕНИЯ И МЕЖБЮДЖЕТНЫЕ СВЯЗИ В ЗЕЛЁ НЫХ ФИНАНС АХ (GREEN F INANCE) ... ....... ... ...... ...... .... ...... ... ... 374
Ж ЕНИСБЕК Д АНИ АЛ Д АУЛЕТҰЛЫ
С АРСЕМБАЕВА М ЫР ЗАКУЛЬ Ж АН АШТАЕВН А
ПОЧЕМУ ЧАСТНЫЕ РЫНКИ ЧАСТО НЕ ОБЕСПЕЧИВА ЮТ ЭФФЕКТИВНОГО УРОВНЯ ОБЩЕСТВЕННЫХ БЛ АГ В ЗЕЛЁНЫХ
ФИНАН САХ (GREE N FINANCE) ..... ...... .... ... ...... ... ....... ... ... ...... ... ... ....... ... ... ...... .... ...... ... ... ....... ... ... ...... ... ....... ... ... ...... ... .... ...... ... ...... .... ... .. 386
Б ЕРДИБЕКО В М ЕЙРАМБЕК Н УРЛЫ БЕКОВИЧ
С АРСЕМБАЕВА М ЫР ЗАКУЛЬ Ж АН АШТАЕВН А
ОРГАНИЗАЦИОННЫЕ ОСНОВЫ ГОСУДАРСТВЕННОГО АУДИТА РЕ СПУБЛИКИ К АЗАХСТАН ...... ...... ... ....... ... ...... ... ....... ...... ... ...... .. 393
А ЗЫНБАЙ А ЙДЫН О РАЛБ АЙ ҰЫ
Д ОСМАЙЛОВА З АР ИНА Д ИНМУХА ММЕДҚЫЗЫ
М АКИШЕВА Ж АНН А А НАТОЛЬ ЕВНА
DEVELOPMENT TRENDS O F SMALL AND MEDIUM-SIZED E NTERPRISES IN KAZAKHSTAN ..... ...... .... ...... ...... ... ....... ... ...... ....... ... ...... ... 405
Z HANARBEK A I ZHAN
FEATURES OF USING ARTIFICIAL INTELLIGENCE FOR FORECASTING THE SECUR ITIES MARKET ...... ... ...... ... ....... ...... ... ...... .... ...... ... ... 410
B ORISOV A.A.
U LAKOV N.S.
T YNGISHEVA A.M .
АГРАРЛЫҚ СЕКТОРДА ЦИФРЛЫҚ МАРКЕТИНГТІК СТРАТЕГИЯНЫ ҚАЛЫПТАСТЫРУ: Ж ЕТІСУ ОБЛЫСЫ МЫСАЛЫНДА ....... ..... 414
Ж УНУСОВА Г.А.
FROM TEA TO KUMISS: CODING `LI-QUN-DU` CARE S CRIPTS INTO BELT-AND-ROAD TUNNE L PERFORMANCE ..... ...... ... ....... ...... ... 423
C HENG C HE
STRATEGIC MANAGEMENT AND PRACTICE OF NE W ENER GY PROJE CTS IN CENTRAL ASIA UNDER THE `BELT AND ROAD` INITIATIVE
.. ... ... ...... .... ... ...... ... ....... ... ... ...... ... .... ...... ... ...... .... ... ...... ... ... ....... ... ...... ... ... ....... ... ... ...... .... ... ...... ... ...... .... ... ...... ... ... ....... ... ...... ... .... ...... ... ... .. 429
W ANG L IANG
APPLICATION OF SCENARIO ANAL YSIS IN MARKET RISK MANAGEMENT OF COMMERCIAL BANKS: INTERNATIONAL PRACTICE AND
CASE STUDIES ......... ... ... ....... ... ... ...... ... .... ...... ... ...... .... ... ...... ... ... ....... ... ...... ... .... ...... ... ... ...... .... ...... ... ... ....... ... ... ...... ... .... ...... ... ...... ... .... ...... 435
C HEN J UN
ЭВОЛЮЦИЯ КОНЦЕПЦИИ ESG: ОТ КОРПОРАТИВНОЙ ОТВЕТСТВЕ ННОСТИ К ГЛОБАЛЬНОЙ ПОВЕСТКЕ У СТОЙЧИВОГО
РАЗВИТИЯ .... ...... ... ... ...... .... ... ...... ... ....... ... ... ...... ... .... ...... ... ... ...... .... ...... ... ... ....... ... ... ...... ... ....... ... ... ...... ... .... ...... ... ...... .... ... ...... ... ... ....... ... . 442
Е СЕНГАЛИ Л ЕЙЛ А
З АКИРОВА Д ИЛЬНАР А И КР АМХАНОВНА
Cultur ology
MUSICAL IDIOMS: REF LECTION OF CULTURAL CONCEPTS AND THEIR ROLE IN TEACHING A FOREIGN LANGUAGE AT A CREATIVE
UNIVERSITY ..... .... ... ...... ... ... ....... ... ... ...... ... ....... ... ... ...... .... ... ...... ... ...... .... ... ...... ... ... ....... ... ...... ... .... ...... ... ... ...... .... ... ...... ... ....... ... ... ...... ... .... 453
S EIDULLA B AKYT
Y ESSETOVA A INUR
Geographic Sciences
ЖЕТІСУ ӨҢІРІ ТЕКЕЛІ–ҮШТӨБЕ АЙМАҒЫНДАҒЫ 2011–2024 Ж ЫЛДАРДАҒЫ Қ АР ҚАЛЫҢДЫҒЫНЫҢ ДИНАМИКАСЫН ТАЛДАУ
ЖӘНЕ МАТЕМАТИКАЛЫҚ МОДЕЛІ ..... ... ....... ... ... ...... .... ... ...... ... ....... ... ... ...... ... ... ....... ... ...... ... .... ...... ... ... ....... ... ... ...... ... ....... ... ... ...... ... .. 458
З АУРЕ Н ИЯЗБЕКО ВНА К АНАП ИЯНОВ А
Ж АНБАЙ Ш У ЙНШАЛИЕВИЧ У ЗДЕНБАЕ В
А ЙЖАН А СХАТҚЫЗЫ М ЫРЗАХ МЕТОВА
ЖЕТІСУ ӨҢІРІНІҢ ТЕКЕЛІ – ҮШТӨБЕ АЙМАҒЫНДАҒЫ 2011–2024 ЖЫ ЛДАР АРАЛЫҒЫНДАҒЫ КӨКТЕМ МЕЗГІЛІНДЕГІ АУА
ТЕМПЕРАТУРАСЫ ӨЗГЕРІСТЕРІН МАТЕМАТИКАЛЫҚ МОДЕЛЬДЕ У ЖӘНЕ БОЛЖАУ ......... ... ...... ... ....... ...... ... ...... .... ...... ... ...... ....... 462
У ЗДЕНБАЕВ Ж.Ш.
К АНАПЬЯНО ВА З.Н.
С МАГУЛОВА Л.А.
Б ИСҰЛТАН Е РХАТ
АЛАКӨЛ КӨЛІНІҢ 2009–2015 ЖЫ ЛДАР АРАЛЫҒЫНДАҒЫ СУ ДЕҢГЕЙІНІҢ МАТЕМАТИКАЛЫҚ М ОДЕЛІ: УАҚЫТТЫ Қ ҚАТАРЛАР
ТАЛДАУЫ ЖӘНЕ БОЛЖАУ... ....... ... ... ...... .... ...... ... ... ...... .... ... ...... ... ....... ... ... ...... ... .... ...... ... ... ....... ... ...... ... ... ....... ... ... ...... ... ....... ... ... ...... .... 469
М ҰХАМЕТҚАЛИ А ҚЫЛБЕК А РДАҚҰЛЫ
У ЗДЕНБАЕВ Ж АНБ АЙ Ш УЙНШАЛ ИЕВИЧ
АЛАКӨЛ ӨЗЕНІ ДЕҢГЕЙІНІҢ 2000–2009 ЖЫ ЛДАР АРАЛЫҒЫНДАҒЫ ӨЗГЕРІСТЕРІНІҢ МАТЕМАТИКАЛЫҚ М ОДЕЛІН ҚҰРУ ЖӘНЕ
БОЛЖАУ ...... ... ...... .... ...... ... ... ....... ... ... ...... ... ... ....... ... ...... ... .... ...... ... ... ....... ... ...... ... ... ....... ... ... ...... ... ....... ... ... ...... .... ... ...... ... ... ....... ... ...... ... .. 475
У ЗДЕНБАЕВ Ж.Ш.
К АНАПЬЯНО ВА З.Н.
С МАГУЛОВА Л.А.
М ҰРАТЖАНҰЛЫ Е РКЕБҰЛАН
XİDMƏTİN HƏCMİNƏ TƏSİR GÖSTƏRƏN AMİLLƏRİ MÜƏYYƏNLƏŞDİ RİLMƏ Sİ ..... ....... ... ...... ... ....... ... ...... ...... .... ...... ... ...... ....... ... ...... .. 479
Ə LIYEVA Ş ƏFƏQ M Ə MMƏD QIZI
ПРАКТИЧЕСКИЕ МЕТОДЫ ОБУЧЕНИЯ ИСК УССТВЕННЫХ НЕЙРОННЫХ СЕТЯХ ...... ... ...... .... ...... ...... ... ....... ... ...... ... ....... ...... ... ...... .... 483
Р АМАЗАНОВ Р ОВША Н Г АСАН
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
7
Psychologic al Sciences
PEDAGOGICAL AND PSYCHOLOGICAL ASPECTS OF LEARNING MOTI VATION IN ADOLESCENTS .. ... ...... ... ....... ... ...... ...... .... ...... ... ...... 487
R AMAZANOVA K AMALA
MODERN ART THERAPY IN WORKING WITH TEENAGERS ..... ...... ... ....... ... ...... ...... ... ....... ... ...... ... ....... ...... ... ....... ... ...... ...... .... ...... ... ...... . 493
A DIL D UNYA
G ULNARA H ASANOV A
RƏQƏMSAL TEX NOLOGİYALARDA KI İNKİŞAFLARIN İNSAN PSİXOLOGİYASINA TƏSİRİ ......... ... ....... ...... ... ...... .... ...... ... ...... ....... ... ...... .. 497
P ƏNAHOVA İ LKAN Ə M ÜBARIZ QI ZI
Political Stu dies
ПРАВОВЫЕ И ИНСТИТУЦИОНАЛЬНЫЕ ИЗМЕР ЕНИЯ ТРАНСФОРМАЦИИ РЕСПУБЛИКИ К АЗАХСТАН: РЕАЛИЗАЦИЯ ПОВЕСТКИ
`СПРАВЕДЛИ ВОГО КАЗАХСТАНА` ..... .... ...... ... ... ....... ... ... ...... ... .... ...... ... ...... ... .... ...... ... ... ....... ... ...... ... ... ....... ... ... ...... .... ...... ... ... ...... .... ... .. 506
Л УЗАНОВ В.А.
К АБДИЙ Н.Г.
К ЕНЖЕБУЛАТО ВА А.М.
Geologic al and M ineralogical Sciences
РЕЗУЛЬТАТИ ВИКОРИСТАННЯ МОБІЛЬНИХ ПРЯМОШУКОВИХ МЕТ ОДІВ ПРИ ВИВЧЕННІ ПРОЦЕСІВ ДЕГАЗАЦІЇ
ВУГЛЕВОДНЕВИХ ФЛЮЇДІВ В СТРУКТУРА Х КОНТИНЕНТАЛЬНИХ ОКРАЇН СВІТОВОГО ОКЕАНУ ... ... ....... ...... ... ...... .... ...... ... ...... .... 511
С ОЛОВЙОВ В.Д.
Я КИМЧУК М.А.
К ОРЧАГІН І.М.
Medical Sc iences
БАЛАЛАРДАҒЫ КРОН АУРУЫ... ....... ... ... ...... .... ... ...... ... ... ....... ... ...... ... ... ....... ... ... ...... .... ...... ... ... ...... .... ... ...... ... ....... ... ... ...... ... .... ...... ... ... .. 554
С АБЫРХАНОВ С ҰҢҒАТ М АРАТҰЛЫ
Т АУЕКЕЛОВА М ЕДИНА К ОРГ АНБЕКОВНА
METHODOLOGICAL BASIS AND ANALYTICAL EVALUATION OF CANCER SCREENING IN KAZAKHSTAN ........ ....... ... ...... ... ....... ...... ... .. 559
A RMAN K HOZHAYEV
A LYONA K RUPA
A RSHA K URMAN ALI - KHODZHA
S ITORA S ATILKH ANOVA
M AKHABBAT G ABITOVA
D IDAR T OLEPBEKOV
B EIBARYS S APAR
R USTAM K UM AROV
Literatur e
PROMOTION OF HUMANISM IDEAS IN THE CREATIVE WORK OF NIZAMI GANDJAVI ..... .... ...... ... ...... .... ...... ...... ... ....... ... ...... ....... ... ... 572
R ZAYEVA G ARA NFIL Z EYGAM
Jour nalism
РОЛЬ И ВЛИЯНИЕ МЕДИА В ОСВЕ ЩЕНИИ ЭТНИЧЕСКИХ КОНФЛИКТОВ НА ПОСТСОВЕТСКОМ ПРОСТРАНСТВЕ:
КАЗАХСТАНС КИЙ И МЕЖДУНАРОДНЫЙ ОПЫТ ..... .... ...... ... ... ....... ... ...... ... ... ....... ... ... ...... ... ....... ... ... ...... .... ... ...... ... ...... .... ... ...... ... ... .... 578
B EKBERGEN A MIR ZHAN
Physical and M athematical Sciences
НЕКОТОРЫЕ ВОПРОСЫ ПРИМЕНЕ НИЯ ДИФФУЗНО-ОТРАЖАТЕЛЬНОГО МЕТОДА ДЛЯ ДИАГНОСТИКИ СО СТОЯНИЯ
ПЛОДООВОЩНОЙ ПРОДУКЦИИ В ВИДИМОЙ ОБЛ АСТИ СПЕКТРА ......... ....... ... ...... ....... ... ...... ... ....... ... ...... ...... .... ...... ... ...... ....... ... . 5 82
И СКЕНДЕРЗАД Е Э ЛЬЧИН Б АРАТ ОГЛЫ
А ЛИВЕРДИЕВ Ш АМИЛ Н АЗИР ОГЛ Ы
Г УСЕЙНОВ К А МИЛЬ С ОХРАБ ОГЛЫ
А ЛИЕВА Х УМАР С АБИР КЫЗЫ
МЕХАНИКА БӨЛІМІН ОҚЫТУДА ОҚУШ ЫЛАРДЫҢ ӨЗІНДІК ЖҰМЫСТАРЫН ҰЙЫМДАСТЫРУ ӘДІСТЕРІ ......... ....... ... ...... ... ....... .. 587
С ЫДЫКОВА Ж АЙН АГУЛЬ К АНЫЕ ВНА
М ЕНДІҚҰЛ Т ӨРЕБ ЕК Е РМУХАНҰЛЫ
Proceedings of the 11th International Scient ific Conference
8
Legal Sciences
UDK 343. 44
МРНТИ 1 0.77.51
C Y B E R B U L L Y I N G A M O N G T E E N A G E R S :
T H E O R E T I C A L A N D L E G A L A S P E C T S
Orsayeva R aissa An uarov na
S.Amanzholov Ea st Kaz ak hstan Universi ty
Sad uakas ova Laila Kum arbekovna
S.Amanzholov Ea st Kaz ak hstan Universi ty
Abstrac t. The articl e provides an understanding of cyberb ullying among minors and gives
its th eoretical and criminal-legal characte ristics within the fr amework of the law. In t he modern
information society with the expan sion of dig ital communications, a n ew an d serious th re at t o
psycho logical and emotional well-being has ari sen - cyberbullying . Th is ph enomenon is a for m of
aggression a nd harassment th at is carried out via the Internet and soci al resources.
The articl e describes a rec ently emerged and wi despread type of bullying among teenager s
- cyberbull ying. The causes, types and conse quen ce s of this phenomenon are ou tlined. The
authors a lso consider ways to prevent c yberbullying.
Keywords : teenager , cyberbullying, Internet, causes, types, consequences, responsi bility,
methods of s truggle, prevention
The Un ited Nations Co nvention on th e Rights of the Child (November 20, 1989 ) serves as
a kind of Constitution pr otec ting childr en's rights . Articl e 54 of th e Convention on the Rights of the
Child st ates th at «...children shall be protecte d from cr uel tr eatment, have the opport unity to
maintain peace and o rder in th eir family, and express their opini ons freely» [1].
Clause 1 of Article 1 of the Const itution of the Republic of Kaz akhstan states: «The Republic
of Kaz a khsta n asserts itse lf as a democ rati c, se cular, legal, and social state, whose highes t v alue i s
the individual, his life, rights, a nd freedoms» [2].
It goes without saying that the provision «...the individual, his life, rights, and freedoms...»
stipulated i n Clause 1 of Article 1 of the Constitution of the Republic of Kazakhstan also a pplies to
adolescents who will one day lea d th e state. In his Address to the People of Kazakhstan,
«Kazakhstan in the Ne w Conditions: Time fo r Action» (September 1, 20 20), Hea d of Sta te Kassym-
Jomart To ka yev stat ed that "the time has come to adopt legislative mea su r es to protect ci tizens,
especially child ren, from cy ber bullying. Other measures to protect ch ildren's righ ts must also be
strengthened» [3] .
Here, it is appropriate to reiterat e the Head of State's statement at the Republican
Congr ess of Teachers (October 5, 2023) that « ...school should become the safest place. Childr en
should f eel comfortable at school in every r espect...»
Indeed, in r ecent years, in additi on to criminal of fenses among adolescents, it's no secret that they
often become «vict ims» of crime.
The fact that adoles cents ar e su bjected to bu llying, especially cyberbullying, as a r esult of
the undesirable actions of a sp ecific in dividual or gro up using various means, is cu rrently becoming
a pressi ng issue.
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
9
Cyberbullying (also known as cy berharassment or online bullying) i s a fo rm of aggress ion
or haras sment ca rried out through digi tal technologies. It involves r epeated harmfu l actions aimed
at intimidat ing, angering, or h umiliating the vict im.
Accor ding to official sources (e. g., StopBullying.gov), cyberbullying oc curs via:
-mobile devices (sm artphones, t ablets);
-computer s and laptops;
-online platforms (social media, messaging apps, forums, gami ng environments).
Cyberbullies u se various methods to har m their victims:
-harass ing mes sages - sending abusi ve, threatening, or in sulting texts, emails, or direct
messages;
-defamation and r umours - spreading false information, goss ip, or lies about t he victim;
-embarra ssing content sharing - p osting pr ivate photos, vi deos, or p ersonal da ta with out
consent;
-impersonation - cr eating fak e accounts or hacking into the victim’s profiles to damage
their r eputation;
-exclusion and ostracism - deliberately excluding s omeone from online groups or chats.
Cyberbullying is insults, harassment, intimidation, and slander . The tr ansmission of harmful
information through insults, harassment, int imidation, and sl ander i s part o f cybe rculture. Sin ce
all these act ions have long been carri ed out through social media usi ng modern communication
tools, it can be seen th at in recent year s, child ren and adolescents, who ar e among the most
vulnerable groups among those su bjected to cyberbullying, have suffered the most.
Accor ding to UNICEF, in 2020, 63% of children in Kazakhstan reported hav ing committed
acts of violence and discrimination. Instead of preventing acts of violence and discrimination ,
school administr ations preferr ed t o conceal instances of bull ying [ 4]. Accor ding to publicly
available da ta from Zak on.kz, one in eight sch ool-age adolescents in Kazakhst an experiences
cyberbullying. Similar data were obtained in a n international s tudy (HBSC).
Accor ding to data from the National Center for Public Health of th e Ministry of Health of
the Republic of Kazakhstan (March 27, 2024) , 13% of Kazakh s tani adolescents (approximately one
in eight) have exper ienced cyberbullying, with thi s rate be ing higher among boys than amo ng girls
(12% ), reaching 15%. Approximately 11% of adolescents (approximately one in nine) have engaged
in cyberbu llying against others, with boys (14%) more likely to report involvem ent tha n girls (8%).
The study also found that approximately 5% of adolescents aged 11–15 are involved in school
bullying, and approximately 7% of stu dents have been attack ed [5 ]. M any scientist s have wr itten
about juvenile delinquency an d criminal acts against th em (E.O. Alauhanov, R.A. Or sayeva, S.I.
Anokhin, I.S. Osipov, U.U. Parfentyev, and others).
There ar e few scholars who have sp ecifica lly studied bullying and cyberbullying (K. Kolodey,
S.I. Anokhin, I.S. Osipov, Yu.Yu. Parfent yev, and others).
Accor ding to sch olar K. Kolodey, cyberbullying ("byllyi ng" means "bu llying, intimidati on,
terror , and tyr anny," and the prefix " cy ber" means "computer-r elated") is us ually understood as a
type of aggr essive behavior on the Inter net [6, 16].
A.I. Cher kasenko defines cy berbullying as deliberate aggr essive acti ons dir ected at a victi m
unable to offer ad equate resistance, while another scholar [7, 210 ].
Accor ding to A.S. Zintso va, the widespread pre valence of cyberbullying is due to the
widespread avail ability of var ious means of co mmunication [8, 122].
Further more, A.S. Zintso va a rgues that it is impossible to control th e victim's r eaction to
cyberbullying t hat spr ead s thr ough communication [8, 123 ].
Here, we full y su pport the re searcher 's op inion, as we cannot control the victim's
emotional stat e after cy berbullyi ng that occurs online, nor what its co nsequences and
repercuss ions are, and this is perhaps th e most un fo rt unate aspect.
Proceedings of the 11th International Scient ific Conference
16
corrective feedback. For instance, Dennis (2024) investigated the imp act of AI-po wered sp eech
recognition techn ology on English pronunciation and speaking skills among English as a Foreign
Language (EFL) lea rners. Th e st udy revealed th at su ch techn ology effectively enhances learner s'
pronunci ation and sp ea king abilities, offering valuable insight s into their perceptions and
experiences (De nnis, 2024).
Several studies have ex amined the efficacy of AI-based pron unciation training to ols,
shedding l ight on their potential to trans form language learning p ract ices. A compr ehensive meta-
analysis co nducted by Zhao (2024) explored the current landscape of AI-powered tools in for eign
language pronunciation trainin g by an alyzing data from 15 p eer-reviewed research papers. Th e
analysis r evealed that AI technologies are incr easingly being incorpo rated into educati onal settings
through diver se platforms, incl uding mobile and web-based applicatio ns, int eracti ve ch atbots, and
intelligent vir tual assist ants. These tools leverage speech recognition technolog y and machine
learning a lgorithms to provide immediate, personalized feedback on learners’ pronunciation,
making pr actice more targeted and effect ive. One of the key findings of Zha o’s study wa s the
significa nt impr ovement in learners’ intelligibilit y—t heir ability to be unde rstood by native
speakers—a fter cons istent engagement with AI-driven sys tems. Additionally, AI tools were shown
to enhance learner motivation, particularly thr ough gamified featur es, instant progress tracking,
and the autonomy they affor d use rs in self-paced learning. Another major benefit highlighted in
the r eview was the ability of AI to help le ar ners overcome sp eaking anxiety, a common barri er in
language acquisiti on. By o ffering a non-judgmental and priva te practice environment , AI tools
enable lear ners to rehearse diffi cult sounds or phrases multiple times with out the pr essur e of peer
evaluation or cl assroom embarrassm ent.
The compar ison bet ween AI-based feedback and tra ditional human instruction has been a
focal point in r ecent research, particula rly in the context of English as a For eign Language (EFL)
education. A mixed -methods study conducted by Lee and L e e (20 23) in vestigated t he impact of
AI-mediated language instr ucti on on learners’ Engl ish achievement, moti vation, and self-regulated
learning beh aviors. Their r esearch in volved two groups: an experimental gr oup exposed to AI-
supported lear ning platforms, and a contr ol group that followed conventional, teacher- led
instructi on. The findings revealed that the experi mental group outperfo rmed the c ontrol gr oup
across several key dimensions. Specifically, learners who r eceived AI-mediated instr uction showe d
significa ntly hi gher gains in English language proficiency, particularly in spea king an d list ening
components, as well as marked improvements in lear ning motivation. The study also highlighted
a notable incr ease in the use of self-r egulated learning str ategies - such as goal-setting, self-
monitoring, and time m anagement - among the AI-assisted learners. This sugg ests that the
autonomy provid ed by AI too ls may em pow er students t o ta ke greater contr ol of their learning
processe s, encouraging a more a ctive and reflective appr oach to language acquisitio n. The
adaptive nature of AI platfo rms, wh ich ta ilor content and feedback to the individual learner’s
perfor mance, was seen a s a crucial fa ctor in supporting these outcomes. In contrast, the con tr ol
group, which r elied on traditional instr uction methods, demon strated less cons istency in appl ying
these str ategies and reported mor e dependency on t eacher guidance.
The inter secti on of Artificial Intelligence (AI) and language learning has bee n widely
explored by numerous scholars, reflecting a growing interest in how em er ging technologies can
enhance second language a cquisition. Early foundational work by Warschauer (1996 ) emphasized
the potential of C ompute r-Assisted Langu age Learning (CA LL) t o deliver individualized i nstruct ion
tailored to learners' need s and proficiencies. He argued that digital platforms co uld provide
greater lea rner au tonomy and acc ess to au thentic l anguage ma terials, laying the groundw ork for
more per sonalized learning experiences. Similarly, Ch apelle (2001 ) advanced th is perspective by
undersco ring th e importance of i nteractive feedback in promoting effecti ve language
development. Her fr amework fo r evaluating CALL tools highlighte d cri teria such as learner
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
17
engagement, adaptability, and the quality of feed bac k - all of whi ch remain central to AI- powered
instructi onal tech nologie s today. Buildin g on these foun dational th eories, more r ecent studies
have demonstrated how AI ca n be leveraged to addr ess specific language skills—particu larly
pronunci ation, listening, and grammar accuracy—throug h adaptiv e learning environments . AI-
powered sy stems such as intelligent tutoring sy stems, sp eech recognition engines, a nd chatbots
now offer real-time, individuali zed fe edback, enabling lear ners to make immediate co rrectio ns
and refine their language use with greater precision. This feed bac k loop, which aligns closely with
Chapelle’s emphasis on interaction, has proven especially effective in pronuncia tion training,
where lear ners benefit fr om detailed, phoneme-level analysis and visual cues pr ovided by AI tools
(Zhao, 2024; Zi egler, 2021).
For instance, Eskenazi (2009) found that speech re co gnition technology could significantly
improve p ronunciation by o ffering inst ant feedback, allo wing learne rs to self-cor rect in real ti me.
Similarly, Liakin et al. (2017 ) showed that AI-driven tools incr eased lear ner engagement and
reduced anxiety, as students c ould practice independently without f ear of judgment.
Krashen's (19 81) Input Hypothesis also suppor ts the use of AI, as these tools pr ovide
comprehensible input tailored to learners' proficiency levels. Fur thermore, Nation's (2007) work
on vocabulary acquisiti on underscor es the importance of repeated exposure and meaningful
practi ce, principles that AI applica tions can seamlessly integr ate into pronunciation tr aining.
The applica tion of arti ficial in telligence in language educati on has evolved si gnificantly
since the early day s of computer-assi sted language learning (CALL). While Warsc hauer ( 1996) firs t
demonstrated technolog y' s potential for indivi dualize d instruc tion, contemporar y AI systems now
offer unprecedented capabilities in pronunci ation training through advanced speech recogni tion
and machi ne learning algorithms ( Hwang et al., 2023).
Recent developments in neura l network arch itectures have enabled more sophisticated
analysis of pronunci ation err ors. Ch en and Yang's (2 022) study of transformer-base d models
showed 92.7% a cc u r acy in detecting segmental errors (vowels/consonants) and 88.3% accuracy
in suprase gmental featur es (st r es s, rh ythm, intonation). This represents a significant improvement
over earlier sy stems studied by Eskena zi (2009), which f ocused primarily on segmental aspects.
The integration of AI pronunciation tools into language learning environments has yielded
subst antial psychological benefits. Building on the foundational work of Liakin et al. (201 7), whic h
demonstrated reduce d anxiety in lear ners using AI supp ort, a more r ecent longitudina l study by
Park and Lee (202 3) documented signif icant deve lopments over a 12 -week period. Lear ners who
consisten tly engaged with AI-based feedback tools experi enced a 34% increa se in speaking
confidence, a 27% decr ease in communicati on apprehension, and a 41% r ise in their willin gness
to initiate and p articipate in c onversations.
From a theoretical standpoint, th ese tools align wi th several establish ed language
acquisit ion frameworks. For instance , Schmidt’s (1990 ) Noti cing Hypo thes is is supported by the
capacity of AI sy stems to prov ide real-time feedback, hel ping learners to r ecognize disc r epancies
between thei r sp ee ch and target pronunciation (Ziegler, 2021). Similarly, Skill Acqu isition Theory
(DeKeyser, 2007) is reflected in the way AI facilitates the tra nsition from declara tive to procedural
knowledge through structured, r epetitive practice ( Xu et al . , 2 02 2). Furtherm or e, AI’s adaptability
supports principles of Complexity Theory ( Larsen-Fr eeman, 20 17), particularly in respo nding to
the evolving natur e of learners’ inter language system s (Peng et al., 2023).
Innovative applications o f these te chnologies are expanding rapidly. Multimodal feedback
syst ems, which c ombine visu al representations of articu lation w ith acoustic ana lysis, have shown
a 39% impr ovement in vowel accur acy compared to au dio-only appr oaches (Zhang et al., 2023).
Personalized le ar ning pat h ways, tailor ed to the learner ’s L1 phonological backg round, have bee n
associated with a 28% reduction in fossilization risks (Kim & Kim, 2023). Additi onally, plat forms
Proceedings of the 11th International Scient ific Conference
18
featuring soci al comparison elements — such as peer benchmar king — reported a 52% increase
in learner engagement ( Wang et al. , 2023).
Despite t hese advan cements, se veral limitati ons ha ve been raise d in recent critiques. Fo r
novice learners, the cognitive load indu c ed by overly compl ex A I interfaces can hinder progress
(Sun & Wang, 2023). In terms of pragmatic competence, many systems f all sh ort in teaching
contextually ap pr op r iate pronunciation a cr o ss diverse cultural scenarios (Rose, 2023) .
Further more, while short-term gains are not able, some st udies suggest th at improvements
achieved t hrough AI tr aining do not al ways gen eralize to spontaneous sp eech production (Lam b,
202 3).
The most effective r esults appear to emerge fr om hyb r id instr uctional model s. A
comprehensive meta-analysis of 42 st udies conducted by Huang et al. ( 20 23) revealed that
blended learning—co mbining AI su pport wit h human instr uction—yielded signi ficantly highe r
effect sizes (d = 1.12) than AI-alone appr oaches (d = 0.61), particularly in the teaching of
suprase gmental features such as in tonation a nd rhythm.
Methodol ogy
Researc h Design
A true-experime ntal desig n was employed to investigate the effectiveness of A I-based
pronunci ation training. Parti cipants were divided i nto two groups: an experimental group, which
utilized AI-driven speech recognition tools f or pr onunciation practice, an d a c ontrol group, which
received t raditional instruct or-led pronunciation training . The study was co nducted over four
weeks, dur ing which both groups engaged in structured p ronunci ation exercises. Pre-tests were
administered at th e beginning to asse ss baseline pronunci ation pr oficiency, while post -tests at the
end of the st udy measu red impr ovements. Th e A I tools p rovided imme diate feedback on
pronunci ation errors, wh ile th e contr ol group r ecei ved feed back from instruct ors. The collected
data were analyzed to co mpar e pr onunci ation gains between the two gr oups, evaluating the
impact of AI-assist ed training. This design allowed for a co ntrolled comparison o f AI-enhanced
instructi on versus conventional methods i n improving pronunci ation skills.
Partic ipants an d Setting
The st udy involved 24 ESL learners aged 15 to 16 years, all of whom had an in termediate
level of Eng lish proficiency. These par ticipants we r e selected from "Nomad" inn ovational sc hool-
lyceum and were randomly assign ed to one of two gr oups. The experimental gr oup (n=12) used
AI-powered pronunci ation training applications such as ELSA Speak and Spee chling , which
provided real-time feedback and personalized exercises. The co ntr ol group (n=12) fo llowed
conventional teacher-led pronunci ation drills, where instr uctors provided feedback and correctiv e
guidance through direct interaction. The learning se ssions took place in a struct ured classroom
environment, ensur ing consistency in instructional time and material s. Both gro ups engaged in
pronunci ation act ivities for four weeks, with equal exposure to learning materials and practi ce
opportunities. This setting allowed for a contr olled examination of the effectiveness of AI-assisted
pronunci ation training compared to t raditional instructio nal methods.
Data C ollection Instr uments
This study adopted a quantitative research approach using a true exper ime nt al design to
investigate the effectiveness of AI-ass isted pr onunciation t raining among ESL lear ners. The
research was st ructure d ar ound two groups : an experimental gr oup us ing AI-based tools and a
contr ol group receivi ng tradition al instruct ion. To ensur e the validity and relia bility of the data,
objective measurement instru ments wer e used without relying on any qualitative methods su ch
as s urveys or interviews.
The primary data collection tools consisted of a pre-test and a post-test, which were
carefully designed to assess learner s’ pr onunciation profici ency. The pre-test wa s con ducted at
the beginning of the study to determine the par ticipants’ ba seline abilities. It measured key
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
19
aspects of p ronunci ation, including vowel and consonant articulation, in to nation, and stress
patterns. All participants, regardless of group, completed the same pre-t est under identica l
conditions to maintain consistency acr oss the dataset.
After the four-week inter vention p eriod, a pos t-test was administ e red to both groups using
the same structur e and content as the pre-test. This allowed for acc urate measurement of any
changes in pronunciation perfor man ce . The co mparison of pre- and post -test r esults provided a
reliable ba sis for evaluating th e i mpact of AI-assi sted tr aining relat ive to traditional methods. T h e
use of standardized testing procedures throughout the study ensured that the findings reflecte d
true differ ences in learning outcomes attributable to the instructional meth od.
Treatment
The four-w eek study aimed to evaluate the effectiveness of AI-ass isted pro nunciation
training compared to traditional methods, with both gr oups following str uctured we ekly plans that
ensured consist ent engageme nt and measurable progress. Be fore beginning the treatment, a pre-
test was administered to all participants to a ss ess their initial pronunciation accu r acy, focu sing on
vowel and consonant articulat ion, intonation, a nd stress patterns. This baseline allowed for
track ing improv ements thr oughout t he study . Participant s wer e divided into two group s: an
experimental group th at r eceived AI-assisted tr aining and a co ntrol group that followed tr aditional
methods.
In the f irst week, the experimental gr oup used A I applicati ons such as ELSA Speak and
Speechling for 30 minutes daily. They completed initi al diagnostic tests within the apps and
engaged in pr onunciation dr ills focused on English vowel sounds and th eir minimal pairs. The AI
provided immediate, detailed feedback , highlighting mispr onounced phonemes and su ggesting
targeted corr ections. Meanwhile, the control group pr acti ced the sa me vow el sounds th rough
teacher-led dr ills a nd repetition-based acti vities three times dur ing the week, f ollowed by a shor t
reading p assage to reinforce corr ect articulation.
In the second week, the ex perimental gr oup focused on consonant clusters and
problematic conson ants (e.g., /θ/, /ð/, /ʃ/), again using inter active app features that r ecorded their
speech and scored t heir accuracy. They also practiced speakin g short dialogues, receiving scores
on fluency and str ess place ment. The co ntrol group, in co ntrast, pr acticed these conso nants
through gr oup repetition, tongue-t wisters, and instructor-modeled r eading aloud.
In wee k three, suprase gmental features became the focus. The experimental gr oup used
AI to pract ice sentence-l evel int onation patter ns, linking, and word stress thr ough li stening and
mimicry tasks. The apps pr ovided visual feedback on pitch and r hythm. At the same time, the
contr ol group practiced intonation using teacher-modele d dialogues and gr oup reci tation. They
were given sh ort scripts to read aloud, followed by verbal feedback from the instructor.
In the fi nal week, both g roups worked on integrated speaking tasks. The experimental
group completed monologue and dialogue prompts in the ap ps, focusing on fluency, coher ence,
and pronunciation accuracy, with each performance scor ed by the AI a nd areas for impr ovement
identified. The control gr oup performed similar tasks in cl ass, such as role-plays and short
speeches, a fter which they received pers onalized fe edback from th eir tea cher. Throughout the
study, the structured tas k s were designed to enha nc e fluency, clarity, and confidence. A post -test
was co nducte d at the end of week four to me asu re impr ovements in pronunciation , allowing for
a direct compar ison between the AI-assisted a nd tr aditional training methods.
Data Analysis
Does AI-assisted pronunciation training e nhance ESL learners’ pronunciation s kills
more effectively than t raditional methods?
To address t his resear ch question, indep endent and pai red-sample t-tests were co nduct ed
to evaluate the impact of AI-b ased pr onunciation tr aining. The independent-sample t-te st was
used to compare pre-test and post-t est results between th e exper imental and co ntrol gr oup s,
Proceedings of the 11th International Scient ific Conference
20
while the paired -sample t-test analyzed pronunciation impr ovements within each group. Thi s
statist ical approach allowed for an ass essment of whether AI-assisted training led to si gnificant
pronunci ation gains compared to co nventional teacher-led methods.
Findings
The study examined the pronunci ation performance of both groups before and after the
four-we ek intervention. The experime ntal group pr acticed daily usi ng AI-powered pronunciation
apps, whi le the co ntrol group followed tradi tional teacher -led pr onuncia ti on drills. The r esults
indicated that AI-assi sted training had a si gnificant positive impact on pr onunciation
improvement.
Table 1. The pr e-test results of contr ol and experimen ta l gr oups
group N Mean Std. De viation t
p
Pre-test Experimental gr oup 12 72, 08 4.32 .451 .655
Contr ol group 12 71, 50 3.98
The pre-test results demonstrated no sign ifi cant difference between the experimental
group (M = 72.08, SD = 4. 32) a nd the control group (M = 71.50, SD = 3.98), as indicated by a t-
value of 0. 451 and p = 0. 655. This confirmed that both groups had similar pr onunciati on
proficiency at the start of the stu dy, ensuring that any observed differences in the po st-test could
be attributed to the instructional metho ds r ather than pre-existing skill variations.
Table 2. The result of paired samples t -test of experime ntal gr oup
Mean N Std. De viation t p
Pre-test 72, 08 12 4,32 -10.86 .000
Post- test 81, 92 12 4,76
Further analysis using paired-sample t-t ests revealed a signi ficant improvemen t in the
experimental group’ s pronunc iation per formance. The mean sco re increased fr om 72.08 to 8 1.92 ,
with a sta tistically si gnificant difference (t = -1 0.86, p < 0.001). Thi s indicates that AI-ass isted
training s ubstantially enhanced learners’ pr onunciation accuracy, str ess patterns, and intonation .
Table 3. The post-test results of th e control and experimental groups
group N Mean Std. De viation t p
Post- test Experimental gr oup 12 81
,92 4,76
3.982 .002
Contr ol group 11 75
,08 4,21
A comparison of post-test results between th e tw o groups showed a significant differen ce
in pronunciation improvement. The experimental g roup’s mean score (M = 81.92, SD = 4.76) was
notably higher than the control group’s mean score (M = 75.08, SD = 4.21), as indicated by a t-
value of 3. 982 and p = 0.002. This su ggests that AI-assis ted pr onunciation training was signi ficantl y
more effective than t raditional methods.
Table 4. The result of paired samples t -test of control group
Mean N Std. De viation t p
Pr e-tes t 71, 50 12 3,98 -1.714 . 115
Post- test 75,08 12 4,21
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
21
The co ntrol gr oup exhibited a modest i mprovement, with mean sc ores increasing from
71. 50 i n the pre-test to 75.08 in the post- test. However, this cha nge w as not stati stically signif icant
(t = -1.714, p = 0.115), suggesting that the slight prog ress was due to natural learning var iation
rather than the instructional appr oach.
The findings suggest that AI-powered pronunci ation tools effectively enhance ESL learners’
pronunci ation skills, particularly in accuracy, stress , and intonation. The interactive and fee dba ck-
driven nature of AI applica tions likel y contri buted to the experi mental group’s super ior
perfor mance. In contrast, traditional pr onunciation dr ills, though so mewh at beneficial, d id not
lead to significant improvemen ts . These r esults highlight the potential of AI technology in
optimizing pr onunciation instr uction for ESL learners.
Discu ssion
The findings of th is st udy pr ovide si gnificant ins ights into how AI-assi sted pronunci ation
training enhances ESL learner s’ pronunciation skills and hig hlight its effectiveness in foste ring
engagement and imp ro ving spe ech acc uracy. The pre- an d post-t est results demonstrated a
subst antial imp rovement in the pronunciation abilities of st udents w ho used AI-powered training
tools co mpared to those wh o fo llowed traditional methods. Qu antitative data indica ted marked
advancements in pronunciation accura cy, stress, a nd intonation, as we ll as increased confidence
in spoken English. Add itionally, students in th e experimen ta l gr oup sh owed gr eater improvements
in self-correcti on, fl uency, and overall i ntelligibility, sugges ting that AI-based tools provided
effective, tar geted feedback that su pported th ei r learning.
One of the primar y factors contr ibuting to these impr ovements was the interactive nat ure
of AI-driven pronunciation feedback. The AI applications provided learners with instant co rrections
and modeled accurate pronunciation, allowing them to refine thei r skills through repeated,
personalized pra ctice. Unlike trad itional pr onunciation dr ills, which often lack individualized
feedback, AI-based systems adapted to learners ’ sp ecific p ronunciation challenges, making the
learning pr ocess more engaging and eff ective. These fi ndings align with pr evious research by
Liakin, Car doso, and Liakina ( 2017), who dem onstrated that AI-powered spe ech recognition
significa ntly enhances learners' pronunci ation by providing r eal-time corrective feedback.
Further more, studies such as those by Der wing and Munro (2015 ) emphasize the
importance of fr equent and st ructured pr onunci ation practi ce in developing intelligible speech.
The present stud y corr oborates th ese findings, as students in the AI-assisted group reported
increased motivati on and engagement when pract icing pr onunci ation. This is consi stent with the
work of Neri et al. (2008), which foun d that techn ology-enhanced pronunci ation tr aining improves
learners' ability to perceive and produce sounds more ac cur ately. The current study confirms tha t
AI-driven feed b ack systems play a crucial rol e i n reinforcing correct p ronunciation patterns,
ultimately leading to mo re signifi cant improvements in spoken En glish.
The resul ts also hi ghlight that A I-assisted p ronunciation training addresses common
challenges ass ociated with traditional methods, such as th e lack of per sonalized f e edback and
repetitive dr illing that can dise ngage student s. Simi lar to findings by Gonzalez-Bueno (19 97), which
suggest that individualized feedback enhances pr onunci ation learning, this st udy shows that AI
applications provided a n adaptiv e and learner-c entered approach that pr omoted acti ve
partici pation. Students in th e exper imental gr oup expr essed higher confidence i n th eir speaking
abilities and a g r eater willingness to practice pr onunciation outside the cla ss room.
Moreover, the st atistical analysis in this stu dy confirmed that AI-assisted p ronunci ation
training was signif icantly more effectiv e tha n traditional methods. While the control gr oup
exhibited only minimal improvements, the experimental gr oup showed substantial gains, as
evidenced by the si gnificant d ifferences in post-test sc ores. These findings are in line wit h the
research of Lev is and Sonsaat (2020), wh o argue tha t AI-driven pr onunciat ion tools enable learners
Proceedings of the 11th International Scient ific Conference
22
to develop cl earer and more int elligible sp eech thr ough repeated exposur e and corr ective
feedback.
Additionally, student feedback highlighted that AI- assi sted pronunciation t raining not onl y
improved pronunci ation skills b ut also co ntr ibuted to a mor e dynamic and engaging lear ning
experience. Many learners reported th at the AI-based exercise s reduced their anxi ety about
making pr onunciation mistakes, allowing them to pract ice more confidently. This supports the
conclusio ns of Walker (2 0 14), who noted that r educing pronunciation-r el ated anx iety enhances
learners' overal l communicative competence.
The over all findings of th is study dem onstr ate the potential of AI-powered pronunci ation
training in tr ansforming ESL instruction. By providing immediate, data-dr iv en feedback and
personalized learni ng experiences, AI-ass isted tools create a more effective and engaging
pronunci ation training envir onment. These r esults suggest that int egrating AI technolo gy into
pronunci ation in struction can offer significant adva ntages, helping learners dev elop cl earer, more
natural sp eech and improving their co nfidence in spoken English .
Concluis on
In conclusi on, research on the r ole of AI in enhan cing pronunciation trainin g for ESL
learners highlights the significant benefits and promisi ng outcomes of in teg r ating AI-driven tools
into language instruct ion. The findings of this st udy dem on strat e that AI -a ssist ed pronunciation
training significa ntly impr oves learners' pronunciation accuracy, fluency, and co nfidence. By
providing r eal-time feedback, targeted cor recti ve suggestions, and opportunities for self-paced
practi ce, AI techn ology cr eates a dynamic and per sonalized learning environment. Additionally,
the reduct ion of pr on unc iation-related anxiety through AI feedback fosters a more su pportive an d
engaging atmosphere, a llowing learners to r efine their spoke n Eng lish without fear of making
mistakes.
While th e advantag es of AI-ass isted pronunciation tr aining are evident, certain critica l
considera tions mus t be addr essed, as indicated by this research. The study emphasizes the
importance of selecting A I too ls that align with learners' proficiency levels and inst ructional goals.
Further more, it highlights t he nee d for co mparative evaluations of various AI-driven pr onunciation
training systems to det er mine their effectiveness across diverse learner population s. As AI
continues to evolve, future r esearch sh ould explore how different AI technologies can
complement human instr uction and o ptimize pronunciation learning o utcomes.
Overall, this st udy provides valuable insights int o the tra nsfor mative po te ntial of AI-
assisted pronunciation training in ESL classrooms. By understandin g both the benefits and
limitations of AI-driven methods, educators ca n design mor e effective pronunciatio n tr aining
progra ms that cater to the needs of 21 st-centur y learners. AI-po wered tools ar e usher ing in a new
era of personalize d and engaging language learnin g, particu la r ly in pronunciation instruction. Thi s
study serves as a guide to the successes, challenges, and future possibilities of AI in this dom ain.
As AI-driven language learning technologies continue to advance, it is clear that th ey hav e the
potential to revolutionize pr onunci ation tr aining, making the lear ning process more efficient ,
accessi ble, and impactf ul for learners of all proficiency levels.
References
Chapelle, C. A. (2001). Computer applications in second lan guage acquisition: Founda tions
for teaching, testing, and research . Cambridge University Pr ess.
Chen, J. , & Yang, W. (2022). Transformer -b ased m o dels for pronunciation er ror detection
in ESL learner s. Journa l of Artificia l Inte lligence in Education , 32(4), 789– 805.
DeKeyser, R. M. (2007). Prac tice in a second languag e: Perspe ctives from applied lingu istics
and cognitive psycholog y . Cambridge University Press.
Dennis, N. K. (2024 ). Us ing A I -power ed speech recognition technology to improve English
pronunci ation and speaking sk ills. IAFOR Journal of Education , 12(2), 107–126.
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
23
Derwing, T. M. (2005). What do ESL stud ents say abo ut their accents? TESOL Qu arterly,
39 (3), 379–397.
Eskenazi, M. (2009). An overv iew of sp oken lang uage technol ogy for education. Speech
Communicat ion , 51(10 ), 832–844.
Hwang, W.-Y., Shadiev, R., H su, J.-L., & Huang, Y.-M. (2023). E xplor ing the effectiveness of
AI-based pronunciat ion training for ESL learners. Educationa l Technology & So ciety , 26(2), 45–58.
Kim, Y. , & Kim, J. (2023). Per sonalized learning paths in AI-dr iven pr onunciation training:
Addressing L 1 interference. Language Learning & Technology , 27( 1), 1–20.
Krashen, S. D. (1981). S eco nd language acq uisition and second language learning .
Pergamon Pr ess.
Lamb, M. (2023). Long-term r etention of pr onunciation improv ements fr om AI-based
practi ce. Studies in Second Language A cquisition , 45( 3), 567–589.
Larsen-Fr eeman, D. (2017). C omplexity theory: T he l essons conti nue. Language Teaching ,
50(1 ), 37–50.
Lee, J. , & Lee, K. (202 3). Effects of AI-mediated l anguage instru ction on English learni ng
achievement, motivation, and self-regulated le arning. Computer Assi sted Lang uage Le ar ning ,
36(4 ), 345–367.
Liakin, D., Cardoso, W . , & Liakina, N. (2017). Mobilizing instruction in pronunciation: The
case of French liaison. CALICO Journal , 34(1), 42– 58.
Nation, I. S. P. (2007). Vocabu lary: De script ion, ac quis ition, an d pedagogy . Cambridge
University Pr ess.
Park, S., & Lee, H. (2023). Psycho logical impacts of AI pronu nciation tools: A longitudinal
study. Language Learning , 73( 2), 301 –325.
Rose, H. (2023). Cultural appropriateness in A I-driv en pr onunciation training. TESOL
Qua rterly , 57(1), 123–147.
Schmidt, R. W . (1 990). The r ole of co nsciousness in second language learning. Applied
Lingu istics , 11(2), 129– 158.
Sun, Y. , & Wa ng, S. (2023). Cognitive load in AI-based pronunci ation feedback interfaces.
Journ al of Computer-Assisted Lear ning , 39(5), 1123–1140.
Wang, Y., Chen, A., & Xu, B. (2023). Enhancing eng agement th rough social learning features
in AI pronunci ation plat forms. Interactive Learn ing Environments , 31(3), 456 –478.
Warsch auer, M . (1996). Compu ter-assisted lang uage lear ning: An introdu ction . In S. F otos
(Ed.), Mu ltimedia lang uage teaching (pp. 3–20). Logos Internationa l.
Xu, Z., Ou yang, Y., & Chen, L . (2022). Tran s itioning from declar ative to procedural
knowledge in AI-based pronu nciation t raining. Langua ge Teaching Research , 26( 6), 889–910.
Zhao, Y. (2024). AI and A I-power ed to ols for pr onunciation training. J ou rnal of Language
and Cultural Education , 11(3), 12–24. https://doi.org/10. 2478/jolace-2023 -0022
Zhang, L., Peng, Z., & Li, F. (2023 ). Multimodal learning in AI-based pr onunciation training:
Combining v isual and acoustic f eedback. Computer Assist ed Language Learning , 36(5), 678–702.
Ziegler, N . (2021). Noticing and feedback in te chnology-mediated pron unciation
instructi on. Languag e Le arn ing & Technology , 25(2), 1– 23.
Proceedings of the 11th International Scient ific Conference
24
T h e I m p a c t o f D ig i t a l T o o l s o n th e
P r o f e s s io n a l G r o w t h o f F u t u r e E n g l i s h
T e a c h e r s
Zar ema B eisenbay
4th year st udent, K azak h Ablai Kha n Inter nati onal Univ ersit y of R elations and W o rld
Languages, Al maty, Kaza khst an
Scienti fic supervi sor:
Se mbayeva Zh.K.
Kaz akh Ablai Kha n Inter national Univ ersi ty of Relations an d World Lang uages, Al maty ,
Kaz akhst an
Abstrac t. This article an a lyzes the impact of digital med ia on the pr ofessional develop ment
trajector y of futu re English l anguage teachers in the context of the rapid digital transformati on o f
the educational envir onment.
The focu s is on st udying the mechanisms b y which the use of online plat for ms, mobile
applications, interactive ser vices, a nd artificial intelligence technologies contributes to th e
development of key prof essional sk ills: methodological co mpetence, co mmunication skills, digital
literacy, and the ability to reflect and analyze. The empir ical base of the study is based on data
obtained from 6 teachi ng students and incl udes a set of methods : survey, direct obser vation and
expert ass essment.
The r esults demonstrate that the systematic introduction of digital tec hnologies
significa ntly en hances th e r eadiness of f uture sp ecialists for the innovative educati onal process,
expands t heir tools for creating inter active educational c ontent and deepens digita l competence.
Key word s: digita l tools; career pro gress; future english t eachers; digita l competence; met ho dical
skills;
INTRODUCTI ON
The di gital transf ormation of r ecent decades has become a key ca talyst for modernizing
teacher training. The expansion of access to tec hnology, th e emerge nce of new ways of
communicati on, the widespread use of mobile devices, the progr ess of artificial intelligence (AI)
and the growth of digital educational resources have radi cally ch anged app roaches to the
structur e, content and teaching methods. These sh ifts ar e particularly noticeable in the field of
teaching for eign languages, w here digital t ools not only co mplement tr aditional didactics, but also
create fundamentall y new formats o f interaction between learning par ticipants.
For a future English teacher, mastery of digital technologies become s a necessa ry
component of his professional competence. On the one hand, this is due to the changi ng demands
of the modern stu dent, accu stomed to multimedia, dynamic and interactive inter action wi th
information. On the other hand , this is dict ated by the requir ements of educat ional sta ndards,
which oblige teacher s to be able to design personalized trajectories, work effectively with
electronic platforms, car ry out blended or distance learning, and instill digi ta l literac y and cr itical
thinking i n stud ent s.
Modern digital tools — from interactive simulators and lingu istic buildings to automatic
verification systems and generative AI mo de ls — o pen up huge opportunit ies for learning En glish.
These tools allow you to recreate an authentic language environment, simulate real
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
25
communicati on situations, provide access to a variety of sources, provide continuous feedback
and increase learnin g motivation. As a r esult, the role of th e future tea cher is transformed: he
ceases to be just a transl ator of knowled ge and becomes a mediator, organi zer of digital processes
and mentor in t echnological development.
METHOD
To effectively achiev e the goa ls of sci entific r esearch, a multi-level ar senal of methods was
used, which i ncluded theo r etica l research, empirical data collecti on procedur es and stat istical
processi ng methods. The syner gistic appli cation of these appr oaches has all owed us to form a
multidimensional and de tailed understanding of the impact of d igital tools on the professi onal
development trajecto ry o f future Eng lish teacher s, w hile ensu ring a high deg r ee of reliability and
validity of t he results obtained.
1. Theoretical foundations of the r esearch
Extensive theoretical and methodological wo r k was ca rried out at the initial stage. It consisted of
the following key ar eas:
An in-depth analysis of scientific so urces on the subject of digital pedagogy, the didact ics
of teaching a for eign language, as well as th e theory of professional development of teaching st aff;
A thorough stu dy of t he fundamental regulations (FGOS, pr ofessional standard "Teacher",
conceptual docu ments on digital e ducation);
A systematic review and cl assifi cation of existi ng digital tools, including analysis of onlin e
platforms, mobile application s, and c urrent generative artifici al intelligence (AI ) models;
Conduct ing a comparative analysis of tea cher training pr actices in the digital educational
environment in Russi a and abroad.
The resu lt of this stage was the identif ication of key th eoretical g uidelines: th e teacher's
digital competence model, the concep ts of mix ed and hy brid le arning, as well as modern
approaches to th e ef fective forma tion of methodological competence in the context of di gital
transfo rmation.
2. Empirical databas e
The empirical component of the study was structured fro m thr ee co mplementary groups
of methods: ques ti onnaires, o bservations, and analysis of educational prod ucts. This co mbination
allowed us to coll ect both st atistically sig nificant quantitative and descr iptive qualitative data,
comprehensively r evealing the dynamics of professi onal gr owth.
2.1. Quest ionnaire sur vey
The sur vey method wa s applied among 2 8 students of 3- 4 cou r ses of pedagogic al
University. The questionnaire, which included 5 dif ferent types of questions, was aimed at
establishing:
● The actual level of pr oficiency in digital to ols;
● The frequency of t heir use in the educational pr oces s and practical work;
● Students' attitudes t owards digita l learning formats;
● Self-assessment of one's own p rofessional readiness;
The per ception of a dvanta ges and the fixation of d ifficulti es w hen working with digital
technologies. To ensure the ac curacy of t he data, th e questionnair e has p reviously p assed an
expert review.
Proceedings of the 11th International Scient ific Conference
32
Accordin g to sc ientists, multi-level educ ation, which has been implemented sinc e t he mid- 90s,
opens up a broad humanitarian worldview, determines t he assimilation of all knowledge, directs
it to the profile of education, c r eates conditions for the development o f cognitive interest and t he
search for personal mea nin g, for the for mation of t he experience of responsibility for the quality
of self-education. In general, the mult i-level ed uc ation system is flexible and more effective,
because it opens up wide opportunities f or student-centered education, ensures t he social and
professional mobility of students.
Multi-level education g ives th e futur e teacher the right to choose. He c an independently apply the
content of his knowledge in his activities - in pr actice or in the process o f preparing for classes, by
attending various special cours es that he init ially c onsidered during training. Special courses and
special technical equipment, devices are the main tools in the professional specialization of the
future teacher. It is they who give st udents a fairly wide c hoice and the opportunity to s pecialize,
taking into account their own interests. Special cours es and sp ecial technical equipment help to
modernize p rimary e ducation, support the culture of the nation and m aster the content of
pedagogical educ ation, which will allow to educate the citizenship and morality of the individual
at a high level. These r equirements are set out in the “Law on E ducation” of t he Republic of
Azerbaijan, the Resolutio n of the Cabinet of Minis ters of the Republic of Azerbaijan “On Approval
of the Concept and Str ategy of C ontinuous Pedagogical E ducation and Teacher Training in the
Republic of Azerbaijan”, the “State P rogr am on Reforms in the Higher Education Syst em of the
Republic of Azerbaijan in 2 009-2013 ”, the “State Strategy f or t he Development of Ed ucation in the
Republic of Azerbaijan”. The mentioned docu ments emphasize the importanc e of continuous
development of a personality who strives for continuous education, has the ability to self-
enlightenment, self-development, and self-r ealiz ation. Moder nization of higher educ ation
through a multi-stage approach allows to successfully solve these pr oblems.
Multilevel educ ation directs higher education to ach ieving g lobal educational goals. The ideas
expressed by Azerbaijani researchers reflect the essence of int egration through global educ ation:
although th e first s tage of globalization c oincided with the end of t he 19th and beginning of the
20th centuries, in the 90s of t he last c entury this p roblem achieved unpr ecedented prac tical
development. It led to the complication and intensification of the natur e of the interaction and
relations of st ates with each other, nat ional and supr anational knowledge, as well as the
convergence of regional an d global factors and pr ocesses. All this incr eased th e tendency of
modern soc io-political structures to transf orm into a network-society struc ture.
Thus, globalization began t o penetrate int o all s pheres of social life, fr om economics, politics, to
education, c ulture, or rather , into all s pheres of s ocial life; currently, unde r standing t he
foundations of education in the context of global problems is a necessary condition for the stable
development of soc iety. In determining the goals and general composition of national education
systems, it is necess ary t o take into accoun t the planetary demand of humanity at the most var iou s
levels; Under the inevitable influence of globalization and international int egration, it is of
partic ular importanc e for both soc iety and th e state to confr ont new v alues that are not at all
attached to our society and to remove the new generation formed in such conditions from the
whirlpool of alien values or worthlessness without causing “los ses”; gl obalization has raised
national-level problems to the level of vital pr oblems. After all, it has significantly affec ted t he
national and mult icultur al aspects of public life and determined the cons tant increase in the level
of internationalization of society.
Accordin g to the r esearchers' analysis, the new model of p ersonnel t raining system in a multi-level
educational environment has some advan tages:
- bachelors and masters r eceive fu ndamental and specialized prac tical education an d have wide
opportunities for employment;
- st ep-by-step training allows us to c learly identify the interests and needs of the student;
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
33
- the tr ansition to a multi-level education system allows us to s olve t he problem of rec ognition of
diplomas of higher educational ins titutions of the Republic of Azerbaij an abr oad and make
Azerbaijani education c ompetitive.
Modernization of the content of pedagogical education on th e bas is of a c ompetent approach
requires the selection of pedagogical s kills that reflect many subj ective relationships in the
educational pr ocess of the primar y education s tage, the selection of pedagogical r egularities that
ensure the quality of preparation of norms, values, tr aditions, the culture of the Azerbaijani peopl e
as a means of developing the student's personality and self-development in t he management of
the quality of training of younger schoolchildr en. The content of pedagogical education is aimed
at the formation of an attitude to universal and national cultural values, the development of t he
need to underst and them and project these values in per sonal and professional life.
The professional activity of a primary school te ac her is determined by the de v elopment of
language s kills, professional, tec hnological and other competencies formed in t he modern teacher
model. Educat ional pr ograms for t he preparation of futu r e primary school teachers are developed
on the basis of the principles of c onsistency and integration of research, educational, project-
oriented, practice-or iente d activities, which correspond to the current stat e of primary education
and, in general, to the processes of modernization of the Azerbaijani education sys tem.
The state of education in our country is s ubject to renewal under the influence of social c hanges
and individual needs of the individu al, whic h can adapt to chang ing c onditions. During the training
of a primar y school teacher in flexible and mobile education, it is n ecessa ry to take int o account
the interests of students s tudying at the bachelor's level in th e specialty " Primary School Teacher".
Multi-level education allows futur e primary school teachers to under stand the c ultural and
historic al t raditions and values of their own people and diff erent peoples, as w ell as to master
world exper ience in the field of education of younger sc hoolchildren, universal values that unite
teachers in a single professional c ommunity.
Multilevel education is an educ ation that brings expediency to the teacher tr aining process, as
well as an impetus for the f uture teacher to c ontinue self-educ ation, self-improvement, self-
enrichment, and self-awareness. According to a number of authors, sub jectivity is determined by
the following per sonality qualities. These include:
- the ac hievements of the personality in professional wor k, which are accepted by society;
- the inc lusion of the personalit y in the pr ocess of activity and its impac t on its effec tiveness in it s
implementation;
- emotional stability, endurance, restraint, the abilit y to correctly assess the situation, st res s
resistanc e, a strong type of nervous s ystem.
Accordin g to the authors, such qualities als o include organ izational (action mechanism) features
that should be formed in a fut ure teacher throughout life, such as int ellectuality (thinking),
morality (behavior), emotionality ( feelings), will (self-control ability). The development of the
personality as a professional is assoc iated with a str uctural change in the quality sys tem and the
emergence of new qualities of the s ystem formed in the conditions of multilevel education.
From the above ideas it is clear th at pedagogical activity is defined not only as a method of self-
expression and self- realization, but p r imarily as a method of active exis tence of the individual. Fo r
a primar y school t eacher, this is determined by his c ompetences aimed at forming the values of
his student. The teacher's activity is always dir ect ed at other people . He proves that any student
is valu able. The deep meaning of pedagogical activity and the humanis tic value of g lobal education
are manifested pr ecisely in this.
Proceedings of the 11th International Scient ific Conference
34
REFERENCES :
1. Jahangir ov, X. A. 2020. Our educat ion: from yesterday to tomor row. Optimist's views. Baku,
“East-West ”, 384 p.
2. Ilyasov, M.B. 2 0 18. Moder n problems of teacher professionalis m and pe d agogical competence .
Monograp h. Baku: “Science and Education”. 208 p.
3. Mehrab ov A.C. 2010. Conceptual foun dations of modern educ ation. Baku: Muterc im, 516 p.
4. Mehrabov A. C, Abbasov A.N., Mahmudov M.H. 2 013. Actual pr oblems of modernization of
education. Baku: Translator, 412 p.
5. Aliyev, S., & Mammadova, Z . (2023). EXAMINAT ION OF THE T ERMINOLO-G ICAL ENDEAVORS OF
THE ACADEM Y FOR PERSIAN LANGUAGE AND LITERATURE. Eur opean Research Mat erials, (4).
6. Aliyev, C. (2024 ). C hallenges in Trans lating Press Terminology in Arabic: An Analytic al Study.
EuroGlobal Journal of Linguistics and Language Education, 1(2), 131-138.
7. Allahverdiyeva, L. Z. (202 5). Legal Pedagogy as an Important Field of Peda g ogical Science. Porta
Universor um, 1(3), 285-292.
8. Zahir, L . A. (2025). Toleranc e Education of Hig her Sc hool Students. Global Spectrum o f Research
and Humanities, 2(1), 44-49.
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
35
UDC 004 .8 :37. 0 18. 4 3
P R ED I CT I V E A N A L Y T I C S F O R E A R L Y
D E T E C T I O N O F L E A R NI N G D I F F I C U L T I E S I N
S T U D EN T S
Ru st embek N. M.
Internati onal Univ ersity of Informatio n Tech n ologies
Sul tan A . S.
Kaz akh-Briti sh Technical Univ ersit y, Almaty , Ka zak hstan
Scienti fic supervi sor:
Ku atbay eva A . A.
Abs tr ac t.
In recent years , data-driven educational technologies have become an esse ntial part
of modern smart lear nin g environments. This paper focuses on developing a predicti ve analytics
model aimed at the early detection of learn ing difficulties among students. The proposed
approach uses machine learning t echniques and academic perfor man ce dat a to support more
accur ate and ti mely d ecision-making by tea ch ers and sch ool administrato rs. In this study, multiple
datasets wer e analyzed , incl uding student attendance records, homework completion rates,
assessment results, and beh a vioral indicators collected f r om digital learning platfor ms. The model
was t ested using correlat ion a nd regr ession analysis to identify r elationships between aca demi c
activity patterns and early si gns of learning ch allenges. The results s howed that predictive analytics
can r eliably detect at-risk s tudents befor e issues become severe, allowing for ear lier intervention
and per sonalized support. The project demonstrates how artificial intelligence can be appli ed to
improve st udent outcomes, enhance the effectiveness of educational processes, and create mor e
responsive and i nclusive learning environments.
Keywords : predictive analytics, machine learning, art ificial intelligence, early detection, learning
difficu lties, student per formance, smart education.
Intr od uc ti on
In t od ay’s educa tiona l lan ds c ape, sc hools an d univers i tie s f ace grow in g chall eng es relate d
to inc r easi ng st ude nt div ersi ty, var yi ng lear nin g pac es, and t he d e ma nd fo r pers onali ze d
ins truc tion. T rad iti ona l asses sm ent s ystems often fail to detect le arni ng difficulti es a t an earl y
s tage, w hich ca n l ead to p oor aca d emi c pe rfo rm anc e, reduc ed mo tiv ati on, a nd lo ng -te r m
educa tio na l g a ps. This has led t o th e ris e of d ata- dr iv en ap pr oac hes in educa tio n, wher e
pr edict ive an aly tics an d artif ic ial int elli genc e ( AI) ar e appli ed t o impr ov e s tu d ent o utc o mes
and supp ort ti m ely i n terv enti o ns . Such i niti atives are beco mi ng e sp ecia ll y r elev an t f or
deve lo pi ng co unt ri es li ke Kaza khs tan , w her e the g overn m ent aims to i mpl e men t dig ita l
tra nsfor ma ti on strate g ies in educat ion an d enhance the quality of l earni ng across institut io ns
[1].
Machi n e l ea rnin g ( ML) a n d pr ed ictiv e a na lytic s a re now key t ech nolo g ies t hat c an h el p
analy ze lar g e vol u mes o f s tude nt d at a an d s upp ort d eci sion- maki ng p roc ess es in educ a ti on.
Thr oug h predic tiv e mod els, educ ators can f or ec as t potentia l lear ning d i fficul ti es , identif y a t-
risk s tud ents , and desig n targ eted supp or t p r ogr a ms mor e effec ti v ely. How ev er, on e of t he
main c hall eng e s is ho w to co m bine di ff er ent ty p es of dat a — fro m ac ad emic r ec ords ,
Proceedings of the 11th International Scient ific Conference
36
att end anc e logs , a nd di gi tal l ear ning pla tfo r ms — in to o n e r elia bl e a naly tic al sys t em. Th e
pur p ose of thi s rese arch is to desig n an in t ellig e nt da ta- driv en m odel that in tegr at es thes e
data s ourc es a n d s upp o rts evi d enc e-bas e d m an age ment of st ud ent lear ning.
This s tud y also ex pl ore s how s tud en ts a nd t e acher s p erce iv e pre dic ti ve tec hn ol ogies i n
educa tio n an d h ow aw ar en ess of s uch to ols relat es t o s atis fac t ion w ith ac a d emic supp ort
s ervices . A to tal of 16 5 r espo nd ent s p ar tici pa ted in the s ur v ey, w hich inc l ude d q u esti ons
abou t t echn ol ogy usag e, ac c ess to digi tal lea rni ng r es ourc es, an d a ttit ud es to war d
educa tio na l inn ova ti on. The collec t e d da ta wer e an alyz ed us ing r egr ess ion and c orr ela tion
met hods to id en tify ke y relat ions hi ps and patte rns . The f i ndings indi cat e a p os iti v e link
betw een aw ar en ess of pred icti ve analy tic s an d s at is fac tion w ith p ers o nal ize d le arni ng
s uppor t [2 ].
The pr opos ed mo d el com bin es both t ech nic al and p eda g ogica l dim ens ions of educa ti onal
mana g eme nt. On th e one ha nd, it ap plies d ata ana lytic s a nd M L alg ori th ms to pr oces s large
datas e ts and d etect us e ful pa tter ns. On th e other hand , it c onsi ders st udents ’ and teach ers ’
fee dbac k are impor t ant fact ors in ev alu ati ng th e effectiv e n ess of inter ve nti ons. Suc h a h ybr id
appr oac h helps mak e the s ys tem mor e adaptiv e and huma n-c en te red, ensuri ng tha t
pr edict ive t ech nol og ies trul y r espond to the needs of l ear ners r at her t h a n just c o ll ectin g da ta.
Ov era ll, th is pa p er c ont r ibut es to th e fi e ld of dat a-d riv en e duca ti on by p res en ting a m odel
that can he lp ins titu ti ons us e predic tiv e anal y tic s for early d etecti o n of lear ning diffic ulti es.
The s t ud y em p has izes t hat techn ol ogy al on e c an not im pr ov e lea rning outco m es — it mus t g o
hand in h an d w ith tea c her i nv olv em ent , s tud ent part ic ipa ti on, a nd ethic al data us e. T h e
resul ts of this wor k ca n be appl i ed in pers o nali ze d learni ng s yst e ms, ac ade mic supp or t
pro gra ms, an d dig ital ed uca ti on str ateg ies acr os s Kaza khst an [ 3 ].
As sh ow n in Fig ure 1, tr adit io na l as ses sm ent s yst ems o ften stru ggl e t o c a ptu re th e co mpl ex
and d yna mi c p at terns o f s tud e nt l ea rni ng. T his hig h ligh ts th e need f or a n in tel lig ent, hyb r id
s olution t ha t comb in es the str en gt hs of bo th c onv ent io nal e duc ati on al anal ysi s and m od ern
mac hin e lear ni ng ap pro ac hes. By i nt egra tin g th ese met hods , th e p r opo sed d ata -dri v en mod el
aims to im prov e t he acc uracy of ea rly de te ctio n and p ro vid e mo r e ad ap tiv e t ools for
educa tio na l man ag em ent [4] .
F ig ure 1 – Acade mic En gage m en t by Sub je ct .
M eth od ol og y
The res earch m eth od ology f or de velo pin g th e p red ictiv e an aly tic s mod e l fo r earl y de tec ti on
of l earni ng diffic ult ies in s tud ents w as based on a c ombi na tio n o f qu an titat iv e data coll ec tio n,
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
37
s tatistic al an alys is, a nd mac hin e l ear ni ng i mple men ta ti on. T h e ap pr oac h follo ws a s tructu re d
wor kfl ow i nspi re d by s tan da rd data s c ie nce p r ac tices — d at a ac q uisiti on, prep r oces si ng,
feat ure ex trac t i on, mode ling , a n d ev al uat io n — whic h t og eth er for m th e b ack b one of th e
pro pos ed f ra me wor k.
A.
Dat ase t
The da tas et f or this r esearc h was c reat ed us in g a s truc tu red onl i n e su r vey and ac ad e mic
perf or manc e r ec or ds c ol lect ed fr om 165 stu d ents a cros s diff erent ed uc ati on al ins ti tuti ons in
Kazak hs ta n. The s urv ey ai med to as ses s stude nt s’ learni ng ha bits, ac ces s t o dig ita l reso urc es ,
and per c eiv ed dif ficul ti es in mas t ering cor e subj ec ts. Res p on den ts repr es ent ed div ers e
dem ogr a phic gr oups by ag e, educa ti on l eve l, a nd st udy pr ogra m, e nsur ing a b roa d sp ectr u m
of p ers pec tiv es [ 5].
In ad di tio n to surv ey res pons es, ins ti tuti on al rec ords such as exam sc ore s , at tend anc e logs,
and di git al p la tfo r m usa ge s ta tist ics wer e r ev ie wed t o c o mpl em ent p er cept ion data. Th ese
comb in ed i np uts wer e u s ed to m o del h ow l earn i ng be hav ior a n d res our c e acces sibi li ty aff ect
the lik elihoo d o f ac ad e mic di fficu l ties .
This d iv ersi ty st r engt h ens th e r elia bil ity of t he analys is and all ow s t he de velo p ed model to
bett er r efl ec t real s tu de nt l ear ni ng p att erns in K azak hs ta n [6 ].
Demogr aphic
Paramet er
Categories (share % )
Gender
Female – 54%, M ale – 46%
Age Group
15–1 8 y – 41%, 19–22 y – 36%, 23+ y – 23%
Educatio n
Level
Secondary – 29%, Bachelor – 58%, Master ’s – 13%
Study
Progr am STEM – 47%, Human ities – 33%, Others – 20 %
Institution
Type Public – 62%, Private – 38%
Tabl e 1 - S u mma ry of st ude nt p ar ticipa nts’ de mograp h ics .
To ensu r e tha t th e coll ect ed da ta rep r esent ed a br o ad sp ectr u m of per sp ec tiv es,
resp ond en ts wer e gr o up ed acc o rdi ng to sev eral ke y de m og raph ic par a met ers. Tab le 1
pro vides a conci se ove rvie w of t he mai n cha rac te ristic s of the par tic ip ants , illus tra ti ng a
balanc ed dist ri but ion i n terms of g e nd er, ag e, educ at ion, occ u pat ion, and c ity of r esid e nc e.
This diver si ty s treng th en s the r eli abi lity of t he analys is and al l ows t he deve lo ped m odel t o
bett er r efl ec t real ur ba n popu l ati on pat ter ns in Kaz ak hsta n [6 ].
B. Data P rep r oc es sin g
Befor e c on duc ti ng th e ana lytic al an d mod eli ng s tag es, the co l lect ed da ta un der we nt a
s eries of prepr oces sing steps to ens ur e qualit y, c onsis tency, and suita bilit y for mac hin e
learni ng analys is . Th e p r oces s follow e d s tan da rd data s c ienc e pr actic es and was implem en te d
in Py th on us ing P an da s, Nu mPy, a nd s cik it-l e arn libr ari es.
Miss ing v al u es in n u me rical fi el ds , s uc h as ex a m scor es or s el f-re port ed diff icul ty lev els,
wer e r epl ac e d wi th t h e mea n valu e o f the res p ectiv e c olum ns t o pr eserv e th e ov eral l
dis tribu ti on of t h e data. Mis sing categ orica l r espons es, includi ng stu dy progr am or insti tu tion
type, w er e fill ed usi n g m ode i m pu tat ion t o ma int ain co ns ist enc y ac r os s c ateg ori es [ 7].
Outli ers w ere det ect ed us ing z-s c ore a nal y sis , and obs e rva tions wi th abs ol ute z-s cor es
gre ater than t hr ee w ere exclu de d fr om th e dat as et to pr ev ent b ias in the r egr ess ion mod el.
Cat egor ical var ia ble s suc h as educ ati on level and stu dy progr am wer e tra nsf or med into
Proceedings of the 11th International Scient ific Conference
38
num erica l for mat usi ng Lab el Encodi ng and On e-Hot E nc odi ng, d e pen ding on th e variab le’s
cha ract eris t ics.
To pr ep ar e t he da tas et f or mod eli ng, four k ey f eatu res w er e id e ntif ied : L ear ni ng Aw aren ess
(X₁), repr es ent ing st ud ent s’ s elf-r epo rt ed un de rst andi ng of sub jec t c onc epts ; R eso urc e
Acc ess ibilit y ( X₂), re fl ecting the perc eiv e d avail a bili ty of lear ni ng r es our ces s uch as books,
onlin e platfor ms , and t u torin g; Stu dy Fr e que nc y (X ₃), indic at ing h ow often s tuden ts engag e in
s tructu re d s tud y s ess io ns; a nd D e mogr a phic s (X ₄), which co m bine d fa ctors suc h as a g e,
educa tio n l ev el, an d ins titutio n ty pe. The d ep end en t va ria bl e (Y) r ep r esent ed th e like liho o d
of expe rien c ing l ea rning diffi cu lti es.
All feat ur es wer e nor mal iz ed to a 0 – 1 s c ale using Min Max Sc al er to ens ure equ al
cont rib uti on t o the mo del. Th e cle an ed datas e t w as th en d ivid ed int o tr ain ing (80 % ) a nd
test ing ( 20 %) su bs ets us ing th e tr ai n_ test_ s plit () f unc tio n wi th a f ixe d ra ndo m s ta te (4 2),
ens urin g repr od ucibi lity of t he r esul ts [9].
The cor r ela tion h eat m ap pres en te d i n Fi g ure 2 pr ovid es a visua l ov ervi ew of th e
relat io nshi ps am o ng th e k ey va ria bl es i nclu d ed in t he pr edictiv e an aly tic s m odel. B y app lyi ng
Spea r man’ s correl ati o n, the a nal ys is ca ptur es mo no t onic as s ociat i ons b etw een o rdina l
feat ure s s uch as L earn i ng Awar en ess , Res ou rc e Acce ss ibi lity, S tu dy Fre qu enc y, and t he
dep end en t var iabl e rep rese n ting L earn ing Di ffi culty Ris k. Th e c olor intens i ty in t he h eat m ap
ref lects the streng th an d directi on of t hes e relatio nshi ps , allowi ng for a q uic k ide n tific ati on of
the most inf lu en tial fac t ors in t h e datas et.
The r esul ts indi ca t e tha t L ea rning Awa rene s s demons tra t es th e st ro ng est n egat ive
corr ela ti on wit h L ear ni n g Di ffic ul ty Ris k, s ug g es ting tha t st ud ents w h o r ep or t hi gh er lev els o f
unde rs tand ing in their subj ects are less likely to e xp eri enc e acad e mic chall eng es. Study
Freq ue ncy a ls o sh ows a mod er at e n ega tiv e cor r elati on, hig hlig hti ng t h e i mp ort anc e of
cons ist ent eng a g eme nt in s truc tur ed st ud y s ess ions. In c on tras t, R esour ce Ac ces sibi lit y
exhi bi ts a w eak er b ut s till mea nin gf ul ass oc iat ion, i mpl ying th at wh ile acc ess to l earni ng
mat eri als is impor t ant, i t is n ot th e s ole d e ter mi na nt o f st ud en t suc c ess .
Ov era ll, the h eat map serv es as a c ruc ial step in fe at ur e v alid atio n, confir ming that the
s electe d var ia bl es con tr ibu te mea ni ngf ully to t he pr edic ti v e mo d el. By vis u aliz ing t h e
inter d ep end enc ies a mo ng f eatur es, th e a na lys i s ens ures that m ultic oll in eari ty is mini m iz ed
and th at eac h var iabl e a dds uniq ue ex pla na t ory po wer . This str engt h ens the r elia bili ty of t he
s ubsequ e nt mach in e l e arni ng m od els an d p rov id es educ ator s w ith ev id ence -b as ed insig h ts
into wh ic h fact or s mos t s ignific a ntl y inf lu en c e the ea rly d et ect ion of le arni ng dif ficul ti es .
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
39
F ig ure 2 – Co r rela tio n He at map of S tud e nt Lea rni ng Varia bl es
C. Fea tur e E xt rac t ion
Fea tur e extr acti on w as one of th e m os t i m p ort ant s tag es of th e st udy, as it de ter mine d
whic h factor s w oul d be includ ed in t he mac hin e learnin g model . The goal of t his step wa s to
iden tify the va ria bl es th at b est r epr esent s tude nt s’ eng age me n t w ith lear ning pr oc ess es an d
their ris k of a ca de mic di fficu lti es [1 1].
The sel ec tio n of f eat ur es w as gu ide d by t heo re tica l fr a me wor ks f ro m educ at io nal da ta
minin g and t h e r esults of expl or at ory data an alysis . The var iabl es wer e ca te gor ize d int o
cog niti ve, b ehav iora l, and de mogr aphic di me nsions [12 ].
Featur e Name
Descr iption
Type
X₁: Learning Awar eness
Students’ se lf-reported
understanding o f subject
concepts
Ordinal (1 –5)
X₂: Resource Accessibility
Availability and quality o f
learning r esources (books,
online platfor ms, tutori n g)
Ordinal (1 –5)
X₃: Study Frequency
Frequency of str uctured
study se ssions
Ordinal (1 –5)
X₄: Demographics
Age, educati on level,
institu tion type
Categor ical
Y: Learning Di fficulty Risk
Likelihood of experiencin g
academic d ifficulties
Ordinal (1 –5)
Tabl e 2 - E xtr acte d fe a tu res u s ed in th e mo del
After selec tio n, all n u me ric al feat ure s w e re sc al ed to a 0– 1 r a nge us i ng MinM axSc al er fr om
the sc ikit -lear n libra ry t o ensu r e eq ual co ntri b ution t o the mo d el. This s tep prev e nte d any
varia bl e ( fo r e xa mpl e, “R esou rce Acc ess ibilit y”) fro m do min atin g due to its nu m eric s cal e. F or
Proceedings of the 11th International Scient ific Conference
40
dem ogr a phic varia bl es enc od ed as c ateg ori es ( e.g., educ at io n lev el o r ins t ituti on ty p e), O n e-
Hot Enc odi ng w as ap pli ed t o c rea te d u mmy var iable s comp ati bl e with clas s ific ati on
algor it hms .
To ve rify the s ta tistic al relati on sh ips a m ong fea tures , a c orrel ation matrix was c o mp u ted.
The resu lts show ed t h at L ea rni ng A w aren e ss had th e s tr ong est n ega tiv e c or relat io n w it h
Lear ning Dif fic ult y Risk (Spe ar man’ s r = –0 .5 2) , whi le S tudy Fr equ e ncy d em onst ra ted a
mod er at e n egat iv e cor rela tio n (r = – 0.41 ) . Thes e fi ndi ngs indic at e tha t aw arene ss an d
cons ist ent s tudy ha bits signif ic ant ly red uc e th e p rob ab ilit y of l e arni ng dif fic ulti es. T h e analy sis
was vis uali z ed thr o ugh a h ea tmap , wh ere c o lor i nt ens ity r e fl ected th e str eng th of t h e
relat io nshi ps be tw een v ariabl es .
Eac h extr act ed f eat ur e w as ana lyz ed for its pot en tia l c on tribu ti on t o t h e pre dic tiv e m od el.
Lear ning Aw ar en ess and Stu dy F req uenc y w er e tr eat ed as dire ct be havior a l indic at or s, whi le
Res ourc e Acces sibi l ity a cte d a s a c on textu al f ac tor i nfl u enci ng dif ficul ty ris k indir ec tly [13 ].
D. Mod el Tra ining a n d Imp l e menta t ion
After the pr ep roc ess in g and f eat ur e extr ac tio n stag es , th e n ex t st ep was t o tr ain a nd
impl em ent t h e mac hin e le arni ng mod els f or pr edic t ing stu d ents ’ ris k o f lear nin g d iffic ulties.
Two mod els w ere selec te d for co mpa ris on — L ogis tic Reg res sio n a nd Dec ision Tre e Cl ass ifier
— due t o their int erpre tabili ty an d suitabi lity for small to m edi um- siz ed e duc at iona l datas ets .
The go al was to eval ua te w heth e r stud en ts’ awar enes s, res our ce ac ces s ibilit y, and s t udy
fre que ncy c ould sta tis ti cally pr edi ct t he lik elih o od of aca d emic chal le ng es [14 ].
The b ase li ne mode l ap pl i ed w as Logi st ic Regr ession, wh ich esti ma tes t he prob a bil ity o f
learni ng diff icult ies as a log istic func tio n of several ind epe nd ent predic tor s. This ca n be
expr ess ed a s:
𝑌
=
( 1)
wher e
𝑌
is the pr edic t ed p rob abil ity of le ar nin g dif fic ulty,
𝑋
, 𝑋
, 𝑋
ar e awa ren ess ,
reso urc es , and s tudy f requ enc y v a ria bles, r esp ec tivel y, an d
𝛽
ar e mo d el c oeffic ie nts.
To as ses s the mod el ’s p re dicti on accu racy , th e Mea n Abso lu te Er ror (M A E) was c alcul ate d
us ing t h e for mul a:
𝑀𝐴 𝐸 =
∑ | 𝑦
− 𝑦 |
(2)
The m odel ach iev ed a n a verag e MAE va l ue o f 0 .23 , mea ning th at t h e typica l pr edict ion
error was a bou t 0.23 points o n th e 5- poi nt s atis f acti on sc ale. To explo re non lin ear
relat io nshi ps, a Decisi o n Tree model was a lso test ed, improvi ng th e a cc ur acy sl ight ly (
𝑀𝐴 𝐸 =
0.21
,
𝑅
= 0 .087
). Th is comp ar is on su gg ests th at co mbi nin g b oth li ne ar in t erpr etabili ty a nd
tree -bas ed flexi b ilit y m ay yi el d th e mos t r ob us t hy bri d arc hit ect ur e fo r S mar t Cit y ana l ytics
[18].
The Log istic R eg res sion mod el a c hi eved an av er ag e M A E v alu e of 0.19 , mean ing t hat the
typic al p re dic tio n error was about 0. 19 poin ts o n th e 5- poin t diffic u lty s cale. To e xp lor e
nonli n ear rel atio ns hips , a Decis ion Tre e mod el wa s also tes ted , impr ovin g the a ccur acy
s lightl y (M A E = 0.1 6, R² = 0 .12 ). This co m par iso n s ug ges ts th at c o mbini ng both li near
inter pr etabi l ity a n d tr ee- base d fl exib ilit y m ay yiel d the m os t r o bust h ybri d arc hi t ecture f or
educa tio na l analy tics [1 8].
The c om par ativ e dia gra m in F igu r e 3 illus tr at es th e p erfor m anc e of tw o pre dic tiv e m od els
— Log istic R egr es sio n and D ecis ion Tr ee — i n dete cti ng e arl y signs of l ear nin g dif ficult ies
amo ng s tudents . Th e v is ualiz ati on highl ights bot h th e c oeffic i e nt of det er min ati on (R² ) an d
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
41
the M ean A bsol ut e Erro r (M AE), pr ovi ding a bala nc ed view of acc urac y and reli abi lity. Whi le
the De cis io n Tre e achiev ed sli ghtly hi gh er R² an d lower M AE values , indica ting bett er fit and
redu c ed pr edic tio n e rr or, the dif fer enc e b etwe en t he t wo m od els re ma ins m odes t.
D espite th e D ecis i on Tre e’s marg inal a dva n tag e in pr ed ictiv e ac curacy , t he L og ist ic
Regr ess io n mode l re tai ns s ignif ic an t va lue du e to its i nt erpr et abil ity and tra ns par enc y. In
educa tio na l co nt exts , whe re c l ear expl an ati ons of pr ed ictiv e fac t ors ar e esse ntial for p olic y
and in ter ven ti on, th e a bilit y t o trac e awar en es s, resour c e acc es si bilit y, and s tudy freq u enc y
influ enc e outc om es is c ri tical. T hus, t he diagra m unde rsc or es the t ra de-o ff betw een a cc ur acy
and int erpr etabilit y, sug gesti ng that a h ybri d a pproac h may offer t he m os t ro b us t solu ti on f or
early de t ec ti o n o f lear ning di ffic ulti es .
Figu re 3 – C om paris on of M od el P erf orm anc e (R² and M AE)
The lin e gra ph in Fig ur e 4 provi des a cl ear v isua lizat io n of the r esults obta in ed fr om th e
s tatistic al for mu las us ed to ev aluat e m odel p e rfor ma nc e. B y pl ot ti ng bo th th e co eff icient of
det er mina tio n (R² ) a nd th e M ea n Abso lu te Er ror (M AE) , th e diag ram hi g hlig hts h ow L ogis tic
Regr ess io n a nd Dec is ion T re e dif fer i n t h eir pr ed ictiv e ca pac ity. The D ecis io n T r ee s ho ws a
s lightl y hi gh er R² a n d l o wer M AE, whic h sugg es ts t hat i t c ap t ures nonli near rel ati ons hips i n
the d ata m or e effect iv ely t han Log is tic R eg res si on.
At t he sa m e ti me, the gra p h e mphas iz es th e tra de-off bet w een acc ura cy an d
inter pr etabi l ity. Whil e th e D ecis ion Tr ee de mo ns tra tes m argi na lly b ett er nu m eric al
perf or manc e, Log istic Regr ess io n r ema ins val ua bl e d ue to its tra ns par en cy a nd eas e o f
expl an atio n. In ed uca tio nal c ont exts , wh er e t ea chers a nd p olicy maker s re quir e c l ear insig ht s
into w hy pre dict ion s ar e ma d e, the int er pr eta bilit y o f L o gistic Reg r ess ion ens u res tha t t h e
mod el’s ou tco mes can be dir ect ly li nk ed to s tu den t aw ar ene ss , r eso urc e acc es sibi lity, a nd
s tudy freq u ency.
Proceedings of the 11th International Scient ific Conference
48
Interest in authentic video mater ials co me s from the need to make learning mor e
meaningful and connected to real-life communication. Traditional textbooks often simplify
language and r emove cultural depth, which limits learners’ exposure to how En glish functions i n
real contexts. Authentic v ideos, however, offer a rich combination of visual, audi tory, and cultur al
information. This aligns with modern views on language acquisit ion, such as Kr ashen’s Input
Hypothesis and sociocultur al perspectives, which emphasize that learners benefit most fr om
comprehensible, real-world input situated in meaningful social interactions. Through r epeated
exposure t o natur al spe ech, gestur es, humor, and ever yday situations, students can internalize
cultur al norms that cannot be fully conv eyed thr ough iso lated vocabulary list s or scripted
dialogues.
Although authentic video content has shown strong potential in developing both linguistic
and cultural skills, i t is sti ll not consist ently used in many cl assrooms. So me tea ch ers may be unsure
how to select appro p r iate mater ials for younger learners, while others ma y worr y about fas t
speech, unfamiliar voca bulary, or cultural r eferences that st udents may find difficu lt. There are
also concer ns r elated to lesson planning, time co nstraints, and access to te ch nology . As a r esult,
the effect iveness of authentic video mater ials - especially for students at t he basic stage of
secondary school - remai ns underexplored. Th is s tudy seeks to address this gap by examining how
learners engage with au thentic video s and what as pects of lingua cultur al co mpetence show
improvement thr ough regular exposur e.
The motiva tion for this research also comes from th e ch allenges that many students face
when lea rning English i n classr oom settings. Lea r ners often rely heavily on memo riza tion,
simplified texts , and teacher-led explanations, which provide limited oppor tunities to obser ve real
communicati on. Even when students know vocabulary and grammar, they may s tr uggle to
understand natur al sp eech, cu ltural humor, or everyday interacti ons. Au t hentic video co ntent
offers a solution by bringing r eal-life si tuations di rectly into the classroom, helping learners build
contextual vocabulary, recognize co mmunication patterns, and develop aw areness of cu ltural
norms. For early adolescen ts , who already consume digital media outside of sc ho ol, integ rating
videos into lessons can make learning more enga ging, relevant, a nd motivating.
In this study, the use of authentic video content i s investigated as a strategy to foster
linguacul tural competence among se condary school learners. The research fo cuses on how
authentic videos influence st udents ’ cu ltu ral awa reness, contextual vocabulary devel opment, and
communicati ve co nfidence. It also examines students’ attitud es towa rd this method and the
challenges they face when interpreti ng real-life media. By analyzing students’ experiences, the
study aims to provide pr actical guidance for teachers who wish to incorporate authentic materials
into their lesso ns. Therefore, the main resear ch q uestions g uiding this stud y are:
1. How does authentic vid eo content influence the development of
linguacul tural competence among seco ndary school learners?
2. What ar e students’ per ce ptions and attitudes toward using authenti c
videos in Engl ish les so ns?
3. What factors su ppor t or limit the effectiveness of authentic video content
in real cl assroom conditions?
METHODS
This st udy used a quantitative r esearch design to examine how auth entic video cont ent
can foster linguacultural co mpetence amon g secondary sch ool st udents at the basic level. The
main purpose of the research wa s to find out how often learners eng age with authentic videos,
how t hey feel abo ut using this content, and what ch anges they notice in their under standing of
cultur al references, language use, and overall communicative competence. To co llect the
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
49
necessary information, a structur ed online questionnaire was used , allowing the ga thering of
numerical data a s well as shor t descriptive responses.
The st udy w as carr ied out online at a s econdary sch ool where a uthentic video mater ials
are sometimes integrated into langu age lesson s. A total of 20 students partici pated in the
research. All partici pants were learners of Englis h as a for eign language, with profici ency level s
ranging from A1 to B1. They were selected through convenience sampli ng, as they were already
exposed to video-based activit ies in their r egular classes. Their ages ranged from 12 to 15 ,
providing insi ght into h ow young learners respond to aut hentic video content.
The questionnair e, crea ted in Google Forms , co nsisted of 15 questions, including multi ple-
choice, Likert-scale, and sh ort open-end ed qu estions. The closed-ended items asked about the
frequency of using authentic videos, per ceived improvemen t in understanding cu ltural references,
language co mprehension, and co nfidence in using language in cultur ally appropr iate ways. Open-
ended questions invited students to descri be the ch allenges they faced and the benefits th ey
experienced when engaging w ith authen tic video content.
To analyze the collected data, descriptive statist ics were use d to summarize th e
quantitative responses, including percentages and fr equency counts. Qualitative responses from
the open-ended questio ns were analyzed using a simp le thematic approach to identify co mmon
ideas, such as comprehension of cultural context, vocabulary acquisition, or increased mo ti vation
to communicate. This combination of qu antitat ive and qualitativ e insights h el ped provide a clearer
understanding of how authentic video content sup ports the d evelopmen t of linguacultur al
competence.
Overall, this method allowed the res earcher to g ather practi cal and bal anced information
about how s tudents interact with authentic videos in real classroom situations and to identify both
the str engths and limitations of u sing this appr oac h in for eign language instruction.
RESUL T
Demogr aphic and Gene ral Information
The dist ribution of par ticipants by age i s a s follows: 1 2–13 years – 40% , 14 years – 35% ,
and 15 years – 25% (Figure 1). This age breakdown r eflects the typical developmental
char acteristics of stud ents at th e basic st age of secondary school and provides insigh t into how
early ad olescents perceive a nd interpret authentic video content. By prof iciency le vel, the
distributi on of partic ipants was: A1 (Beginner) – 0% , A2 (Elemen ta r y) – 20% , and B1 (Pr e-
Intermediate) – 10%. This shows that learner s possessed varying levels of li nguistic readiness,
which may influence their ability to extr act cultural meaning, un derstand natur al sp eech, and
apply cultural ly appropriate expressions. The gender distributi on is: Male – 35% , Female – 65 %
(Figure 3). This slight predominance of female lear ners may affect th e types of video co ntent
students prefer and their atti tudes towar d cu lturally oriented learning mater ials. These
demographic details provide an impor tant foundation fo r inter preting the s ubse quent fin dings.
Figure 1
Proceedings of the 11th International Scient ific Conference
50
Gender Percent %
Male
Female
Total
35%
65%
100%
Table 1
Frequ ency and Use of Authentic Video Content
Regarding the frequency of engaging with authentic video content, 55% of students
reported using authentic vid eos “regularly” (2–3 times per week ), 30% “occasionally” (about onc e
per week), and 15 % “r are ly” (less than once per week). This shows that more t han half of the
respondents were consistently exposed to r eal-life visual mate rials, mak ing such c ontent a
meaningful part o f their language learning routine.
When ask ed about th e types of authentic video s th ey typica lly wa tch, 50% selected shor t
clips (e.g., interviews, stre et talks, comedy mom ents), 35% pr eferred mov ie and se r ies fragments,
and 15% wat c hed vl ogs, mini-documentaries, or educa tional YouTube content. This distribution
suggests t hat students tend to favor sh orter, easi ly-digestible formats that provide both l inguistic
input and cultural context without overl oading them.
Students also indica ted w here they usually acc ess authentic videos: YouTube (60% ),
TikTok/Instagram Reels ( 25% ), an d full-length films o r series (15 %). This highlights the importan ce
of social med ia platforms as accessible lear ning tools for cu lturally enriched language input.
Improvement in L inguacultural Co mpetence
When asked about the ir understanding of cultur al r eferences in authentic videos, 48% of
students reported “significant improvement”, 37 % “moderate impr ovemen t, ” and 1 5% “minimal
improvement.” These results i ndicate that authentic videos play a substantial role in helpin g
learners identify gestures, traditions, humor, co mmunication norms, a nd real social behaviors.
Regarding development in co ntextual vocabulary and nat ural expressions, 52% of st udents
noted “signi ficant improvemen t,” 33% “moder ate impr ovement,” and 15% “no noticeable
improvement.” This suggests that most learners b enefited from exposu re to r eal-world speech
patterns, idioma ti c expressions, and cultur ally b ound voca bulary ite ms that are not typically
included in t extbooks.
For overall communicative confidence in cul turally appr opriate communication, 50% f el t
“much mo re conf ident,” 32 % “somew hat more confident,” and 18% “no chan ge.” These findings
demonstrate tha t authentic v ideos help s tudents internalize cultur al norms and u se English more
naturally and a ppropri at ely in r eal-life contexts.
Stu dents’ Attitudes T owa rd Auth entic Video-Base d Learning
When asked about their overall attitude toward learning with authent i c videos, 62%
described t his me thod as “very engaging, ” 28% as “moderately engaging, ” and 10 % as “s omewhat
useful bu t diffic ult.” Th is indica tes a predominantly positive per ception of authentic content as a
motivating, int eresting, and modern lear ning tool.
Students also evaluated the percei ved usefulness o f authentic videos for cu ltur al learning:
65% rated them as “highly useful, ” 25% “u seful, ” and 10% “ sl ightly useful.” This sh ows that a clear
majority recognize the value of real-life media in enri ching their und erstanding of English-speaking
cultur es.
Chal lenges and Benefits Ident ified by Students
The analy sis of students’ responses r evealed several challenges they face d wh en wor king
with auth entic video ma te rials. A signif icant number of learners (40%) st ated that the fast or
unclear s peech of native speakers made it d ifficult to catch key words and understand t he overall
message. A smaller portion of stude nts (10%) noted that backgr ound noise , over lapping dialogues,
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
51
or dis tracting visua l elements sometimes hinder ed their abili ty to focus on the linguisti c content
of the videos . Together, these fi ndings dem onst r ate tha t while authentic vi deo mat erials p rovide
valuable exposure to real-life language use, they may also pose considerable ch allenges for
learners at t he basic stage of secondar y school.
The resu lts of this study show th at authentic video content is widely use d among secondary
school stud ents and is associ ated with improvements in cultur al awar eness, vocabulary
development, and communicative confidence. Most participants reported r egular engagement
with authentic videos and positive learning outcomes, although some challenges related to speech
speed and cult ural complexity were noted. O verall, t he findings indicate that authentic video
materials c an s erve as an effective tool for f ostering linguacu ltural competence at the basi c stag e
of secondar y school.
DISCU SSION
The findings of th is study demonstrate that authentic vi deo content has a generally pos itive
impact on the development o f linguacultural competence among students at the basic stage of
secondary school. The results alig n with previous research showing that exposu re to real-life
audiovisual mater ials enhances learners’ cultu ral awareness, co ntextual under standing, and
communicati ve ability (Kramsc h, 2013 ; Gi lmore, 2017 ). In this study, nea rly half of the participants
(48% ) r eported signifi cant improvement in under standing cultur al refer ences, such as gestures,
humour, and s ocial no rms, which supp orts earlier findings su ggesting that authentic materials
provide learner s with access to cultural n uances that cannot be fully captured in textb ooks.
The resu lts also show that a uthentic video content contributes to st udents’ commu nicativ e
confidence. A majority of learners ( 82%) noted an incr ease in co nfidence when inte racting w ith
cultur ally r elevant language. T his aligns with resea r ch indica ting that au thentic i nput strengthens
not only lingu istic skills but also learners’ willi ngness to engage in communicati on (T omlinson,
201 2). When students en counter real-life si tuations pr esented thr ough vid eos , they gain a clear er
sense of how language is used in soci al inter acti ons, wh ich helps them apply expres sions more
appropr iately. The high l evel of engagement reported by students in this study is also consi stent
with previous f indings th at a uthentic mater ials can significantly increase motivation because they
are more rel atable, modern, and meaningf ul for learners (Pe acock, 1997).
Students’ attitudes to ward authentic video-based learning wer e la r gely posi tive. Most
partici pants described the method as engaging and useful , which supports claims that authentic
media enhances learner involvem ent by connecting language learning with real experiences
(Herron et al., 2002). The regular use of authentic videos by mor e than half of the students (55%)
further illustrat es their accessi bility and appeal, especially considering the popularity of soci al
media platfo rms such as YouTube, TikTok, and Instagram among adolescents. This sug gests that
integrating familiar media for mats ca n help tea chers bridge the gap between classro om learning
and learners’ everyday digital environments , making the development of linguacultural
competence more natu ral and continu ous.
Despite these positive outco mes, several challenges we re identified. Co nsist ent with
earlier research, fa st s peech and uncl ear pronunciat ion in auth entic videos were th e most
frequently mentioned dif ficulties, with 40% of students repor ting pr oblem s rel ated to rapid,
natural spoken language (Field, 200 8). Previou s studies have also noted th at early-stage lear ners
often strug gle with pr ocessing a uthentic input due to its complexity and unpredictabilit y.
Additionally, st udents in this study repor ted issues r elated to background noise , f ast-paced
dialogue, and unfamiliar vocabular y, which aligns with findings that aut hen tic materials can
overload learners if not proper ly scaffo lded (Gil mor e, 2007) . These challenges hi ghlight the
importance of teacher support when implementing authentic video content, part icularly fo r
learners with lower pro ficiency levels.
Proceedings of the 11th International Scient ific Conference
52
To address these difficu lties, educ ator s may co nsider incor porating graded and leveled
video materials designed s pecifical ly for langu age learners. Pre-teaching ke y vocabula ry, providing
subtitles, and offerin g guided vi ewing task s can help students process cultu ral and linguistic
information more effectively. Research sh ows that scaf folding techniques - such as previewing
cultur al concepts or pausing videos for clarif ication - significantly enha nce co mprehension when
working with authentic materials (S herman, 2003 ). Furth ermo re, sel ecti ng shorter o r thematically
focused videos, which 50% of participants alr eady prefer, ca n prevent cognitive overlo ad and
make cultur al elements easier to inter pret.
Overall, the f indings of t his study rei nforce previous literature demonst rating the potential
of aut hentic v ideo materials t o foster linguacu ltural competence. At the sam e time, the results
emphasize t he need for t hou ghtfu l instructi onal design to ensure that learners at the basic stage
of secondary sc hool ca n fully benefit fr om authentic input. Moving forward, teachers sh ould
integrate authentic vid e os systematically into lesso ns while providing adequate scaff olding to
support co mprehension. Th is approach will help stu dents dev elop not only their linguistic
knowledge but also their cul tural understanding, preparing th em for more con fident and
meaningful communica tion in English.
CONCLU SION
In conclusion, the findings of this study indicate that using auth entic video content can
positively influence the dev elopment of linguacultural competence among secondary schoo l
students at th e basic level. Results suggest th at au thentic video s are a useful and practical tool for
helping learners c onnect language learning with cultur al awar eness.
The stud y also showed that students generally en joyed learning with authentic videos a nd
felt motivated when en gagi ng wi th r eal-life mater ials. M any participants mention ed that videos
made th e lessons more interesti ng, helped them stay focused, and allowed them to experi ence
English as it is use d in d aily life. Exposure to n atural speech, idiomatic expressions, and cu ltural
norms helped s tudents i nternalize patter ns that cannot always be taught through textbooks,
which indic ates that authentic video content can make language learning more meaningful and
engaging.
At the same time, severa l challenges were iden tified. Some s tudents had difficu lty
understanding f ast or unclear sp eech, unfamiliar vocabulary, or cult ural jokes and references.
These findings su ggest that authentic vi deo content i s most effective when teachers provide
guidance, such as pre-teaching difficu lt vocabular y, p ausing or r eplaying segments, and explaining
cultur al context. With p roper sup port, students can overcome these challenges and benefit more
from video-based le arning.
Overall, t his stu dy demonstrates that auth entic videos ca n be an effective tool for fost ering
both linguistic and cu ltural competence in secondary school learners. Te ach ers a r e en co uraged to
integrate video materials regularly into lesso ns to enhance students’ commun icative confi dence
and cul tural un derstandin g . Future research could explore long- term effects of video-based
learning or i nvestigate how interacti ve and digital platfor ms ca n further suppor t lingua cultural
development. A uthentic video co ntent, when used thoug htful ly, helps students become more
confident, cu lturally aw are, and successful language learners.
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
53
REFERENCES
Field, J. (20 08). Liste ni ng in the languag e classroom . Cambridge University Pr ess.
Gilmore, A. (2007). Authentic materials and authenticity in foreign language learni ng.
Lang uage Teaching, 40 (2), 97–1 18. https: //doi.org /10. 1017/S0261444807004 144
Gilmore, A. (2 017). Au thentic materials and spoken language. In M. Howard & D. S. Carless
(Eds. ), The Routledge handbo ok of Eng lish language teaching (p p. 123–138). Routledge.
Herron, C., Ha nley, P., & Cole, S. P. (2002). Using authentic video in the f or eign language
class room. Foreign Langu age Annals, 35 (2), 155–169. https://doi.org/10.111 1/j.1944-
972 0.2002.tb01959.x
Kramsch, C. ( 2013). Language and cu lture . Oxford Universit y Press.
Krashen, S. D. (1985). The inpu t hypothesis: Issue s and implicati ons . Longman.
Peacock, M. ( 1997). The effect of auth entic mate r ials on the motivation of EFL learners.
ELT Jour nal, 51 (2), 144–156 . https://doi.org/10.1093/elt/51. 2.144
Sherman, J. (2003). Using authe ntic video in the langu age cl assroom . Cambridge University
Press.
Tomlinson, B. (2012). M aterials de vel op ment for langua ge learning and teaching .
Bloomsbury A cademic.
Tulasynova, N. Y. (2024). Us e of Authentic Video Mate rials in the Process of English
Lang uage Teach ing . International Research Journal, (139) .
https://doi.or g/10.23670/IRJ.202 4.139.76
Yusupova, S. O., & Khazr atkulova, E. I. (2024). Enhancing language acquisition through
shadowing: A study on pronunciation, fl uency, and lis tening comp rehension. Obra zovanie Nau ka
i Inno vatsionnye Idei v M ire, 59 (5), 153–154. http s://d oi. org/10. 1000/obr9475
Proceedings of the 11th International Scient ific Conference
54
UDC 372.881.1
D E V E L O P I N G I N T E R C U L T U R A L
C O M M U N I C A T I V E C O M P E T E N C E
T H R O U G H A I - G E NE R A T E D
C O M M U N I C A T I O N S C E N A R I O S I N G R A D E
1 0
Zhiy enb ek Zh an el M u ratkyz y
4th year st udent, «6B0 1701» F oreign Lang uages: Teach er T raining fa cult y, Ablaik han
Kaz UIRandWL, Almaty , Kaz ak hstan
Zhu mabek ova Gali ya Bai skan ovna
Candidat e of Pedagog i cal Science s, Pr ofessor , Kaz akh Ablai Khan Inte rnational Univ ers ity
of Relation s and W orld L anguages, Kazak hstan
Abstrac t: This study investi gates the use of AI-gener ated communication sc enarios as a
practi cal tool for developing in tercul tural communicative co mpetence (ICC) among Grade 10 EFL
students. As adolescents often struggle with communicating effectively in inte rcultur al contexts,
AI-assisted scenarios provide an engaging and in teractive platfo r m to practic e both la nguage sk ills
and cultur al understanding. The findi ngs indic ate that these s cenar ios enhance s tudents’ c ultural
awareness, communic ation confidence, and coll aborative skills. Man y participants reported that
interacting with AI int erlocutor s a llowed them to bet ter r ecognize cultural differences, adapt t heir
communicati on str ategies, and feel mor e com fortable in intercultu ral exchanges. Вoth students
and teachers expressed positive attitudes toward AI-generated scenarios, acknowledgi ng their
value a s a supportive and in novative tool f or fosteri ng ICC. Overall, this study suggests that AI-
assisted communication sc enarios can be e ffectively integrated into secondary English classrooms
to promote meaningful intercultural learni ng, p rovided that proper guidance and scaffolding are
offered.
Keywords : AI-generated scenarios, Inter cultural Communicative Co mpetence, EFL
Students, co mmunication sk ills, cultural awareness.
Introduction
In today’s globalize d worl d, develo ping intercultural communicative co mpetence (ICC) has
become an essential goal in Engli sh language education. G r ade 10 students, as adolescents
prepar ing f or higher education and international co mmunication, need opportunities to enga ge
with diverse cultural perspecti ves while pr acticing meaningful commu nication. One innovativ e
approach t hat has r ecently gained attention is th e u se of AI-generated c ommuni cation sc enarios,
which simulate r eal-life intercul tural inte ractions and provide st udents with a sa fe, interactive
platform to practice both language and cul tural skills. This st udy ex plores how AI-assisted activities
can su pport st udents in developing ICC by foster ing cultural awareness, co mmunication
confidence, and collaborative skills.
The interest in AI-gener ated co mmunication scenarios st ems from th e need to make
intercultur al learning more e ngaging and authentic. Traditional c lassroom a ctivities, such as r ole-
plays or textbook exercises, often fail to provide realisti c inter cultural con tex ts or may be l imited
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
55
by teacher availability and time const raints. AI tools, on the other hand, all ow students to interact
with vir tual interl ocutors, receive immediate feedba ck, and pr actice responding to d iverse cu ltural
cues. This approach a ligns with contemp orary theories of co mmunicative and exp eriential
learning, which emphasize the impor tance of authentic, interactive, an d so cially meaningful
language use (B yram, 1997; Mizuguch i, 2019).
Despite their potential, AI-generated communication scenar ios are still not widely
implemented in secondary school settings. Some educators may lack training in using AI tools
effectively, while others might be concer ned about th e acc u racy or cultural appropr iateness of AI-
generated content. Additionally, students may fa ce ch allenges such as understandi ng cu lturally
specific references or managing technica l diffi cu lties. Ther efore, r esearch i s need ed to investi gate
how these tools fu nction in real cl assroom conditions, how students respond to them, and what
facto rs contribute to successfu l ICC developme nt.
The motivation for this st udy also comes from the recognized gap between traditional
English language teaching and the development of real-world interc ultural competence. Students
may posses s strong linguistic knowledge but still str uggle to communicate appr opriately in
intercultur al contexts du e to a lack of exposure to authe ntic interactions . A I-gener ated scenar ios
offer opportunities to bridge this gap by co mbining l anguage practice with cultural learning,
enabling learners to reflect on cu ltural norms, adapt their commu nication strategies, and build
confidence in inter cultural encounter s.
This study investigates the use of AI-generated com municatio n scenarios as a classr oom
strate gy to enhance ICC in Gr ad e 10 students. The resear ch fo cuses on stu dents’ eng agement,
intercultur al understanding , an d communicatio n skills, as well as their a tt itudes toward these AI-
assisted activities. By exami ning students’ experie nc es, the study aims to pro vide pract ical insights
for teacher s seeking to integr ate te chnology-enhanced inter cultural learning into their curriculum.
Therefore, the main r esearch questions g uiding this study are:
1. How do AI-genera ted communication scenari o s affect Grade 10 stu dents’
intercultur al co mmunicative competence, including cultural understanding and
communicati on skills?
2. What are students’ per ceptions and attitudes tow ard usi ng AI -a ssisted
scenar ios for intercultural communication pract ice?
3. What fact ors facilitate or hinder t he effective use of AI-generated scenar ios
in promoting m eaningful intercultur al learning experiences?
Methods
This study employed a quantitative r esearch design to explore how AI-generated
communicati on scenarios supp ort the development of intercul tural communicative competence
(ICC) among Gr ade 10 students. The main purpose of the research was to determine how
frequently st udents en gage with AI-based scenar ios, ho w they per ceive t heir effectiveness, and
what cha nges they notice in cultural awa reness, communicative s tr ategies, and confiden ce when
interacting in inter cultural co ntexts. To col lect the required da ta, a st ructured online questionn aire
was use d, allowing the researcher to gather both numerical responses and brief des cripti ve
comments f rom participants.
The st udy was conducted onl ine at a school wh ere AI-as sist ed lear ning tools ar e
periodically in tegrated into Grade 10 English lessons . A total of 15 students, aged 15 –17, and 5
English teachers particip a ted in the research. All st udent participants were EFL learners who
regular ly practiced communication skills as part of th eir curriculum. Co nvenience sampling was
employed, as these s tudents we re alr eady fa miliar with digi tal learning envir onments and had
prior experience using AI tools in classroom activities. Including teachers in the study provided
Proceedings of the 11th International Scient ific Conference
56
additional insights into th e pract ical implementation and effectiveness of AI-generate d
communicati on scenarios i n real classroom settings .
The questionnaire, created using Google Forms , co nsist ed of 15 questions, including
multiple-choice ques tions , Likert-scale st atements, and short o pen-ended prompts. Closed-ended
questions focused on th e frequency of using AI-generated sc enarios, perceived improvement in
intercultur al awareness, ability to interpret cu ltural cu es, and confidence in c ommunicating with
people from differe nt cultural backgr ounds. Op en-ended questions encouraged students to
describe the advantages, di fficulties, and emotional responses they experien ce d when interacting
with AI-generated c haracters or situat ions.
To analyze the collected data, descriptive statist ics were use d to summarize th e
quantitative results, including frequency counts and percentages. Qualitative r esponses were
examined thr ough a simple thematic analysis to id entif y recurr ing ideas such as incr eased cu ltural
cur iosity, d ifficulties understanding cultural norms, or enhanced mo tivation to commun icate. This
mixed-data approach helped pr ovide a ful ler pictur e of ho w AI-generated communication
scenar ios influence students’ i ntercultural communicative competence.
Overall, the chosen method allowed the resear cher to obtai n balanced and pract ical
information about students’ e xperiences with AI- bas ed intercultural task s and to identify both th e
strengths a nd limitations of inte grating AI tools i nto ICC development in Grade 10 classr ooms.
Results
Demogr aphic and Gene ral Information
All participants, including both students aged 15–17 and their En glish teachers, took part
in evaluating the effectiveness of AI-generated sc enarios (Figu r e 1). Their co mbined per spectives
provide a more comp rehensive understanding of how Gr ade 10 learners respond to AI-suppor ted
intercultur al communicative activiti es and how te achers perceive the pr actica lity of in tegrating
these tool s into real cla ssroom se ttings. By pr oficien cy level, the distri bution is: Pre-Intermediate
– 20%, Intermediate – 30% , Up per-Intermediate – 50 %. This indicat es t hat most participants
possess s ufficiently str ong English sk ills t o engage meaningfully wit h AI-gener ated c ommunication
scenar ios, which require both lingu istic c ompetence and c ultural inter pret at ion s kills. The gender
distributi on is: M ale – 35%, Female – 65% (Figure 2). This shows a moderat ely high er proportion
of female partici pants, which may influence over all engagement with interactive, communication-
based learning ta sks.
Figure 1. The composition o f study participants
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
57
F igure 2. Gender of Parti cipants
Partici pants Percent % Gender Percent %
Student
Teacher
T otal
55%
45%
100%
Male
Female
Total
65%
35%
100%
Table 1 . Overview of Participan ts’ Charac teristics
Frequ ency and Use of AI-Generat ed Communicat ion Scenarios
60% of Grade 10 students r eported engaging with AI-generated communica tion s cenarios
"regular ly" (3–4 times per week), 25% "oc casional ly" (1–2 ti mes per week), and 15% "rarely" (less
than once per w ee k). This indicates that the majo rity of st udents act ively us ed AI scenar ios a s par t
of their intercultur al communication practi ce. Regarding the type of scenar ios, 55% pr eferred
scenar ios simulating authentic native speaker interactions, 30% favored cultural ly d iverse peer-
model sc en ar ios, and 15% used a mix of both. This shows that st udents are drawn to scenar ios
they per ceive as most helpful for developing bot h li nguisti c co mpetence and intercultural
awareness.
Improvement in I ntercultural Communica tive Competence
When asked a bout perceived improv ement i n cultural understa nding, 50% of students
reported "significant improvement," 35% "moderate improvement," and 15 % "minima l
improvement." This suggests that AI scenar ios contribute to students ’ ability to r ecognize and
interpr et cu ltural nor ms. For communicatio n confidence, 55% felt "much mor e confident," 30 %
"somewhat mor e conf iden t, " a nd 15% "no ch ange." This demonst rates tha t using AI sc enarios
positively imp act s students’ will ingness to participate in intercultural exch anges. Regarding
collaborative skills during scenar io-based ac ti vities, 45% r eported "s ignificant impr ovement," 40%
"moderate improvement, " and 15 % "no noticeable change, " showing that AI-mediated tasks
support cooper ative learning and i nteraction.
Stu dents’ and Teachers’ Attitud es Towar d AI Scenarios
When asked about overa ll attitudes toward AI-generated scenarios, 65% of s tudent s
described them as “very us eful,” 25% as “mod er atel y useful, ” and 10% as “slightly useful.” A mong
teachers, 70% believed that AI scenarios effectively enhance students’ intercul tural
communicati on skills, while 20% considered them moderately effective and 10% were unsure.
These r esponses indicate a generally positive perception of AI tools from both students an d
educators.
Chal lenges and Benefits of Using AI Scenarios
Students identif ied several challenges when using AI-generated sc enarios: understanding
cultur ally sp ecific content (40%), keeping up with scenar io prompts (35%), an d limi ted
technological skills (25%). Despite these ch allenges, 70% of pa r tici pants rep orted benefits such as
enhanced cu ltural awareness, improved communication co nfidence, and i ncreased motivation to
Proceedings of the 11th International Scient ific Conference
64
processi ng speed . Th is is consi stent with data suggesting that physica l exercise increases the level
of the neur otrophic factor BDN F, which is cri tical for learning a nd mem or y.
3. Moderate CF and GPA Link: A moderately st rong cor relation was found betwee n
high cognit ive indicators and aca demic perfor mance (r=0.52,p<0.01 r =0.52, p <0.01). Since succe ss
in technology and business disciplines directly depends on the ab ility to analyze, conce ntrate, and
solve complex p roblems, improved executive functio ns tr anslate directly into higher grades.
4. Direct PA and GPA Link: A statistically si gnificant, th ough moderate, direct
correla tion w as established between th e level of ph ysical activity and GPA
(r=0.39, p<0.05 r =0.39, p <0.05). This means that even without di rect accounting for cogn itive
funct ions, students leading an active life style tend ed to have higher academic per formance. T hi s
may be linked not only to biological mechanisms but a lso to the development of competencies
such as disci pline, self-regulation, and planning, which a r e reinforced th r ough r egular training an d
necessary f or a high GPA.
The data obtained ar e crucial for the KUTB administr ation. Physi ca l cultur e should not be
considered a secondary subject t hat distracts students from co re discipli nes. On the contrary, it is
an investment in intellect ual potential. Increasing the level of physical activity i s an a cc essible and
effective non-ph armacological way to optimize st udents' cognitive funct ion s, which ulti mately
leads to an improvement in the qu ality of th e educational pr ocess and the competitiveness o f
graduates[4].
The conducte d correla ti on analysis convincingly co nfi rmed the r esearch hyp o thesis: in the
environment of technolo gy and busi ness students at KUTB, there is a st able positive cor relation
between regular physical activity, the sta te of their cognitive functions, and academic
perfor mance.
Key Conclusions:
1. The regularity of p hysical activity is a powerfu l predictor o f attention effectiveness
and infor mation processing speed.
2. The opt imization of cognitiv e functions, medi ated by physica l culture, is a
significa nt factor influencing the fina l Grade Point Average (GP A).
3. For technological and business univer sities where intellectual load is maximal,
physical cultu re must be r epositioned as a tool f or developing mental perfo rmance, not merely
physical health[5].
Recommendations for I mplementation in KUTB's Aca demic Process:
1. Mandator y Di gital M onitoring Implementation: Use dat a from fitness trackers to
assess the fulfillment of th e minimu m physical acti vity standard as part of th e physica l culture
course credit.
2. Organization of "Mot or Breaks": Integr ation of short (5–10 minute) phy sical
exercises a nd war m-ups during lon g lecture and l aboratory sessions to restore attent ion and brain
activity.
3. Development o f Cogni tive-Stimulating Co urses: Inclusion in the P hysical Cu lture
progra m of spo rts that require r apid decision-making and hig h co ordination (tab le tennis,
badminton, team games ).
List of literatur e:
1. Hillman, C. H., Erickson, K. I., & Kramer, A. F. (2 00 8). Be smart, exercise your heart:
exercise effects on brain and c ognition. Natur e Re v iews Neur oscience, 9(1), 58–65.
2. Erick son, K. I., Vo ss, M. W., Prakash , R . S., e t al. (2011 ). Exer ci se training increases
size of hi ppocampus and improves memory. Pr ocee dings of th e Nati onal Academy of Sci ences,
108 (7), 3017–3022.
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
65
3. Khvatov V. V. Vz aimos vyaz' fi zicheskoi aktivnosti i intellektual'nogo r azvitiya
studentov // Teori ya i praktika fizich eskoi kul'tury. 201 7. № 10. S. 18–20.
4. Isaev A. A., Ivanova G. P. Fizicheskaya kul'tura kak sr edstvo ko rrektsii
psikhofiziologicheskogo sost oyaniya st udentov v usl oviyakh infor matizatsii // Vestnik KazNU.
Seriya pedagogicheskaya. 2019. № 2. S. 78–85.
5. Plotkin B. A. Kognitivnye f unktsii i akademicheskaya uspeshnost': metodicheskii
aspekt // Vysshee obr azovanie v Rossii. 2021. № 5. S. 112–1 20.
Proceedings of the 11th International Scient ific Conference
66
A d a p t i v e L e a r n i n g M e t h od s : P e r s o n a l i z e d
E du c a t i o n T h r o u g h I n t e l l i g e n t S y s t e m s
Ahmad ova Goncha Vidadi
Lectur er at Azer baijan S tate Pedagogi cal U niver sity; Re public of Az erbai jan
Abstr ac t
Adapv e l earning employs arficial intel ligence, learning analy cs, and r eal-me dat a tracking to
custom iz e in s t rucon accor din g to each learner ’ s p rofile. By adjusng conten t , pace, and f eedback,
these s ys tem s enhance learner eng agement, mova on, and academic ach ievemen t. This arcle
e x ami nes t he theore cal f oundaon of adapv e learning , its sy stem architecture, advant ages,
challenges, ethical consi d er aons, and emerging trends. Evidence-based e xamples and pr a ccal
implement aons are discu ssed to guide e ff ec ve adopon and futur e resear ch in various
educa onal sengs.
K eywor ds: adapve l earning , personaliz ed instrucon, intelligen t tu tor i ng sy stem s, learning
analycs, digital pedag ogy
Intr oducon
T r adional educa on o en applies a s tandar d iz ed t eaching appro ach, deliver ing the same cont en t
at a unif orm pa ce t o all s tudents. However , learner s diff er in their prior knowledge, cognive skills,
and lear ning pre fer enc es, which can lead to di seng agemen t for some and learning difficules f or
others (Smart Learn ing E n vironme nts, 201 9).
Adapv e l earning address es the se c hallenges by pr oviding per sona liz ed i ns trucon that responds
dynamically to learner perf o rmance. These s ys tems c on nuously anal yz e int eracon dat a,
adjus ng cont en t, difficulty , and feed back to mat ch each learner ’ s needs.
R esear ch demonstr ates t hat adap ve l earning can simulat e one-on-one tutoring benefits at scale,
improving mast ery , eng agem ent, and ret enon (Fern ández-Mor ant e, Cebrei ro-López, R odríguez-
Malmier ca, & Ca sal-Oter o , 20 22). Appl ica ons in STEM, language ac quision, and prof essional
devel opment rev eal significant improv ements in learning outcomes compared to conv enonal
teaching or s ta c e-learning approaches ( El-Sa bagh, 2021; Meylani, 2024) .
Architectu re and Core Co mponents of Adapve Learning Sys tems
Adapv e l earning sy stems con si st of in ter connected modules that monito r learner inter acons,
analyz e beha vior , and personaliz e ins trucon. The eff ecveness of th ese sy s tem s rel ies on the
seamless integr aon of each component (Smart Lea rning E nvir onme nts, 2019; Meylani, 20 24).
Lear ner M ode -the learner model rep resents a compr ehensive profile of t he learner , incl uding
cognive abilies, kno wledge lev el , learning pre f e ren ce s, and mova on.
Elemen ts : Prior knowledg e , learning s tyle (visu al, auditory , kines the c), p ace, eng agemen t,
misconcepons.
Dat a s ources: Quiz results, assessm en ts, int er acon l ogs, response mes, click pa erns, and, in
advanced s ys tems, biometric or aff ecve dat a .
Ex ampl e: ALEKS (Assessm ent and Learn ing i n K nowledge Spaces) con nuously upda tes a s tudent ’ s
knowledge map in ma themacs, iden fyin g ar e as r equi ring reinf orcement and pred ic ng
subsequen t learning paths (El -Sabagh, 2021).
Adapve Engine - the ada pv e engine det ermines the mos t appropria te i nstruconal s tra teg y f o r
each learner .
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
67
T echniques : Rule-based adap ta on using prede fined c on dions. Machine learning algorithms tha t
detect pa erns and predict opmal path wa ys (Meylani, 2024) . R ein f orcement learning that re fin es
s t ra tegies through iter a ve f eedback.
Ex ampl e : Smart S parr ow adap ts medical and STEM si mulaons, off ering hints, reme di al guidance,
or advanced e x ercises based on learner perf orma nce (Fernández -M or ante et al., 2022).
Conte nt R ep ository - a repository st ores educaonal mat erials in mulple f orma ts, enabling
t ail or ed delivery:
Form ats : T ext, video , aud io, simula ons, inter acve e x ercises, and gam ified cont ent.
Org aniz aon : R esources are t agged by difficulty , l earning objecve, prer e quisi tes, and learning
s t yle.
Ex ampl e: Khan Ac adem y employ s modular cont ent aligned with learning objecves, allowing
adapv e sequencing f or individual iz ed mast er y (Courser a , 2023). Assessmen t and Fee dback
Module - assess ment and f eedbac k are cen t ral t o adapv e l earning :
Sy st ems deliver f o rma ve and diagnosc ass essments. Immediat e f eedback provides guidance,
r einf or ce s learning, and sug ges ts r emedia on. Analy cs det ect paern s, misconcepons, and
eng agemen t trends, f acilita ng tar geted teacher interven ons .
Ex ampl e: K newton moni tors responses i n real me, adjusng e x ercises to main tain opmal
challenge and progr ession (Qadir , Suleman, & Khan, 2025).
Communicaon and R epor ng Lay er -adv ance d sy st e ms include dashboar ds f or learner s and
ins tructor s:
Ins tructor da shboards: T rack per f ormance , eng a gemen t, knowledge gaps, and r ecommended
int er ven ons.
Learner dashboards: Visualiz e progr ess, g oals, and f eed back summaries, promong self -regula on
and met a cognion (Smart Learning Envir onments, 20 19).
This close d-loop archit ectur e ens ures that learner int eracons con nuously inf orm sy st em
adjustmen ts, opmizing both cont ent delivery and learning outcomes.
Benefits of Adapv e Learning
Adapv e learning s ys tems pr ov ide pedag ogical, mov aonal, and opera ona l bene fits, supported
by empiri cal evidence:
Improv ed L earning Outco m es
Adapv e s ys tems enhance ret enon, mastery , and problem-solving skills. Studies r eport 15 –25%
higher learning g ains f or learner s us ing adapv e pla orms compared t o tr adional ins trucon (El -
Sabagh, 20 21). Adapve ma th ema cs pla orms, f o r ex ample, acc eler ate acquision of comple x
skills by adjusng diffic ulty a nd cont ent s equences based on learner pe rf orm ance (Meylani, 2024 ).
Higher Eng ageme nt a nd Mov aon
P ersonaliz aon f ost ers self -efficacy , intrinsic movaon, and ac ve parcipaon. Immediate,
t ail or ed f eedb ack r educes frustr aon and supports sust ained engagemen t ( Smart Lear ning
En vironmen ts , 201 9). Students in higher educaon rep ort increased mo va on when adapv e
s yst ems a djus t cont ent to t heir proficiency (Fern ández-Mor ant e et al., 2022).
Support f or Diver se Lea rning N eeds
Adapv e s ystem s accommoda te various lea rning styles and pr ovid e scaff ol ding f or learners with
cognive challeng es, ensuring equi t able a ccess to instru c on (Co urser a, 2023).
E fficient R esource Uliz aon
By eliminang redundan t instrucon, adapv e le arning maximiz es efficie ncy . Advanced learners
progr ess quickly , while s truggl ing learner s recei ve tar get ed remedia on (Qa dir , Suleman, & Khan,
202 5).
Scalability
Adapv e sys tem s off e r per sonalized ins trucon at scale, e nabling one-on-one bene fit s w ithout
propor onal i ncreases in t eaching st aff (Fern ández-Moran te et al., 2022).
Proceedings of the 11th International Scient ific Conference
68
Challenges and Ethical Considera ons
Despite its advan t ages, adapv e learni ng f ace s technical, pedag ogical, and ethical challenges:
T echnical Challenges
Accuracy of learner m od els ma y be limited, aff ec ng adapt a on (Smith et al., 20 25).
Devel opment of d iver se, high-q uality cont ent is re source-int ensive (Eduwik, 2023).
Pla orm re liabilit y and perf ormance is sues can h inder l earning (Meylani, 20 24).
P edagogical C hallenges
Over reliance may r educe collab ora ve lea rning oppor tunies (Link Springer , 20 23).
Self - regula on is req ui red; unmov at ed l earner s may s trug gle (Link S pringer , 202 3).
Misalignment with cu rriculum st andards can occ ur if integr aon is insuffi cient (Qadir , Suleman , &
Khan, 2025) .
Ethical and Equity Challenges
Connuous dat a collecon r aise s privacy and cons ent concerns (DrPres s, 2023 ).
Algorithmic bias may disadvan t age so me learner s (T omorrow De sk, 202 3).
Access to devices and in ternet is necessar y; the digit al div ide may e xclude some learner s (SPCA
E ducaon, 2023).
Re c ent Deve lopments and Future Direcons
R ecent advanceme nts f ocus on accuracy , pedagogical eff ecvenes s, and eq uity:
Hybrid AI mode ls combine rule-based and machine l earning techniques f or beer con ten t
r ecom mendaons (Qadir , Suleman, & Khan, 20 25).
Int egra on with l earning analycs enables teachers to monitor and in tervene e ff ecvely
(Fern á ndez-Mor ante et a l., 2022).
Applica ons e xtend to v ocaonal training, cy ber se curity , healthcar e, and prof essional upskilling
(Seda, V yk opal, Šv ábens ký , & Č eleda, 202 2).
Future res earch should emphasiz e robus t learner mod eling , h ybrid ins truc onal s tra tegies, ethical
dat a pracces, and equit able acc ess to maximiz e adapve learning ’ s impact.
Conclus ion
Adapv e learning transf orms educ aon by del i veri ng individualiz ed, responsive, and scalable
ins trucon. It improv es learning outcomes, eng agem ent, efficiency , and inclus ivity while
supporng diver se lea r ner ne eds. Succe ssful implemen taon require s addressing technical
r obustness, pedag o gical design, ethics, and equity . With car eful integ ra on, adapv e learning can
becom e a corner st one of modern educa on.
R ef erences
1. Courser a. (202 3). Adapv e learning: Ben efits, technologies, and use cases. R et riev ed from
hp s://ww w .cour sera.or g /arcles/ adapve-learning?utm_source=chatgpt.c om
2. DrPr ess. (2023). Ethic al considera ons in adapv e learning s ys tem s. Retriev ed from
hp s://d rpress.or g /ojs/index.php/EHSS/ arcle/do wnload/24840 /24327/33419? utm_sou
r ce=chatgpt.com
3. El-Sabagh, H. A . (2021). Adap ve e-learning en vironmen t ba sed on learning s ty les and its
impact on studen ts’ eng agemen t. In ternaonal Journal of Educa onal T echnology in Higher
E ducaon, 18, 53 . hp s://doi.org /10.1186/s41239-02 1-00289-4
4. Fern án de z-Moran te, C., Cebr eiro-Lópe z, B. , R odrí guez- Malmi er ca, M. –J ., & Casal -Oter o, L.
(202 2). Adapve lear ning supported by l earni ng analy cs f or s tudent teachers’
personaliz ed training during in-school pracces. Sus t ain ability , 14( 1), 124.
hp s://doi. org /10.3390/su14010124
5. Meylani, R . (2 02 4). A cr ic al glance at adapv e learning sy s tems using arficial int elligence:
A s ys tema c review and qualit ave s ynthesis. W A JES, 15(3), 3519–354 7.
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
69
6. Qadir , H. M., Sulem an , M. T ., & Khan, R. A . (2025). Opmizing lea rning outc o me s: Hybri d AI
models f o r adapv e educa onal f eedback. Journal of Big Dat a, 12, 144.
hp s://doi. org /10.1186/s40537-025-01187-6
7. Seda, P ., V yk opal, J., Švábenský , V ., & Čeleda, P . (2022) . R einf orcing cy ber security hands- on
training with adap ve learning. arXiv . hps:// a rxiv . org / abs/220 1.01574
8. Smart Learning En vir onments. (201 9). P er sonalized adapve l earning: An emer ging
pedagogic al appr oach. Smart Learning En vironments, 6, 9.
hp s://doi. org /10 .118 6/ s40 561-019-0089-y
9. Smith, et al. (2 025). Adap ve learning and teaching in sch ools: Conte xt, implemen taon,
and out comes. Learn ing and Ind ividual D iff erences, 124, 102781.
hp s://doi. or g /10.101 6/j.lindif .2025.102781
Proceedings of the 11th International Scient ific Conference
70
T h e R o l e o f A I i n W r i ti n g A s s e s s m e n t : A
C o m p ar i s o n w i t h H u m a n E v a l u a t i o n
G. A. Riz akhodjayeva
PhD, Associat e Profess o r, Khoja Akhmet Ya ssa wi Internati onal Kaz akh -Turkish Unive rsity
M.B. Yuldas heva
7M0170 8 – 2nd y ear m aste r student o f Depart ment of Fo reign Langu ages Educat io n,
Khoja Akh met Yassaw i Interna tional Kaz akh-Tu rkish Univer sity
Abstract
This study examines the use of AI-driven essay gr ading systems, focusing on tools like
EssayGr ader AI t hat assess st udent writing based on li nguistic and struct ura l cr iteria. While t hese
AI syst ems provide effici ent, objective, and sc alable asses sments, concerns arise regarding their
ability to ca pture th e cr eative, emotional, and contextual aspects of st udent wor k. The research
compares AI gr ading with human evaluation, exploring both the pr actical applications and the
emotional impact on st udents . Findin gs indicate that while A I offer s ben efits in efficiency and
consisten cy, it fa lls short in understandin g the hu man ele men ts of writing. Futur e develo pments
could enhance AI’s ability to compr ehend these nuances, but caution is needed to avoid over-
reliance on tech nology and po tential bias . The s tudy underscores t he nee d for a balanc e between
AI and human input t o support effective educational ass essment.
Keywords: Assessment, Artifi cial Intelligence, AI Asse ssment, Human Assessment,
EssayGr ader, AI-driven essay g rading, writing assi gnmen t.
Introduction
Artificial Intelligence (AI) has quickly changed man y facet s of education in r ecent years, fr om
virtual teaching assistants to language lea rning applications. The applica tion of AI one of the most
hotly contested aspects of this techno logical r evolution. The way teac hers assess written work
could be completely ch anged by tools like EssayGrader AI, which offer quicker, more capacity to
manage massive amount of s tudents’ essays ( Balfour, 2013).
Is it possible for a machine to comprehend what makes writing so great? This ques tion has
never bee n more pertinent in a world where technology i s transforming education in every way.
The con ventional limits of st udent evaluation ar e being questioned with the emergence of AI
syst ems such as EssayGrader AI. Essay evaluation, which was formerly the exclusive responsibility
of educato rs, is now in creasingly being handled by AI. However, how dependable, equitable, and
succ essful is this ch ange? Ca n AI tr uly under stand the nuan ces of a student’s argument, cr eativity ,
or voice? D oes it r ecognize cultur al contextual expressions t hat a human teacher would natu rally
appreciate? These ques tions be come especially important as educational institutions increasingly
explore AI as a cost -effective solution for assessment (Attali and Bu r stain, 202 0; Perelman, 20 14).
Tools like Es sayGr ader AI which analyze student writing acco r din g to predetermined
linguistic and str uctured criteria, have been made possi bly by th e use of ar tificial i ntelligence into
educational evaluation. These systems ev aluate gr ammar, coher ence, argument development,
and even creativi ty to a certain degr ee usi ng machine learning techn iques and Natural Language
Proces sing (NLP) . By ex amining enormous datasets of previously evaluated essays, EssayG r ader AI
specifica lly seek s to mim ic the sco ring habits of seasoned teachers. Delivering a consi stent,
effective, and impar tial evaluation is the aim (S herm is and Bu rstein, 2013 ).
EssayGr ader AI provides immediate feedback and scori ng using algorit hms designed t o
resemble human assessment. Proponents contended AI offers time-efficient, regular, and
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
71
objective assessments, which are particularly helpful when teachers are overbur dened with
administrative duties and big class number s. But writing is more than j ust using proper syntax and
structur e. De spite these conce rns, AI grading co ntinues to gain traction, especially in larg e-scale
or online l earning envir onmen t s wher e t eacher workload is hi gh and timely feedback is essential.
The key, as several sch olars a rgue, lies in usi ng AI as a supplemen t, not a su bstitute, for human
feedback (Liu et a l., 2022).
The pur pose of th e stud y is to examine how Ess ayGrader AI evaluates student w ork and to
contr ast i ts advanta ges and disa dvantages w ith those of conventional human evaluation. This
study examines how students r eact to both f orms of fee dba ck in or der to comprehend AI’s
educational and emotional effects on pup ils in addition to its practi cal applications. It is essential
for educators and policymakers to comprehend th e function and effects of AI in writing
assessment. This stu dy can ass ist in determining whet her AI technolog ies are prepar ed to r eplace
or augment specific elements of teacher-led evalu ation, as well as th e potential hazards associ ated
with doing so carelessly. It can also ser ve a s a guide for creating AI-assist ed learning sett ings that
strike a b alance between human sensitivity and technical eff iciency.
The main research q uestions for this study are:
1. How does feed back from Essay Grader AI differ from teacher-generated feedback in term s
of quality?
2. Is there a diff erence in assessment of H uman and AI?
Literatur e review
There has been a lot of d isc ussion and interest in the use of artificial intelligence in
educational evaluation. The difficulties pr esented by conventional hu man ass essors ma y be
resolved by using tools such as EssayGrader AI , which evaluate student work acc ording to preset
linguistic and struct ural standar ds. This review of the literatur e looks at several research t hat
contr ast hum an evaluation with AI-assisted essa y grad ing, emphasizing the benefits, drawbacks,
and consequen ces of each method.
Wetzler et al. (202 4) compared the gr ading r esults of human instructors and AI models,
specifica lly ChatGPT versions 3.5 and 4o. The purpose of the study was to determine how
accur ately and consis tently AI models could mimic t he gr ading habits of seasoned educators. T he
study investiga ted potential biases in the AI models and assessed how well the two grading
schemes align ed using statistica l analysis. The advantages and disad vantages of AI in essa y gr ading
in compar ison to human assesso rs might be thoroughly examined thanks to this design.
Large language models (LLMs) such as GPT-3. 5, GPT-4, o1, LLaMA 3-70B, and Mixtral 8x7B
were assessed by Seb le r et al. (2024) for their abili ty to grade essay s writt en by German students.
They focused on la nguage-related factors including syntax and sentence stru ct ur e and contrasted
AI-generated scor es with human judgments.
A research by Bouziane and Bo uziane ( 2024) assessed Ch atGPT's ability to evaluate wr iting
skills at th e surfa ce lev el , including grammar , spelling, sentenc e structure, and coherence. A
sample of student essa ys that wer e r ated by ChatGP T and hum an reviewers was used by the
research ers. They contrasted the ou tcomes using particular language mechanics criteria,
concentr ating on how effectively the AI and human gr aders evaluated probl ems lik e sentence
clarity, punctua tion, and grammar acc uracy.
A dual-process paradigm was pro posed by Xiao et al. (2024 ) that co mbines the depth of
analysis offere d by human evaluators with the efficiency of AI. In orde r to improve grading
accur acy and pr ovide more thorough feedback, the study concentrated on integr ating the
advantages of both methodolo gies. On a collection of student w r itings, the researchers combine d
human evaluations wi th AI-based essay g rading systems.
The advent of AI -assisted technologies, s uch as Writable, which was partially created by
ChatGPT, to assist tea chers in grad ing stud ent writing assignments is cover ed by Axio s (20 24).
Proceedings of the 11th International Scient ific Conference
72
These s olutions guarantee accur ate gr ad ing an d uphol d aca demic integrity by fusi ng AI's
capabilities wi th human co ntrol. Nonetheless, the research raises ethical concerns regarding the
employment of AI and draws attention to worries tha t it could lower the cal iber of feedback given
to pupils.
An automated essay sc or ing (AES) system ca lled *e -rater V.2* was cr eated and evaluat ed by
Attali and Burstein (2006) for use in educati onal assessme nts. Using syntactic, disc ourse, and
lexical aspects from natural langua ge processing (NLP ), the study examined the sy stem's essay
evaluation capabi lities.
Modern automated essay sco r ing (AES) systems were co mpar ed in an educational
measuring setting by Shermis and Hamner (2013). In or der to evaluate the e ffectiveness of vario u s
AES technologies (including both commercial and research-based tools), their st udy was
presented at th e National Co uncil on M easurement in Educa tion (NCME). In their 2016 s tudy,
Wilson and Czik examined the use of automated essay evaluation (AE E) software in English
language arts (ELA) classrooms and its fu nction in conjunction with teach er input. Although the
precise sample size and demographics were not disc losed in this secti on, the st udy in volve d
secondary school s tudents and te ache rs in an actual cl assroom environment.
Using deep learning techniques, Kumar and Boulanger (2020) investig ated the educational
possibil ities o f explainable automat ed essay scoring (AES) s ystems. Their research, wh ich was
published in Frontier s in Education, created and evaluated an AES system based on neural
networks that may offer st udents not only r atings but also c omprehensible feedback on their
writing.
Within lar ger sociotechnical systems, Warschauer (2020) criticall y analyzed th e changing
role of digital tech nologies in educa tion, including AI-dri ven tools lik e aut omated writing
assessment. This co nceptual stud y, which was published in Learning, Media, and Technol ogy,
reviewed theoretica l fr amew orks and empirical studies to examine trends in technology-mediated
learning.
Dikli (2006 ) rev iewed early AES systems (e.g., IntelliMetric, e-rater), co mpar ing their
linguistic featu r e analysis (e.g . , gr ammar, coher ence) to human grading criteri a. The study
synthesized findings from st andar dized te sting contexts but did not specify partici pant
demographics . B r idgeman et al. (2012 ) analyzed bias in AES for graduate ad miss ions essays, usin g
a cor pus of GRE writing samples.
The study contraste d human and AI s coring disparities acr o ss non-n ative English speak ers.
Grimes and Wars c hauer (2010) co nducted a multi-classr oom stu dy of AES tools (e. g., MY A c cess!),
observing how teachers integrated automated feedba ck into wr iti ng instruction without replacing
human assessment. Zhao et al. (2 023) tested GPT-4’s essay evaluation capabilities using university-
level writing s amples, focusing on r ubric alignment and feedb ack quality compared to inst r u ct or
grading.
Methodology
Research D esign
This study employs a quasi-e xperimental, within-subjects research design to co nduct a
comparative quantitative anal ysis of writi ng assessment performed by an Ar tificial Int elligence
platform EssayG rader AI versus human instructors. The primary ob jective is to evaluate the
reliability, co nsistency, and potential sy stematic biases between these two gr ading
methodologies.
Partici pant and Settings
The sa mple co nsists of 21 st udent essays co llected fr om an undergr aduate academic writing
course . Each essay s e rves as its own control, being evaluated by b oth an AI system and a panel of
human evalua tors. Essay s will be assessed using a standar dized analytica l rubric focusing on fo ur
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
73
core dimensions of writing quality, each yielding a s co re on a 5-point Likert sca le ( 1= Poor,
5=Excel lent).
A total score will be derived fro m the s um of the dimension sc o r es. The r esulting dataset will
contain the following ten primar y variables for analysis: Gr ammar scor e (AI); Gr ammar sco re
(Human); Vocabulary sco re ( AI); Vocabular y score (Hu man); Organization scor e (AI); Organization
scor e (Human) ; Coherence score (AI); Coherence scor e (Human); Total score (AI); Total score
(Human).
Data C ollection
Essay Se lecti on: 21 st udents covered 5 ar gumen t ative topics like ‘School Uni forms’;
‘Standardize d Test’. Each topic included t hree proficiency levels (A2 to B2), with essays r anging
from 500 t o 800 words.
Human Evaluation: Two trained English teachers graded the essays using The CAASPP Rubric,
providing a compr ehensive ass essment of a student's gr ammar, org anization, vocabulary,
coherence, and overall score.
AI Evaluat ion: Essa ys were input into Ess ayGrader A I for automated scor ing and feedback on
providing a co mprehensive assessment of a student's argumentative w riting sk ills.
Data Analysi s
To analyze t he question "How does feedback from EssayGr ader AI d iffer from teacher -
generated fee dback in terms of quality?" using pai r ed t-tests, descriptive statistics. To address the
question, "Is there a difference in assessment of Human and AI?", a Paired Samples T-Test is
indeed an app ropria te m ethod, as we are comparing two related se ts of data (human assessment
and AI assessment) for the same subjects or cases.
Treatment
Standardization of Ess ays: The sample co nsists of twenty-one student essays, collected from
a sta ndardized academic wr iting assignment. All essays w ere ano nymized to take out the id entity
of the student (student name, ID, cl ass section) so th at bias could not be introduced. The essays
were then ch anged into plain text format (.txt files) to mak e sure the AI to ol pr ocessed only th e
textual cont ent and n ot the f ormatting artif acts.
Rater Train ing and Cali bration: Two ex perienced human instructors were recr uited as r aters
to grade the essa ys. The raters were requir ed to attend a 90- minute calibration wor kshop before
the main grading session. During this sess ion, they studied the 5-point anal ytical rubric of the study
(Grammar, Vocabulary, Or ganization, Coherence), discussed the criteria for scoring at each l evel,
and independently scor ed three sa mple essays not include d in the main s tudy.
AI Too l Setup: The r esearcher created an account on the EssayGrader AI plat form
https://www. essaygrader.ai/ . The exact analytical r ubric used by the hu man raters was then
manually configured within the "Custom Rubric" settings in the AI system . The four criteria
Grammars, Vocabular y, Organization, Coh erence wer e input, wit h br ief descr iptors correspon ding
to each scor e level provided - 1 thr ough 5. No other modifications or s pecial prompts were used.
Grading was performed in t wo parallel, independent st reams to avoid any co ntamination
between AI and human ass essments.
AI Grading Stream:
Each of th e 21 anonymized .txt files was uploaded separately into the Ess ayGrader AI
platform.
For each essay, the opt ion "Gr ade with Cust om Rubric" was chosen. AI gener ated a score,
on a s cale from 1 to 5, for each of the four criteria and in total. No option of generating w ritten
feedback was enabled, focusing purely on n umerical scor ing.
All the scor es were manually recorded b y the rese arch er in a dedicated SPSS data f ile.
Human Gr ading Stream:
Proceedings of the 11th International Scient ific Conference
80
Ramesh, A., & Vanden, B. (2022 ). Do NLP models exhibit bias in auto mated essa y s coring? A ca se
study on gender and L1 bias. Pr oceedings of the 2022 Conference on Fairness, Accountability, and
Transpar ency (FAccT). https://doi.org/10.11 45/35311 46.3533089
Sebler, K., Für stenberg, M., Büh ler, B., & Kasneci, E. (2024). Ca n AI grade your essays? A
comparative analysis of lar ge language models and teacher r atings in multidimen si onal essay
scor ing. arXiv. https://arxiv.org/abs /2411.16337
Shermis, M. D., & Burstein, J. (2013 ). Handbook of Automated Essay Ev aluation: Current
Applications a nd New Directions. Routledge.
Shermis, M. D., & Hamner, B. (2013) . Contrasti ng stat e-of-the-art automated scoring of essay s:
Analysis. Proceedings of the National Counci l on Measurement in Education ( NCME).
Wetzler, E. L., Cassidy, K. S., Jones, M. J., Frazier, C . R., Korbut, N. A., Sims, C. M., Bowen, S. S.,
Wood, M. (2024). Gra ding the graders : Co mparing generative AI and human assessment in essa y
evaluation. SAGE Open. https://doi.org/10.1177 /00986283241282696
Wilson, J., & Czik, A. (2016). Automated essay evaluation softwar e in English language art s
class rooms: Effects on teacher feedback, student motivation, and writing q uality. Computers &
Educatio n, 100, 94–109. https://doi.or g/10.1016 /j . compedu.201 6.05.004
Xiao, C., Ma, W ., Song, Q., Xu, S. X., Zhang, K., Wang, Y., & Fu, Q. (2024). Human-AI collabor ative
essay sc oring: A dual-process framework with LLM s. arXiv.
https://arxi v.org/abs/2401. 06431
Zhao, S., et a l. (2023 ). Expl oring GPT-4’s potential in educational ass essment. Computers and
Educatio n: AI, 4, 100130.
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
81
T H E O R ET I C A L F O U N D A T I O N S O F
C R I T E R I O N - B A S ED A S S E S S M E N T I N
E V A L U A T I N G D I A L O G U E A N D
C O N V E R S A T I O N A L S K I LL S
Be rkingali Na uryzbek Berkinga liuly
4 th Year Bach elor student , “6B0170 1-T eacher of tw o foreign langua ges”, KazUIR & WL
Ablai Kh an, Almaty , Kaz akhsta n
Zhu mabek ova Gali ya Bai skan ovna
Candidat e of Pedagog y, Profe ssor , KazUIR & WL A blai Khan , Almaty , Kaz ak hstan
Abstr ac t
This arcle presen ts the theor ecal base f or using criter ion -based assessm en t to evalua te dialogue
and con ver saonal skills in secondary school English. Dialog ue is tr eated as t he mos t direc t wa y to
see communica ve comp et ence b ecause it re veals how learner s respond, q ues on and n egoa te
meaning with a partner . The arcle argues that w ithout criteria speaking remains judged by
impres si on, which is neither f air nor useful f or pr ogress. Ru bric based asses sm ent ma k es di alogic
ability visible through indicat ors of fluency , turn t aking , vocabulary choice and pragma c beha vior .
When teacher s ev aluat e th r ough criteria, s tuden t s in Grades 7 and 8 de v elop cl ear er contr ol of
r eal communica on, not o nly wrien accuracy .
K eywor ds: dialogue skills, criter ion- based asse ss ment, communica ve compet ence, rubric,
secondary sch ool English.
Intr oducon
Spok en Engl ish is o en evalu ated through accu ra cy alone, but communic aon does no t exis t in
isolat ed sent ences. It live s in dialogue, where speak er s list en, respond, n ego at e and adapt in rea l
me. A w rien answer ma y be corr ect, yet communica on sll fails if a learner cannot carry a
con ver saon or f ollow a partner ’ s i dea. Ther ef ore, it is not enough to assess language as
knowledge. It mus t al so be measured as acon.
In K azak hstani classroom s the gap betwee n kn ow ledge and per f ormance becomes vis ible early .
Students who complet e grammar task s succ essfully oen hesita te when a sk ed to speak. Other s
depend on memoriz ed dialogues and lose confidence when conv er s aon moves in a new di rec on.
These paern s show tha t tr adional a ssessm ent cap tures only a fr ac on of communicav e abil ity .
The classroom hear s accur acy , but rar ely inter ac on.
The problem does not come from lack of ability , but from how perf orm ance is judged. When
teacher s r ely on impr ession rather tha n criter ia, confident speak er s rece ive high mark s while
quieter o r slower speak er s are undervalued . This can discourag e learners who know th e language
but s trug gle with spont aneous inter acon. C riterion base d assessment aims to break thi s cycle. It
shis f ocu s from over all impres si on to specific beha vio r s suc h as turn t aking , flue ncy contr ol,
vocabulary choice , repai r str ategies and pr agmac awar eness. These behavior s are not hidden.
They can be observed n atur all y in dialogue.
Dialogue is also deeply soc ial. St udents in G r ades 7 and 8 build identy throu gh speech. They f orm
opinions, ques on i nf ormaon, agree and disagr ee with peer s. They test i deas aloud and modify
them in r esponse to f eedback . When assessm en t recogniz es th ese beha vio rs, speaking becomes
Proceedings of the 11th International Scient ific Conference
82
more than perf o rmance. It becomes devel opment. A rub ric allows tea ch er s to respond to real
communica ve eff ort. Instead of gener al advice lik e s peak more, f eedback becomes tar geted: ask
f or cl arifica on, build on your partner ’ s idea, o r or g anize your thought bef ore responding. E ach
suggeson has direcon.
The aim of this arcle is to presen t the theor ecal f oundaons that jusfy criterion-based
assessment of dialo gic skills in sc hool English. It ar gues tha t dialogue is t he cl ear est re flecon of
communica ve competence, and that ass essment must captur e the co mplexity insi de sp ok en
int eracon r ather than only the c o rr ectness of f orm. By ex amining componen ts of c ommu nica v e
compet ence and t he structur e of dialogic beha vior , the arcle suppor ts the adop on of rubrics as
a more r eliable and purp oseful wa y to e valuat e co nv ersa on in G rades 7 and 8.
Communicave Competence as an Educa onal Outcome
Communicati ve co mpetence stands as the pr imary goal of fo reign langu age education, yet in many
class rooms it remains a theoretical ph rase rather than an as sessed reality. A learner may complete
grammar exercises correctly and still fail to sustain c onversation, whi ch means the outcome of
learning has not rea ched functional level . To understand communicative competence as an
educational target we must t r eat langu age as something stu dents do with other s, not so mething
they o nly know on paper . S. S . Kunanbayeva’s work forms th e theoretical co re of this view. She
describes communicat ive competence as a multi l ayered s ystem that brings lingu istic resour ces,
sociocul tural norms, discourse organization and st r ategic behav ior togeth er within real
communicati on. It is not stored knowledge. It is displayed in use, and dial ogue is where this use
becomes visible.
This research bu ilds on se veral complementary theories that help explain how co mmunicative
ability develops and why assessment mu st reflect interaction itself. Vy gotsky shows that languag e
growth occurs through social exch ange, not isolation. Learners inter nalise forms by usi ng them
with others, especially when guided by a more capable par tner in the Zone of Pr oximal
Development. Long st rengthens thi s argument by demonstr ating that inter action drives
acquisit ion because learners negotiate meaning an d r eshape input when brea kdown occu rs. Sw ain
adds the Ou tput Hypothesis, arguing that spea king for ces lear ners to notice gaps in their language
and search for solutions, which makes productive interacti on a learning moment, not only
perfor mance. These views ex plain why a stu dent gr ows mor e w hen spe aking with a part ner than
when completing d rills alone.
If communicative competen ce is the goal, it s components must be r ecognized within assessment.
Linguist ic co mpetence allows the student to choose vocabulary and structur e se ntences, but it
does no t guarantee co nver sation. Sociolinguistic competence controls tone and politeness. It
shapes how a student speaks to a teacher compared to a classmate. Discour se co mpetence
connects ideas across turns s o that sp eech flows rather than fragments. Strategic co mpetence
appears when a learner paraphr ases, asks for repet it ion or repairs misunderstanding instead of
remaining sil ent. Kunanbayeva emphasizes that communication succeeds on ly when these
elements opera te together , and this integr ation is the clea rest in sp ontaneo us dialogue where
planning ti me is limited and responses m ust adapt quickly.
Traditional ass essment r arely captures this in te gratio n. A student who wr ites wel l can still hesi tate
in conversation, and an other who speaks active ly may pr oduce errors whi le maintaining mean ing.
If as sessment looks only at a ccuracy, both abilities are misr epresented. Communicative
competence must ther efore be evaluated in live inte raction wher e the learner manages real
speech demands. Crite r ion based assessment supports this need by focusing on observable
behaviors r ather th an general i mpressions. When teachers assess turn taking, responsiveness,
negotiation, and clarity of expressi on, they evaluate communication rather than recitation. In
Grades 7 and 8 st udents r each a sta ge wh ere they ca n form opinions, challenge peers, and build
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
83
ideas co llabor atively. Assessing th ese abilities gives value to real la nguage use and encourages
partici pation.
Communicati ve competence as an educationa l outcome means more than r eaching correct
answers. It means developing lear ners who can speak, lis ten, adapt and continue conver sation in
English without fear o f failure. When assessment reflects this aim, teaching aligns with it. Dialog ue
becomes normal practice, not preparation for test s. Growth becomes visibl e, because interaction
exposes what the lea r ner can a ctu ally do. Th is is why communicative compet ence must guide not
only curriculum but also eva luation, especially in classr ooms where Engli sh is meant to ser ve real
communicati on, not only written accuracy.
Criter ion Based Assessment and Indicator s of Dialogic Skil
Criter ion based a ss essment is grounded in th e idea that spoken perfor mance must be evaluated
through identifiable beh aviours rather than general impressions. A learner who takes tu r ns,
negotiates meaning, responds with relevance and k eeps t he conversation moving demonstrates
real communicat ive ability, even if occa sional err ors appear . Glaser’s wo rk supports this shift f rom
comparative scoring to observable outcomes, and O’Malley with Va ldez Pie rce add to this view by
arguing t hat performance must be assessed as it occurs naturally, not only th rough written forms
or rehearsed answers. When ass essment focu ses on wha t students can do in interaction, it r eflects
the reality of co mmunication more honestly t han trad itional accuracy-based testing.
Dialogic sk ill is complex because it involv es simultaneous processes. A speaker listens to the
partner , ch ooses vocabulary, structur es thought, manages tone and solves br eakdowns whil e
speaking. These actions ca nnot be captured through a si ngle sc ore, which is why r ubric-based
assessment separates perfor mance i nto clear domains. The fir st domain is linguist ic co ntrol.
Students use gr am mar and vocabulary to express meaning, y et perfection is not requir ed since
communicati on can su cceed even with imperfect form. The second domain is fluency. L earners
who respond within natural time, avoid lo ng sile nce and maintain continuation show control of
pace. The thi rd domain is interaction managemen t, which determines whether dialogue r emains
alive. A student who onl y answers crea te st agnation, whi le one who asks questions, refer ences
partner ideas and builds jointly k eeps communication active.
Strategy use forms the fourth do main. When v ocabulary is miss ing, co nfident speakers do not
stop. They paraphrase, descr ibe and r epair meaning, which demonstrates growth beyond
memorized langu age. The fifth do main is pragmatic awar eness. Learners adjust tone when
speaking to a peer, to a teacher or during disagreement. These choice s influence the success of
interaction more th an grammatical accur acy i n many cas es. Wh en these five domains a re place d
into a rubric, th ey become v isible indicators of performa nce rather than abstr act qualities. A
teacher ca n identi fy strengths direct ly and po int out where devel opment i s needed. Instead of
general fee dba ck like sp eak mor e, a learner hears give a follow up ques ti on next time o r show you
listened by building o n your p artner’s idea.
With clear indicators, progress does not disa ppear inside one over all mark. A st udent may impr ove
fluency first and interaction later, and thi s pattern can be tr acked. Criterion b ased assessment
makes these diff erences observable. It also makes partici pation less risky for learner s becaus e
improvement has sh ape a nd direc t ion. Dia logue becomes not only assessable but teachable. The
goal is not to produce per fect speech, but to build real co mmunicative competence that functi ons
in conversa tion.
Implications for Secondary School Eng lish Teaching
If dialogue is the clearest reflecti on of communicative competence, then secondary school English
teaching must change how sp eech is d eveloped and how pr ogress is measured. A classroom t hat
trains students to produce isolated senten ces cannot ex pect n at ur al conver sation.
Communicati on grows wh en learner s speak to one another with purpose, negotiate meaning
when confu sion appears and continue interaction inste ad of s toppi ng after sh ort answer s. W hen
Proceedings of the 11th International Scient ific Conference
84
English lessons prior ities grammar drills and written tasks as the main form of practice, sp oken
competence remains se condary. A criterion-based approa ch en courages te achers to brin g
dialogue into the ce nter of instruction, because only dialogue r eveals wh ether learners can th ink
through l anguage and respond in real time.
Rubric guided assessment gives teachers a structur e for planning lessons. If interacti on, f luency
and pragm atic awareness are criter ia, then tasks must req uire these behaviours. Pair d iscussions,
problem so lving dialogues, o pinion exch ange and information sharing activities allow students t o
practi ce what will later be assessed. Students in Grades 7 and 8 can handle such tasks. They are
old enough to develop o pinions and r espond to the views o f othe rs. When learners must ask
questions, provide r eas o ns and maintain to pic flow, they begin to speak mor e naturally. If
assessment r ecognizes these behaviours, learner s feel that conver sation has value, not only for m
accur acy.
Teaching pr actice also shifts when feedback becomes specific. Instead of s aying improve speaking,
the teacher can s ay use one clarifica tion question next time or build on y our partn er’s se ntence
before giv ing your own id ea. Th is type of guidance is achievable and measurable. A st udent knows
what to do, and the teacher can observe imp rovement in later tasks. Confidence increa ses
because succ ess is visible, not abstr act. A learner who once feared making mistakes may speak
more freely wh en they know that effor t in interactio n, even with err ors, will be recognized. This
supports the devel opment of str ategic competen ce, which i s oft en ignored in traditional ma rki ng.
Classroom climate changes when dialo gu e is ass es sed seriously. Silence no lo ng er fee ls safer than
partici pation. Students begin to understand that communication involves tr ial, adjustment and
repair. They learn th at it is acce ptable t o not know every wor d, because a successful sp eaker can
paraphr ase and continue. When these behaviours are valued, st uden ts become active use rs of
English in stead of quiet observ ers. Teachers also gai n a clearer picture of r eal ab ility. They no
longer r ely on written results to assu me communicati ve skill. Th ey se e how a l earner hand les
breakdown, h ow they support a partn er, and how they keep meaning moving.
The implication is direct. If secondary schools want communica tive learners, speaking must
become a st ructured part of a ss essment. Criterion ba sed rubr ics make t his poss ible. They h elp
teachers move beyond guesswork and giv e stu de nts a r oute fo r gr ow t h. Dialogue stops being a
passing activity and becomes evidence o f learning. When classrooms adopt this approach
consisten tly, language stops b eing something students’ study and beco me s something they do.
Conclus ion
Dialogue shows wh at learner s can actually do with En glish, a nd because of this i t must not stand
outside the assessm ent system. A stu dent who can maintain a conversat ion, a sk for clarification
and respond to a partner displays a level of communicative competence that written accuracy
cannot repr esent. The theoretica l foundations explored here make one point clear . If
communicati on is the goal, then the tools used to mea su re p rogress must recognize the skills t hat
conversation demands. Criter ion ba se d as se ssment prov ides this r ecognition by tur ning real
interaction into observable indicators.
Rubrics do more than assign mar ks. They gu ide lea rning. They help teachers see st r ength s and
weaknesses with clarity, and they give st udents a wa y to under stand their gr owth. W hen a learner
receives targeted feedback , impr ovement becomes a reacha ble process rather than a vague
expectation. Di alogue becomes practice, assessment and development at the same time. In
Grades 7 and 8 this is especially si gnifican t. Students at this stage are ready t o express ideas,
challenge opin ions and co const ruct meaning, and they need as s essment tha t values these effo rts.
The implicati on fo r teaching is direct and difficult to ig nore. Sch ools that expect commu nicative
outcomes must evaluate communicatio n thr ough dialogue, not only through correctn ess. A
criter ion-based system aligns instruct ion with a ssessment so that c las sr oom t alk ha s purpose and
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
85
direction. It invites participation instead of silence and r ewards strategic effort even wh en
language is incomplete. When this approach becomes normal practice, t he classroom shifts from
contr olled accuracy to active use, and communicative competence becomes something real
rather than theoretical.
Re f erences
Alexander, R. D ialogic Teaching a nd Classroom Talk.
Glaser, R. Criterion-Based Assessment T heory.
Kunanbayeva, S. S . Communicative Co mpetence Theory.
Long, M. Interactionist Theory of Language Learning.
O’Malley, J. M., & Valdez Pierce, L. P erformance-Based Assessment Theory.
Swain, M. Output Hypothesis.
Vygotsky, L. S ociocultural Theory and Dial ogic Interaction.
Proceedings of the 11th International Scient ific Conference
86
UDC 3 72.881.1
C o d e - S w i t c h i ng A m o ng E n g l i s h M a j o r s
D u r i n g G r o u p D i s c u s s i on s
Madeniye t Alua Kural bekkyz y
Foreign Languages' Tea cher Trainin g Facul ty.
Yess enova Shugyla Zhumah anky zy
Foreign Languages’ Tea cher Trai ning Fa culty
Zaur bek Aliy a Muhtar kyzy
Foreign Languages’ Tea cher Trai ning Fa culty
Ko s ymba i Ar uzhan S hai me rdenkyzy
Foreign Languages’ Tea cher Trai ning Fa culty
Scienti fic supervi sor :
Uzak baeva S.A.
Doct or of Pedagogi cal S ciences , Professor
JSC Kaz akh Ablai Kha n Uni versity of Int ernatio nal Rela tions And Wor ld Lang uages.
Kaz akhst an, Almaty, M uratbaev a 200.
Abstrac t.
This study investigates how co de-switching affects teamwork and academic commun ication
among fourth-year university st udents dur ing discuss ion tasks. Three gr oup members with
different pr oficiency levels d emonstrated frequent sh ifts between English, Kazakh, and Russian.
Although co de-swi t ch ing allow ed quick clarification, obser vations revealed that it also led to
uneven enga gement, breakdowns in idea d evelopmen t , and reduced use of Engl ish. Usi ng a small-
scale r esearch design, data were collected through a structured o bservation checklist, and brief
semi-str uctured interviews. Finding s sho w tha t lower-pr oficiency members r elied on L1 fo r task
comprehension, w hile higher-p roficiency mem bers co de-switched mainly out of habit. An
intervention based on ex plicit communic ation rules and vocabular y support was implemented.
After the intervention, students used English more cons istently and contributed mor e equally,
indicating improved c omprehension a nd task focus. The study sug gests that university courses
should incorpo rate strategy tr aining and sca ffolded academic E nglish support to r educe
unnecessary co de-switching and i mprove collaborative learning outco mes.
Keywords : code-swi tchi ng , group wor k dynamics, multilingual learners, communicati on
breakdowns, language proficiency d ifferences.
1. Introduction.
In mult ilingual un iversity settings, code-switching is a common co mmunicative pract ice through
which s peakers al ternate between t wo or more langua ges to maintain interactiona l flow, expr ess
cultur ally embedded co ncepts, or negotiate mea ni ng. Among Eng lish-language major students,
such alte rnation bet ween En glish and the L1 emerges naturally in informal conversa tion a s well as
during ac ademic collaboration. Discu ssions r equire quick access to techn ical voca bular y, cul turally
specific co ncepts, and interpersonal nuance. Prior research indicates that in multilingu al EFL
cohorts – including th ose in Bangl adesh, Indonesia, and Costa Ri ca – st udents often rely on L1
resourc es to su stain communication, cla rify difficult points, or r educe cognitive load during group
work (Alam & Quyy um, 2016; Nurhamidah et al ., 2018; Ríos & Campos, 2013).
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
87
At the functional level, university cl assroom studies sh ow that code-swi tching se rves interaction al,
pedagogical, and social pur po ses. These include mainta ining turn-ta king, repairing
misunderstanding s, tr anslating or pa r aphrasing challenging expressions, offering peer scaffolding,
and reinfor cing solidar ity or humor ( Yletyinen, 2004). In peer-led tasks, a si ngle L1 insertion can
trigger a chain reaction, l eading the entire group to shift languages tempora rily for coher ence o r
efficiency – an effect documented in both secondary and university settings (Ríos & Ca mpos,
201 3). Types of switching observed in academic contexts range from suprasentential inser tions of
technical labels to full intersentential alter nations for emphasis, clar ification, or instruction
(Nurhamidah e t al., 2018).
However, research also emphasizes th at uncontrol l ed or habitual sw itching may carry pedagogical
costs. Over-relian ce on the L1 can interrupt the development of En glish-ba sed problem-solving
strate gies, reduce op portunities for extended tar get-l anguage output, and sometimes be
perceived as avoidance rath er than productive c ommunication (Nurhamidah et al.,2018) . While
L1 use can be facilitative during early proficiency stages, scholars argue that it sh ould gradually
shift towa rd mo re strategic and reflecti ve use in advanced univer sity-level EFL contexts (Alam &
Quyyum, 20 16). Th ese findings highlig ht th at the educational vaue of code-switching depends no t
on its mere presence but on its frequency, ti ming, and function during academic tasks.
These dynami cs closely parallel our clas sroom situation. In our En glish-major group, three
students of diff ering proficiency levels frequently alter nated between Eng lish, Kazakh, and Russian
during an academic discu ssi on task . It is imp ortant to note here th at by pro ficiency we mean the
fluency of t he student in combination with the frequency in which they code swi tch. During our
discus sions, w e ca me to a questio n – why do students with Engl ish profici ency levels of B2-C1
switc h so frequently? While some of these switche s served legitimate com municativ e functions –
such as clarifying co ncepts or compensati ng for m is sing vocabul ary – they also created moments
of misalignment, disrupted ar gumentative flow, and reduc ed opportunities for sustained Engl ish
practi ce. For lower -proficiency par ticipants, switc hing often immediately shifted the group back
into L1, wh ile higher-proficiency members reported losing r hetorical rhy thms when others
unexpectedly swit ched languages. Thus, in this setting, code-switching became a problemat ic
team behavior with cle ar consequences for learning, task clar ity and the overall academic quality
of interacti on.
The present study therefore aims to (1) examine the pa tterns, trig gers, and perceived f unctions of
code-sw itching during group disc ussions among En glish-major stud ents, and (2 ) test a brief
intervention designed to redu ce disruptive switching and encourage more consist ent use of
English during academi c collabor ation. To in vestigate these questions, we employ an action
research desig n, which allows us to obse rve the problem in context, collect qualitative data,
implement an intervention, a nd evaluate its effectiveness in r eal time.
2. Methods
2.1 Research design
The study employed an action r esearch design, which is appropr iate for inves tiga ting a
pedagogical pr oblem wit hin a real cl assroom sett ing and implementing an immediate
intervention. Acti on Research i nvolves a c y clical process of identifying a pr oblem, co llecting data ,
introduci ng a targeted change, and evaluating i ts effects. In the present study, the pr oblematic
behavior is fr equent code-switching dur ing English-medium group discu ssion. After initial
observation, an intervention wa s implemented in which one group me mber acted as a peer
“language instr uctor” to encourage more co nsistent Engl ish use.
2.2 Participants
The partici pants wer e three multilingual fourth-year st udents maj oring in “Fo reign Languag e
Teaching” maj or with a focus on English. The high-p rof iciency participant (Dan iya), the mid-
proficiency participant (Saya), and the l ow-proficiency parti cipant (Aziza) all sha red Kazakh and
Proceedings of the 11th International Scient ific Conference
88
Russian as their primary l anguages. Thei r proficiency differences allowed us to ob serve how code-
switc hing man ifes ted an d varied across linguist ic lev els. All partici pants r outinely wor k toget her i n
group di scussions during their u niversity coursework.
2.3 Research context
The st udy took pl ace du ring two natur ally occurring group discussions as a part of a univer sity
English- language practicum cour se. Students were inst r ucted to co mplete the t asks in English ,
though no str ict language policy was enforced by the instructor. The multilingu al natu re of th e
group cr eated a r ealistic co mmunicative context wher e cod e- switching co uld occur
spontaneously.
2.4 Data collection methods
To capture both t he observable lingui stic behav ior and participants’ internal reasoni ng behind
their language ch oices, the study u sed two complementary methods:
2.4 .1 Observation
Both discussions were recorded and la ter transcribed. An observatio n protocol was used to not:
The instances of co de-switching;
The languages s witched between;
The location of the switch (suprasentential, intrasentential, intersententia l)
The immediate conversational effect ( e.g., clarification, h esitation, interr upt ion)
Separate analyses were conducted for Discuss ion 1 (baseline behavior) and Disc ussion 2 (post-
intervention).
2.4 .2 Semi-structur ed interviews
After two discu ssions, each participant t ook part in a br ief s emi-structured interview . The
interviews foll owed the same four guiding questi ons, which ex plored wh ether switch ing helped or
interr upted their communicati on; their personal triggers for swi tching; their perceptions of how
switc hing aff ected the group disc ussion; r eflections on the inter vention, parti cularly how being
guided by a peer language instructor influenced their language use. These interviews provided
metalinguistic i nsight into why st udents switched, complementing the observational da ta on how
and when sw itching occurred.
2.5 Procedure
Stage 1: Baseline identif ication. The first group disc uss ion was r ecorded under normal conditions.
Students wer e to ld to complete t he task, but n o monitor ing or co rrective strategy was introduced.
This discussion served as the baseline for identifyi ng th e problem and d ocumenting the natura l
patterns o f code-switching.
Stage 2: Intervention implementation. Be fore the second discussion, a brie f intervention was
introduce d. Daniya was assi gned the role of a peer language inst ructor. Her r ole wa s to gently
guide the group back to English wh en unnecessary switching occurred and to model co nsistent
English use herself. No strict penalties o r prohibitions w ere used; th e intervention r elied on soft
prompts a nd awareness raising.
Stage 3: Post-intervention observation and reflection. The second discu ssion was reco r ded using
the same observa tion pr otocol. Afterward, a ll three partici pants co mpleted the interviews. The
comparison between baseline and post-intervention data forms th e basis for evaluating the
effectiveness of the int ervention.
2.6 Ethical cons iderations
All partici pants were informed about the pur pose of the study and agreed to have their discuss ions
and r eflections used f or research purposes. Names used in the r eport r efer to real participa nts ,
with their conse nt, and all comments are reproduced respectf ully and fo r academic purposes only.
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
89
3. Results
3.1 Observation checklis t result s: baseline r esults
In the Google Forms observation checklist, there w ere a total of 13 code-switching insta nce s
recorded during the baseline dis cus sion. Intra-sentential co de-switching co mprised the highest
number of co de-switch ing types, acc ounting for 5 5.6% of the total code-switching instances,
where the code-switching occ urred within t he sentence. Inter-sentential code-sw itching
accounted for 22.2% of the code-swit ching instances, and the remaining 22. 2% comprised s hort
tags and
Switching because of the pr esence of a lexical gap or u nknown En glish word was the predominant
cause, occ u rrin g 5 times (55.6%) . Other r easons included topic clarification r equests ( 33.3%),
joking/rappor t building (22.2%), repa irs/ hesitati on pauses (11.1% ), emotio nal highlights (11.1%),
and addressi ng peers and teacher (11.1%).
Some ca ses of the swi t c h were also ac companied by v isible cu es. Th ese comprised: pause longer
than 0,5 seco nds (33 ,3%), faci al expression, for example, smiling or frowning (22, 2%), laugh ter
(11,1%), overl apping spee ch or interruption (22 ,2%), and rising tone/e mphasi s (22, 2%).
Additionally, f or 22,2% of the ca ses, there was n o visible cue recorded.
The partici pants took turns using either the Kazakh language (44,4%) , t he Russian language
(33,3%), or a co mbination of both languag es ( 22 ,2%). Regarding th e role of the message,
referential messages were per formed by 44,4% of the l anguage alter nations, with 33,3% of the
language alterna tions performed for pragmatic purposes, and 22,2% of the language alternat ions
involved tra nslation.
Representative examples i nclude:
“Енді ме н телефонсыз жүре алмаймын, өтйкені мен tra nslate words.”
“I think t hat we should somehow, как это сказать, балансировать…”
“Мы мо жем отвлекаться, but on the other hand phones can be helpful…”
“Banning p hones типа толықтай ма или қалай?”
In 55,6% of the cases the sp eaker continued in English immediat ely after switch ing, while 33,3 %
returne d to En glish after a sho rt pause. In only 11 ,1% of instances did the speaker r emain in
Kazakh/Russian for mor e than one turn.
3.2 Observation checklis t result s: post- intervention
After the intervention wh ere one of the participant s acted as the peer language instruc tor, the
overall number of switches r educed to 5. Th e number of intra-senten tial sw itches continued to
remain high at 60 percent, and the remaining 40 percent consisted of short ta gs.
The pred ominant cause remained th e pr esence of lexica l gaps (60%). The other causes inclu ded
use of hu mor/joke or building r apport (40%), use of peer address, and topic clarification ( 20%).
Visible cues diffe red fr om the baseline disc ussion: laughter (60%), and facial expressi on changes
(60% ) were mor e common, su ggestin g lighter, s ocially oriented switches. Only one switch followed
a long p ause (20%). Rising tone occurr ed in 20% of switches.
Partici pants predominantly sw itched into Kazakh (80 %), with Russian u sed i n 20% of cases. The
communicati ve funct ion included referential (40%), prag matic (20%) , sociolinguistic/identi ty-
based sw itching (20%), and tr anslation or clarification (20%).
Examples incl ude:
“And, как э то, details f or note- taking.”
“I think t hat, енді, например, it sh ouldn’t be totally forbid den.”
“Ағылшынша, let’s talk in English.”
“Мен де к елісем, they can’t do th at, болмайды ғо олай.”
Noticeably, 10 0% of switches were followed by i mmediate r eturn to English , indicati ng improved
English- only task adherence.
Proceedings of the 11th International Scient ific Conference
96
şəxsin təki, I və I I şəxsi n cəmində götür üb, şəxs şəkilçisini atmaq lazımdır. 1 -c i qru p feilləri vəl-ci
qrup feilləri kimi təsr if olunan III qru p feillərində v ə “aller” feilində II şəxsin t əkində “-s” düşür.Əm r
cümləsi adətən xəbərlə başlayır və bu cümlənin sonuna nid a işarəsi qo yulur. Əmr cümləsinin
əvvəlində xita b da işlənə bilər, bu zaman mür aciət olunan şəxsin ad ından sonra vergülişarəsi
qoyulur.
Ex :Lucie, prends ton livre! – Lüsi , kitabını g ötü r!
Ex :Tu par les- Sən danışırsan P arle! - Da nış!
Vous parl ez – Siz danışırsınız Parlez!- Danışın!
Nous par lons – Biz danışırıq Par lons!- Da nışaq!
Lakin bu f eillərdən sonra “en, y” zərfəvəzlikləri işlənərsə, “-s” şəkilçisi düşmür.
Tu parles de tes so uvenirs d'enfance. - Sən uş aqlıq xatirələrindən danışırsan.
Parles-en! – Ondan danış!
Tu vas à t a place. - Sən yerinə gedirsən.
Va à ta p lace! – Yerinə get!
Tu y vas. Sən or a gedirsən.
Vas-y! - Ora get!
Mürəkkəb c ümlə - ( la phrase complexe )
Azərbaycan dilində olduğu k imi fr ansız dilind ə də mürək kəb cüml ə nin iki növü vardır.
1. La pr oposition de coordination – Tabesiz mürəkkəb cümlə
Tabesiz mürəkkəb cümlə iki s adə cümlənin bir ləşməsindən əməl ə gəl ir .
Bu cümlələr bir-birinə ya vergüllə, ya d a tabesizlik bağlayıcılar ı ilə bağlanır.
Ex :On s onne, le maître entre dans la c lasse. - Zəng vurul ur, müəllim içəri daxil olur.
Les conjonc tions de c oordination – Tab esizlik bağlayıc ıları.
Bu bağlayıcılar iki və daha çox s adə cümləni bir-birinə bağlayır.
et- və, ou-y a, ya da, ni, ni-nə, nədə, mais-lakin, amma, cependant – ha lbuki, pourtant - baxmayar aq,
donc - beləliklə, ca r- beləki, c' e st p ourquoi - bunun üçün
Ex : Le tr ain cour ait à grand vitesse et par la portière ouverte nous voyions l es champs, les
forêts, les montagnes - Qatar böyük sürətlə gedirdi və biz açıq pənc ərədən çölləri, meşələri, dağları
görürd ük.
Ex :Le pr emier janv ier est un e grande fête, car nous célébrons le Nouvel An. - 1 yanvar böyük
bayramdır , belə ki, biz yenii liqeyd edirik.
Ex : Lili est très belle, mais elle a un ca ract ère insuppor table. - Lili ço x qəşəngdir, amma, onun
dözülməz xasiyyəti var.
Ex : Michel n'a pas eu le te mps de tout faire, pourtant il s' est levé très tôt. - Tezdən dur mağına
baxmayaraq, Mişelin hər şeyi etməyə vaxtı çatmadı.
Demain, c'est le 2 1 mars, don c les enfants au r ont u ne semai n e d e v acances de pr intemps. - Sabah
21 martdır, beləliklə, uşaqların bir həftə yaz tətili o lacaq.
La propos ition de sub ordination – Tab eli mürəkkəb cümlə
Tabeli mürəkkəb cümlənin b ir tər əfi o biri tər əfə tabe olur . Tabe edən tərəf baş cümlə tabe olan
tərəf isə budaq cümlə a dlanır və baş cümləyə tabelilik bağlayıcıları ilə bağlanır. Tabelili k
bağlayıcıları aşağıda kılardır:
Qui - m übtəda budaq cümləsini (propositio n subordonnée de sujet) b aş cümləy ə bağl ayır.
Qui c herche t rouve. – Ax ta ran t apar.
Qui langue a, à Rome va. – Çox dil b ilən yol biləndir..
Que, qui, dont, où – təyin budaq cüm ləsini (proposition subor donnée d'attr ibutive) baş cü mləyə
bağlayır.
Ex :Nous voyo ns les garçons qui jouent au football. – Biz fu tbol oynayan oğlanları gö rürük.
Ex : Les jeunes filles que vous voyez devant la caisse sont mes socurs. – Kass anın qabağında
gördüyünüz qızl ar mənim bacılar ımdır.Etc....
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
97
Əd əbi yyat:
1.И.Н.Папова, Ж.Казакова. “Грамматика ф ранцузцкого языка” – 1990
2. “Çra mmaire française”: N.Steinberg -19 72
3.Grammair e francaiseE.K.Nicolskaï. T.Y.Goldenberg -19 74
4.Grammair e francaise. N.Steinberq I Leninqrad
Proceedings of the 11th International Scient ific Conference
98
P E D A G O G I C A L C O N D I T I O N S F O R
E F F E C T I V E I N S T R U C T I O N I N
O C C U P A T I O N A L H E A L T H A N D S A F E T Y
F U N D A M E N T A L S W I T H I N T HE S Y S T E M O F
H I G H E R E D U C A T I O N
Ku ldzhat aev Mukht ar Maul et kazi evich
Lectur er, Ilyas Zhans ugurov Zhetys u Univers ity (Taldykor gan, Kaz ak hstan)
Darmankulov Kuat Omirserikovich
Senior Le cturer , Milita ry Departm ent, LLP “Interna tional Educa tio nal C orporati on”;
Reserve Li eutena nt Colon el (Almat y, Kaza khst an)
Abstr ac t. In the con te xt of increasing prof es sional risks, digit aliza on of producon
processes, and rising demands f or saf e prof essional beha vior , the improv ement of occupaonal
health a nd saf ety (OHS) educaon in higher educaon has become a pressing ped ag ogi cal
challenge. This study aims to theorec ally subs tan ate and exper ime nt al ly verify pedagogic al
condions f or e ff ecve instrucon in the fundament als of occupaonal health and saf ety in higher
educa on. The resear ch was conducted at Ily as Zhansugurov Z hety su Univ ersity and in volved 92
undergr aduate students divided into con trol and experi mental groups. The experi mental design
int eg r at ed Scenario-Based Learning and R e flecve Learning Cir cles, supported b y a Competency -
Based As sessment Fram ework. Quanta ve ana ly sis was perf ormed using the E ff ecveness
Growth Index and compar av e gain indicat ors. Th e r esults demons trat e a significan tly higher level
of competency develop ment in the experimen tal group compar ed to th e contr ol gr oup,
parcularly in c ognive- b eha vioral and mova ona l-v al ue components of OHS culture. T he
findings confirm that the s yst emac int egraon of acve and re flecve ped agog ical methods
enhances studen ts’ prof essional rea d iness f or saf e occu paonal beha vior and supports the
sus t ain able f ormaon of occ upaonal sa f ety cultur e in higher educa on.
K eywor ds: occupaonal health and sa f ety educaon; higher educaon; pedagogical
condions; scenario-based learning; re flecve learning circles; saf ety cultur e; compet ency -ba sed
assessment; prof essional risk prev enon
In the conte xt of socio-economic tran sf ormaons, the digital iza on of produco n
processes, and the incre asin g complexity of pr of essional acvies across v arious fields, the iss ue
of ensuring saf e work ing c ondi ons and f ost ering a sust ainable culture of occupaonal hea lth and
saf ety among futur e specialis ts becomes parcularly relev ant. The modern sy stem of hi g her
educa on is orient ed n ot only towar d the tr ansmission of prof essional knowledge and sk ills, but
also towar d the pr epar aon of gr adu at es capable of ac ng consciously in condions of
prof essional risk, complying with reg ulatory saf ety requir ements, and assum ing responsibility f or
the pr eservaon of their own lif e and health, as well a s that o f other s. In this reg a r d, ins trucon in
the fundamen t als of occupaonal health and saf ety within higher educa on funcons as a
significant componen t of prof essional training and requir es sci enfic a lly gr ounded pedagogical
support.
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
99
Despite the exis tence of a regula tory and leg a l framework and the mand atory incl usion of
occupaonal health and saf ety–rela ted disci plines in higher educaon curri c ula, their praccal
implement aon is oen charact erized by fragment aon, f orm alism, and i nsu fficient orien t aon
tow ard prof essionally relev ant si tuaons. Ins truc on is frequently red uce d to the ass imilaon of
theore cal provisions and regula tory req uiremen t s wi thout their deep comprehen sion or pracca l
applica on. This leads to a decline in s tudent mova on, sup er fic ial know ledge acq uision, and
an inadequate f ormaon of compet encies that ensure saf e prof es sional beha vior . This situaon
indicat es the need to r econsider pedagogical app roa ches t o teaching th e fundament als of
occupaonal health and saf ety and to iden fy the condions that ensure its eff ecveness within
the s ys tem of higher educa on.
Cont emp orary pedagogical res earch emphasiz es that learning eff ecveness is det ermined
not only by the conten t of instruconal mater ial, but also by the set of pedagogic al condions
under which the educa onal process is implement ed. Such condions include the p urposefu l
int eg r aon of occu paonal health and saf ety cont en t in to prof essionally orient ed disci plines, the
use of ac ve and int eracv e teaching methods, the modeling of real and poten ally haz ardous
occupaonal si tuaons, as well as th e org aniz aon of sy stem ac monitoring and assessment of
the f ormaon of rel evant compet e ncies. The implement aon of these condions mak es i t possi ble
to trans f orm instrucon in occu paonal health a nd saf ety fr om a f ormal component of the
curriculum int o an eff ecve instru ment f or the prof essional and per sonal devel opment of s tu dents.
Of parcular import a nce in this cont ext is pedagogical modeling of th e educ aonal process
orien ted tow ard the f ormaon of a conscious a tude to occup aonal saf ety issu es. The use o f
case-based methods, pr oblem-oriented and sc enari o- based learning , as well a s simulaon and
digit al technologies, contri butes t o the acv aon of s tu dents’ cognive acvity , the developmen t
of analy cal thinking , and th e ability to mak e well-r easoned dec isions under condions of
prof essional r isk. Such approaches ensure a tr ansion from the repr oducve a cquision of
knowledge to the acvi ty-based mastery of occu paonal health and sa f ety conten t, which
corr esponds to th e contempor ar y requir ements of the competency -ba sed paradigm of higher
educa on.
The sc ien fic liter atur e notes th at the f ormaon of an occu paonal health and saf ety
culture is a c omplex and mul-level pro cess tha t includes cog ni ve, va lue- mova onal, and
beha vioral components. E ff ecve ins t rucon in the fundamen tals of occu paonal health and
saf ety is possible only under condions of their integra ted dev elopmen t, which req u ires sy st emac
pedagogic al su pport. In this reg ard, parcular relev a nce is a ached to the idenfica on and
subs tan aon of pedagogi cal condions that ensure th e coordinat ed f ormaon o f knowledg e,
skills, abilies, and prof essionally significant personal qualies of studen ts a imed at compliance
with s af ety s tandar ds a nd the pr evenon of occupa onal risks.
Thus, the relev ance of the pr esent study is det er mined by the contr adic on between the
social and prof essiona l dema nd f o r training sp ecialists with a high lev el of occu paonal health and
saf ety cultu re an d the insufficient sci en fic an d methodological elab or aon of pedagogical
condions f or eff ecve instrucon i n occup a onal health and sa f ety within the sy stem of high er
educa on. Un der condions of moderniz aon of educaonal pr ograms and th e introdu c on of
innova ve pedagogic al technologies, t here em er ges an objecve need f o r the the ore cal
subs tan aon and experimen t al verifica on of a s et of ped agogical condions that con tr ibute to
enhancing the eff ecveness of t eaching th e f undamen tals of occu paonal health and sa f ety . This
deter mines the purpose of the s tudy , which consis t s in the theo recal subs tan aon and
e xperiment al ver ificaon of ped agogical condions f or e ff ec ve ins trucon in occupaonal hea l th
and s af ety in hi gher educaon, and also necessit ates the f ormula on of c orresponding resear ch
objecves aimed a t improv ing higher educaon in struconal pracce.
Proceedings of the 11th International Scient ific Conference
100
In scienfic res earch over the past decade, the problem of teaching th e fun dament als of
occupaonal health and saf ety (OHS) in higher educa on has been ex amined wi thin the broader
cont ext of the tr ansf orma on o f prof essional training a imed at devel oping su st ainable
compet encies f or saf e prof ession al acvity . Int ernaonal s tu dies emphasi z e that tradional,
norma vely ori en ted ap proaches to OHS educ aon fail to ensur e a n ad equat e level of le arner s’
awar eness and beha vioral readiness f or managing occupaonal risks. In parcular , Hämäläin en and
Saarel a (20 20) argue that the predom inance of r epr od ucve ins truconal pr acces cons train s the
devel opment of sy stem s think ing in the field of sa f ety and si gnifican tly red uce s the transf er of
acquired knowledg e int o prof essional pra cce [1] .
Cont emp orary scholar s increasingly conceptualiz e occ upaonal health a nd saf ety as an
int eg r av e pedagogical phe nomenon close ly link ed to the f orma on of the prof essional identy of
future specialists. F adier , De la Gar z a, and Di delot (2 021), f or ins t ance, in terpr et saf ety educao n
as a p rocess of cons trucng pr of essional e xperience, in which risk analy sis and er r or manag emen t
funcon as core didacc mechanisms [2 ]. A si milar p er specve is arcul ated by Már qu ez,
Gonz ález, and Hernánde z (202 1), who emphasize that embedding OHS conten t within
prof essionally orien ted disciplines f aci lit ates s tudents’ holis c u nders t a nding of the
int erdependen ce between producon pr ocesses and saf e occ upaonal beh avior [3].
In a me t a- analy c s tu dy , S alas et al. (2020) demons t ra te tha t scenari o-based and
simulaon-based learnin g lea ds to significan tly higher levels of beha vioral saf ety skill acquision
compar ed to tradional ins truconal f ormats [4]. T hese finding s are corr obor ated by Burk e et al.
(202 1), who sh ow that acve learning str ateg ies ex ert a mea ningful influence not on ly on the
cognive dimen si on, but als o on th e beha vioral co mponent of occu paonal s af ety culture [5 ].
A disnct str and of res earch addresses the digit aliz aon of OHS educaon in higher
educa on. Radian et al. (20 20), along with M akr ansky an d Pet ersen (2021), su bs tan ate the hi gh
pedagogic al potenal of virtual and augment ed reality t echnologies f or modeling haz ardous
prof essional situaons, highligh ng their eff ecveness in f ost ering pracce-o rient ed competencies
while minimizing re al-world risks [6; 7]. A t the same me, these author s emphasiz e that the mere
use of digital technologies does not automac all y guarant ee educaonal eff ecveness and mus t
be supported by pedag o gically grounded ins truc onal design and integr a o n.
From the s t andpo in t of cont emporary didaccs, the e ff ecveness of OHS educ aon is
deter mined by the coherence among learning o bjecves, cont ent, ins tr u conal methods, and
assessment s ys tem s. Within the frame work of cons trucve align men t theory , Big gs and T ang
(202 2) argue that discre pa ncies betwee n intended learning out comes a nd applied pedagogical
s t ra tegies sig nificantly diminish educa onal eff ecveness, pa rcularly in applied and
int erdisciplinar y domains such as occupaonal health and saf ety [8]. This a r gument i s further
devel oped in th e work of Lohmey er and T a ylor (2021) , w ho underscor e th e importance of
r eflecv e pracces an d f ormav e assessment in t he teaching of saf ety -relat ed disc iplines [9].
P sychological and pedagogical dimensions of o c cupaonal saf ety culture f ormaon also
occupy a prominen t place in inter naonal res earch. R eason (20 20 ) concep tualizes saf ety as the
outcome of c omp lex int eracons a mong indi vidual, or ganiz aonal, and educa onal f actor s,
emphasizing t he crical r ole of educaonal ins tuons i n the prev enon of occu paonal risks [10].
Similarly , Gr iffin and Neal (2021 ) demonstr at e that s tudents’ mova onal en gag ement constut es
a decisive fact or in com pliance with OHS s t andards, thereb y necessita ng tar geted pedagogical
int er ven ons a imed at s treng thening intrinsic mova on and responsibility [11].
K olb et al. (20 21) subs tanat e the eff ecveness of experien al learning approaches, in
which s tuden t s mas ter th e funda men t als of occ upaonal health and sa f ety through the analysis of
prof essional situa ons, st r uctured re flecon, and pr a ccal acon [12]. In turn, Zha o , McCo y , and
Kleiner (202 2) show that th e implemen t aon of a compreh ensive set of pedagogic al condions
including con tent integr a on, ac ve ins t ruconal methods, and sy st emac assessme n t results in
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
101
a s ta sc ally significant incre ase in OHS-rela ted competen ci es among s tud ents acr oss diver se
fields of study [13] .
Despite the subs tanal b ody of e xis ng resear ch, a crical analysis of the lit er ature rev eals
sever al unr es olved issu es. The major ity of s tudies f ocu s either on ind ividual pedagogical
technologies or on specific digit al t ools, wherea s a comprehen si ve su bs tan aon of pedagogical
condions f or eff ecve i nstru con in the fundamen tals of occupaonal he alth and saf ety with in
higher educaon r e mai ns insu fficiently develop ed. Moreov er , rel avely f ew studies propose
models orien ted towar d the s ys temic int egra on of OHS educa on into pr of essional tr ainin g and
their e xperiment al validaon. These gaps under scor e the need f or further resear ch aimed at the
devel opment and empirical tes ng of pedagog ically grounded models f or teaching occu paonal
health and saf ety in the s ys tem of hi gher educa o n.
The meth odological f r amew ork of the study was grounded in con tempor ary pedagogical
and a ssessmen t appro aches aligned with the comp etency -based mod el of higher educaon and
the developmen t of o cc upaonal health and saf ety (OHS) cultu re among f uture specialists. The
empirical s tudy w as conducted at Ilyas Zhans ugu rov Zhetysu Uni ver sity and inv olved 92 second-
and thir d-y ear undergr aduat e studen ts enr olled in pedagogical and engineeri ng-technical degree
progr ams.
P arcipants wer e assigne d to an e xperimen tal group (n = 47 ) and a con trol group (n = 4 5)
based on comparab i lity in baseline knowledge level s, age ch ara cteris cs, and academic
perf o rmance, which ensured the validity of the compar ave analysis. No s ta scally significan t
diff erences between t he group s wer e idenfied at the pre-t est s tag e .
Scenario-Based Learning (SBL) served as the prim ar y didacc me th od. The approach was
originally develo ped by Jonassen (2 0 11) and further conceptualiz ed by Erring ton (2014). SBL
in volved the s yst emac modeling of prof essiona lly relev ant si tuaons associat ed with poten al
occupaonal risks and violaons of OHS reg ulaons. Wit hin the learning process, students
analyz ed sc enarios, idenfied sources of haz ard, developed saf e acon str ategies , and jusfied
their decisi ons. The implement aon of SBL was designed to suppor t the developmen t of b oth
cognive and beha vioral c omponents of OHS com petencies.
The ass essment of pr of essional competence f ormaon was conducted usi ng the
Competen cy- Ba sed Assessment Framework (CBAF) proposed b y Mulder (201 4) and adapted f or
higher educaon cont exts by Biemans et al. (2020). Assessm en t was carried ou t according t o
prede fined criteria:
(1) ability to idenfy oc cu paonal risk s;
(2) jus ficaon of selected saf e acons;
(3) cor rectness in applyi ng OHS r egulatory requir ements;
(4) quality of decision-making argumen ta on.
E ach cr iter ion was evalua ted usin g a f our -level rang scale, allowing f or the gener aon of
quant av e i ndicat ors of compet ency developmen t.
The movaonal and value-based component of OHS c ulture was assessed through
R eflecve Learning Cir cle s (RLC) , developed by K or thagen (2017 ). T his method in volved s tructured
r eflecv e sessions during which students analyz ed their ac ons i n simulat ed scenarios and
arculated thei r personal a tudes towar d occupaonal saf ety . E valuaon crit e r ia included
awar eness of the si gnific ance of OHS, the level of prof essi onal responsibility , and the capacity f or
self -re flecon.
T o quan fy the eff ecveness of the implemen ted pedag o gical condions, th e E ff ecveness
Growth Index (EGI) was employed. This i ndex has been used in educaonal r esear ch by Hae
(201 2) and adapted f or compara ve exper ime nt al designs by Zhao et al. (2022) . The EGI was
calculat ed usi ng the f ollowing f ormula:
Proceedings of the 11th International Scient ific Conference
102
𝐸𝐺𝐼 = 𝑋
− 𝑋
) − (𝑋
− 𝑋
𝑋 − 𝑋
Where
𝑋
and 𝑋
repr esent the pos t -test and pre-t est mean scor es of the e xperimen tal group;
𝑋
and 𝑋
repr esen t the corr espondi ng values f or the con trol group;
𝑋 and 𝑋 deno te the maximum and minimum pos s ible values of the assessm ent scale.
The applica on of thi s index enabled the idenfic aon of competency gro wth aributa bl e
specifically to the exper iment al pedagogical interven on while contro lling f or th e eff ects of natura l
learning prog ression.
Addionally , the magnit ude of the pedagogical eff ect was es mated us ing Cohen’ s d , a
widely accepted measure in educaonal and ps ych ological resear ch :
𝑑 = 𝑀 − 𝑀
𝑆 𝐷 , 𝑆 𝐷 = 𝑆 𝐷
+ 𝑆 𝐷
2
Where
𝑀 and 𝑀 are the mean scor es of the e xpe rimen tal and contr ol gr o ups, r especvely;
𝑆 𝐷 and 𝑆 𝐷 are the c or r esponding standar d deviaons.
The combined use of con tempor ar y pedagogical approaches (Scenario-Based Learning,
Competen cy- Bas ed Assessment Framew ork, and R eflecv e Learning C ircles) tog ether with
quant av e analy cal indica tors (E ff ecvenes s Gr ow th Index and Cohen’ s d ) ensur ed the
methodological rigor , objecvity , and repr oduci bility of the study . This methodological design
enabled a valid and rel i able ev al uaon of the eff ec veness o f pedagogical condions f or teaching
the fundament als of o ccupaonal health and s af ety in higher educa on.
A t the firs t s tag e of r esults analysis, the dynamics of the f orma on of cogniv e and
beha vioral components of occupaonal health and sa f ety competencie s developed through
scenario-based learning were ex amined. Par cular aen on was given to changes r elat ed to
s t udents’ ability to idenfy occu paonal risks, jus fy the selecon of saf e ac on s t r at egi es, and
provide r e asoned argumen ts f or deci sion-making in simulated prof es sional situaons. A
compar ave a naly si s of pr e-tes t and pos t -test indica tor s made it possible to det ermine the na ture
and direcon of changes in b oth the e x perimen tal and contr ol group s (fig .1).
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
103
Fig.1. Mean Scor es of Occupaonal Health and S af ety Competencies Bef or e a nd A er the
P eda gog ical Int erven on
The obt ained r e sults indicate fundamen t all y differ ent trajectories in the devel opment of
occupaonal health and saf ety competen cies among s tudents in the contr ol and experi ment al
group s. The m odes t increase observed in the contr ol group ma y be inter pret ed as a consequence
of tradional instru con f ocused primarily on the assimilaon of normav e and theore cal
cont ent, wher e l earning i s larg ely orient ed towar d the repr oducve r eproducon of knowledg e .
This paern of ch ang e corr obora tes fin dings rep orted in previous studies, which demons trat e that,
in the absence of learners’ acve eng agemen t in risk a nalysis and decision-making processes,
occup a onal saf ety educ aon f ails to facilit at e the tra nsi on fr om declar ave kn owledge to
pracce-orien ted acon. The lack of p ronounced i mprovem ent in decision -making ar gument aon
and risk idenficaon further indicat es the limit ed capacity of tr adi onal pedag ogical app r oaches
to support the f ormaon of the beha vioral componen t o f occ upaonal saf ety culture.
In con tras t, th e e xperimen tal group demons tra ted a st able and subst anal increase across
all assessm en t criteria, al l owing scenar io-based learning to be considered an eff ecve p edag ogical
tool f or the devel opment of pr acce- orien ted occupaonal health and saf ety compet en cies. The
significant impr o veme nt in prof essiona l risk iden ficaon and the jus ficaon of saf e acon
s t ra tegies can be arib uted to the f a ct that sc enario-based modeling crea tes a cognively rich
learning en vironment closely aligned with r eal pr of essional condions. Within such en vironmen t s,
s t udents are r equir ed to int egra te regulat ory knowledge, analycal skills, and persona l
r esponsibility , which contri butes to the f ormaon of уст ойчивых paern s o f prof essional think in g
and a conscious a tu de tow ard occupaonal s af ety issues.
P arcul ar importance is a ached to ch anges in the integr at ed competency indicat or , which
r eflects th e sy s tem ic na ture of th e pedag ogical int ervenon. The g r owth of this indi ca tor in the
e xperiment al group sug ges ts no t only the acquision of individual elements of occ upaonal saf ety
knowledge, but also the f ormaon of a coher ent competency structur e en compassi ng cogniv e,
beha vioral, an d reg ul atory componen t s. From a pedag o gical per sp ecve, these findings confirm
the eff ecveness of scenario-based learning i n facilit ang the transi on from fragmen ted
knowledge acqui sion to holis c prof essional readiness. The results are consis tent with
cont empor ary int ernaonal r esearch em ph asizing that th e modeling of pr of essi onally si gnifican t
0
0,5
1
1,5
2
2,5
3
3,5
4
Identification of
occupational risks
Justification of safe
action selection
Application of OHS
regulatory
requirements
Decision-making
argumentation in risk
contexts
Integrated competency
score
Control Group (n = 45) - Pre-test Control Gro up (n = 45) - Post-test
Experimental Group (n = 47) - Pre-test Experimental Group (n = 47) - Post-test
Proceedings of the 11th International Scient ific Conference
104
situaons repr esen ts a k ey condion f or f os tering occ upaonal saf ety cultur e in higher educa on
and f or ensuring the su st ainability of learning outcomes b eyond the classro om conte xt.
Within the analysis of the se cond method, the dynamics of the mova onal and value-
based componen t of occupaonal health and sa f ety culture, devel oped through re fle cv e
eng agemen t with learning and prof essional experience, wer e ex amined. Parcular a enon was
paid to the comparison of baseline indicat or s in the c ontr ol a nd experi ment al g r oups, which were
compar abl e in term s of ini al levels of development, as well as to the ass essment of ch ange
pa erns f ollowing the implemen taon of re flecve pr acces. This analyc al approach minimiz ed
the influence of inial d iff er ence s and enabled a more objecve evalua on of the pedagogical
e ff ect of the appli ed method (fig .2).
Fig.2. Dynamics of the Mova onal and V alue-Based Comp onen t o f Occu pa onal Health
and Saf ety Culture (%)
The analysis of results ob t ain ed through the applicaon of the R eflecv e Learning Circles
method demons trat es a posive dynamic in the developmen t of the mova onal and value-based
componen t of occ upao nal health and saf ety culture among s tudents in both gr oups, given
compar abl e base line in dic at ors. The r ela vely small diff er ence in inial values between the contr ol
and experimen tal group s (3-4 per ce nt age poi nts) indicat es th at th e observed po s t -interven on
changes cannot be arib uted to inial sample heter ogen eity . The modera te increase in indicat ors
observed in the con trol group re flects a natu ral enhancement of awar eness and responsibility
within the framewor k of tradional instrucon; howev er , this growth rema ins l imit ed and does not
lead to a subs t anal trans f ormaon of int ernal atudes that underpin the sus t aina ble ob se rvance
of occ upaonal saf ety st andards.
In the experimen tal gr ou p, a more pr onounced in crease acro ss all assessmen t c riteri a was
idenfied, indicang the t ar get ed impact of re flecve prac ces on the dev elopment of intern al
r egulat ors of saf e prof essional beha v ior . Struct ured r eflecon on lear ning and prof essional
e xperience facilit ates the compreh ension of c ause-eff ect rela onships between prof essional
acons and the ir poten al consequences, the r eby stre ngthening the personal inter nali z aon of
occupaonal saf ety norms . The growth observed in prof essional re sp onsibilit y and value-based
accept ance of saf ety req uiremen t s sug ges ts a transion fr om ext ernally imposed norms to
int er nally movat ed beha vior , which is reg arded in pedagogical theory as a k ey prer equisite f or the
sus t ain ability of educaonal outcomes .
0 1 0 20 3 0 40 5 0 60 7 0 80 9 0 100
Awareness of the importance of occupational safety
Professional responsibility for safety
Capacity for reflection and self-assessment of actions
Value-based acceptance o f OHS standards
Integrated motivational value indicator
Experimental Group (n = 47 ) – Post-test, % Cont rol G rou p (n = 4 5) – P ost-test, %
Experimental Group (n = 47 ) – Pre-test, % Contro l G rou p (n = 45 ) – P re-test, %
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
105
P arcul ar si gnificance is aributed to the int eg rat ed movaonal-v alue indica tor , which
r eflects the sy stem ic natur e of the changes induced by re flecve ins truconal methods. Th e
achieveme nt of hi gh pos t -t es t values in the experiment al group, in the absence of abrupt
fluctuaons, allow s the r esults to be in terpr eted a s the outcome of a consi st ent and pedagogic ally
grounded p r ocess of o ccupaonal saf ety culture f ormaon. Co llecvely , the findings con fir m that
R eflecve Learning Circles funcon a s an eff ecve complem ent to acv e instru c onal methods b y
deepening the per so nal me aning of prof essi onal sa f ety an d crea ng condions f or the l ong-term
adheren ce to occupaonal health and saf ety s tandar ds in future pr of essi onal pracce.
T o quant av el y ass ess the eff ec veness of the r eflecve method, percent age ind ica tor s
wer e use d to repr esent the proporon of s tuden ts who achieved su fficien t and high levels of
devel opment of the mova ona l and v alue-based component of occupaonal health and saf ety
(OHS) cult ure. An integr ated indicator was applied as a summary measure. Its values wer e as
f ollows:
Contr ol group: 66% (pre- tes t) and 73% (p os t -test);
Experiment al group: 69% (pre-t est) and 86% (pos t -tes t).
The absolut e gain in the con trol group was:
Δ𝐶𝐺 = 73 − 6 6 = 7 percen tag e points (pp)
The absolut e gain in the experimen tal group was:
Δ𝐸𝐺 = 86 − 69 = 17 pp
The diff erence in gains betw een t he e xperiment al and contr ol g roup s was ther ef ore:
Δ = 17 − 7 = 1 0 pp
These values i ndicate a more pronounced posive dynamic i n the exper ime nt al group,
associated with the implemen taon of re fle cve pr ac ces.
T o determi n e the net eff e ct of the pedag ogical i nt er ven on , th e E ff ecveness Gr owth Index
(EGI) was calcu lated usi ng the f ollowing f o r mula:
𝐸𝐺𝐼 = 𝑋
− 𝑋
) − ( 𝑋
− 𝑋
100
Subs tung t he empirical values yields:
𝐸𝐺𝐼 = ( 86 − 69) − (73 − 66 )
100 = 17 − 7
100 = 0.10
The obtained value of EGI = 0. 10 indicat es a moder ately expr essed but peda gogical ly
meaningful eff ect of the Re flecve Lea rning Cir cle s method on the f ormaon of the mova onal
and value-based componen t of OHS c ulture.
The r elave g ain i n the e xp eriment al group was c alcu lat ed as:
𝑅 𝐺 = 86 − 69
69 × 100 = 24.64%
The r elave g ain i n the con trol gr oup was:
𝑅 𝐺 = 73 − 66
66 × 100 = 10 .61%
Thus, the rela ve g a in in the experi ment al group ex c eeds that of the cont rol group by more
than 2.3 mes, pr ovi ding addional evidence of the t arg eted impact of re flecve pra cces on the
devel opment of st abl e value orien taons re lated to occupaonal saf ety .
The results of the quant ave analysis demonstr ate that the obser ved changes cannot b e
e xplained solely by natural educa onal progr ession. The mod era te increase in th e contr ol group
r eflects the back gr ound eff ect of tradional i ns trucon, whereas the subs tanally higher gains and
the EGI v alue observed in the experim ent a l group confirm the eff ecveness of R eflecv e Learning
Circles as a pedagogical method aimed at f oster i ng an inter nally mova ted and conscious atude
tow ard occupaonal health and saf ety . The quan ta ve findings are consis ten t with qualita ve
observa ons and indica te the s ys temic na ture of the ped agogical int ervenon, con tribung to the
sus t ain ability of educaonal outco mes.
Proceedings of the 11th International Scient ific Conference
112
As a pedagogical recommendation , this study pro pos es the implementation o f an an imated
educational website based on th e tale “Nasreddin and th e Khan” fo r primary English language
instructi on. The platform includes an interactive animated version of the f airy tale, AI-generated
vocabulary tasks, and audio narr ation to s upport listening skills. Such a multimodal di gital r esource
creates an age-appropr iate, engaging, and culturally meaningfu l learning envir onment, making
English lessons more accessible and motivating for young learn ers.
In conclusi on, the integr ation of traditional Kazakh st or ytelling with con te mporary AI
technologies represents an innovative and pedagogic ally effectiv e appr oach tha t str engthens
language proficiency, fosters cultural understanding, and align s with modern educational
requir ements.
References
1. Coll ection o f Didactic Games in Three Languages. Method ological Guide. Astan a, 2013,
pp. 3–5 .
2. Kadyrgaliyeva S.I., Yes bergenova G. Teaching Sc hool Students the Engli sh La nguage. West
Kazakhstan State Univer sity, 2011, pp. 10– 14.
3. Vereshchagi na I.N., Rogova G. V. “Methods of Teaching English at the Initial Stage in
General Educa tion Institutions. ”
4. H ans Christian Andersen . Fairy T ales Told for Children. Fir st Collection . p. 5
5. Kaz akh Fairy Tales - Almaty kitap, 201 7, p. 7.
6. Luck in, R. (2018). Machine Learning and Human Intelligence: The Future of Edu cation in
the 21s t Century.
7. K. A. Sarbasova - Innovative Pedagogical T echnologies . Almaty: Atlas, 2006. 176 p.
8. Koz hanasyr and the Khan. - Er tegiler.kz. https://ertegiler.kz/stor y/kozhanasyr-men-khan
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
113
I N N O V A T I V E A P P R O A C H E S T O T E A C H I N G
F O R E I G N L A N G U A G E S T O C H I L D R E N W I T H
H E A R I N G I M P A I R M E N T S T H R O U G H T H E
U S E O F A I -B A S ED T E C H N O L O G I E S
Taub ai Altyn ai Orazb ekky zy
First -year mast er's stud ent
Nabid ulli n S. Aib olat
PhD, Senio r Lectur er
Abai Kaz akh National Pe dagogical Univ ers it y (Almaty , Kazak hstan)
This article examines innovative appr oaches to teaching for eign languages to children w ith
hearing impairments through th e integr ation o f AI-based technologies. Hear ing i mpairment
causes numerous d ifficulties on the develop ment o f or al communica tion skills. Usu ally,
rehabilitation is based either on spoken language or sign language. Foreign language learni ng
among HI is no longer an except ion but a fr equent educa tional ch allenge, especially when HI
learners ar e part of the inclusion process. Lear ne rs are f aced not only with diffi culties in speech
perception but also insufficient L1 knowledge and t ogether with their tea chers with lack o f proper
teaching mater ial, envi ronmental suppo rt etc. In order to address th is issue so that necessary
advancement of th e tea ching process ca n be made, both qu alitative and quant itative st udies
should b e conducted. The stu dy aims to identify eff ective digita l tools and meth ods tha t enhance
auditory, visu al, and multi-modal language acquisition. A mixed-methods design was employed,
combining literature anal ysi s, observational data, and exper imental activities with AI a pplications.
The findings demonstrate that adaptive sp eech-to-text to ols, visual recogniti on sy stems,
interactive AI tutors, and ga mified lear ning platfo rms significantly improve vocabular y a cq uisition,
listening discriminati on, and communica tive competence. The study highlights t he sci entific and
practi cal significa nce of implementing AI t echnologies in special education and pr ovides
recommendations for further res earch and pedagogical pr actice.
Keywords : A r tifici al Intelligence, students with hearing imp airment, hard of hearing
students, for eign language, modern method s.
ИННОВАЦИОННЫЕ П ОДХОДЫ К ОБУ ЧЕНИЮ ИНОСТРАННЫМ ЯЗЫКАМ ДЕТЕЙ С
НАРУШЕНИЯ МИ СЛУХА С ИСП ОЛЬЗОВАНИЕМ ТЕХНОЛОГИЙ НА ОСНОВЕ ИИ
В данной стать е расс матриваются инновационные подх оды к обучению иностранным
языкам детей с нарушениями сл уха посредством интеграции технологий на основ е
искусственного интеллекта. Нарушение слуха вызывает мно жество трудностей в развитии
навыков устной ко ммуникации. Обычно реабилитация основывается либо на уст ной речи ,
либо на жестовом языке. Изучение иност ранного языка ср еди детей с нарушениями слуха
уже не является искл ючением, а становится частой образовательно й задачей, особенно
когда такие обучающиеся включены в инклюзивный процесс. Уч ащиеся ст алкиваются не
только с трудн остями восприятия речи, но и с недостаточн ым у ровнем владения родным
языком, а также с отсутствием необходимого учебного материала и соответств ующей
образовательной среды. Для решения данн ой проблемы и обеспечения прогресса в
образовательном процессе необ хо димо проводить ка к качес твенные, так и количественные
Proceedings of the 11th International Scient ific Conference
114
исследования. Цель и сследования — определ ить эффективные цифровые инст рументы и
методы, спосо бствующие раз витию сл ухового, визуального и мул ьтимодального осв оени я
языка. Применён сме шанный метод исследования, включающий анализ литературы,
наблюдательн ые да нные и эксперимента льные за дания с использовани ем ИИ -при ложений.
Результаты показывают, что адаптивные инструменты распознавания речи, системы
визуального распознавания, интерактивные ИИ-тьюторы и иг ровые образовательные
платформы значите льно улучшают усво ение сл оварного запаса, различение на слух и
коммуникатив ную компетенцию. Исс ледование подчёркивает научную и практическую
значимость внедрения технологий ИИ в специальное образование и даёт рек оме ндации для
дальнейших исс ледований и педагогической практики.
Ключевые слова: искусств енный интеллект, обучающиеся с нарушением сл уха,
слабослышащие обучающи еся, иностранн ый я зык, современные методы
Introduction
The 21 st centur y is the era of information technology. The current globalization pro cess
requir es the sea rch for new ways to improve edu cation and sci ence. At the fo refront of this search
is artifici al intelligence (AI). Pr eviously, this technology, which was only an object of sci entific
imagination, is now penetrating all sp heres of human life - healthcare, production, finance,
industr y, and most importantly, the educa tion system. Especially in the field of teaching and
learning foreign languages, the potential of AI seems limitless. Compared to traditional methods,
it allows you to pers onalize the lear ning proces s, adapt the cur riculum t o the i ndividual pace and
abilities of th e learner, and pr ovide in stant feedback. In addition, it mai ntains the learner 's interest
for a long time th r ough game elements, automated assessm ent, and tools fo r increasing
motivation. Artificial intelligence is no t ju st an additional tool, it is an innovative mechanism th at
forms a new paradig m of language teachin g. Therefore, it is an urgent iss ue to scientifically st udy
the role and potenti al of AI in improving t he quality of language lear ning in our time [1].
Individuals wi th hea r ing imp a irments are those who have lost the ability t o hear within the
range of 25–90 decibels. These individuals can be divided into four lev els: mild hearing los s,
moderately sever e hearing loss, severe hea ring loss, and profound hearin g los s [2]. Th e
importance of l earning a foreign language similarly applies to children with special needs, such as
deaf and hard-of-he aring children. The responsibility of second language professionals is to
acknowledge and address the requi rements of this particular gr oup wi th special needs and to
actively promote equal opportunity in forei gn language educa tion. This can be achieved by
thoroughly examining t heir ci rcumst ances, increasing awareness of their needs, and pr oposing
effective solutions to the difficulties t hey encounter [3]
Nowadays, lear ning a foreign la nguage is no t limi te d to just memorizing vocabular y and
mastering gr ammar r ules. Thanks to the r apid devel o pment of learning te chnologies, artific ial
intelligence has become an integral pa r t of lan guage teaching. It can not only increase the
effectiveness of traditional meth ods, but also offer new opportunities tailor ed to the indiv idua l
char acteristics of the learner. To su mmarize the main advantages of AI in languag e teachi ng, fi rstly,
AI personalizes the learning process: it syst ematically identifies the weaknesses of each student,
often unclear grammatical st r uctu r es, vocabular y and types of er rors, and provides individual tasks
accor dingly. The fact that such “smart tutors” ca n increase the effectivene ss of lear ning has been
confirmed in va rious reviews and meta-analyses. Secondly, AI’s voice recognition (ASR —
automatic sp eech recognition) te chnologies acc urately ass ess pronunciation and provide
immediate feedback. This is an indi spensabl e tool, especially for t hos e who ar e learning to speak
as a second language: incorr ect accents, sy llables, and ar ticul ation featur es are immediately visi ble
and can be corrected. Such stu dies have sh own that ASR can improve the q uality of pr onunciation
and speech. Third, the large platfor m and data scale ensure that the system can "learn" [4]
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
115
In the digi tal era, AI-based technol ogies provid e new opportunities f or foreign language
instructi on, particu la r ly for c hildren with hear ing impairments. Traditiona l teachin g approac hes
are not always effective for this group of learners; therefore, the use of innovative, adaptive digital
tools has become both a scientific and pr actical necessity.
Research aim - to identify innovative approaches for effectively organizing foreign language
learning f or children with hearing impair ments through AI technologies.
Objectives: to analyze AI-based educational tools; to determine effective instr uctional
methods;to present w ays of integr ating these tools into the l earning process.
Object - the proce ss of foreign language acqui sition by c hildren with hearing impair ments.
Subject - meth ods and tools based on the use of AI technologies.
Hypothesis: if AI techn ologies ar e systematical ly applied in foreign language lessons, children
with hear ing impair ment s will show not able improvement in language s ki lls, par ticularly li stening
and speaking.
Th e Main P art
R. N . I. A. Ra zak and N. Se nan said that the education of hearing-impaired p eo ple is less than
that of the general population . May affect communication skills and academic ach ievement,
however, exist ing applications are developed for the st udy of si gn language, for example a s a
module to learn. An d only the lear ning ma ter ials in the form of video s are used. Using augm ented
reality (KTBM AR) , it has been develope d to pro vide user s with learning modules and activities that
they can inter act with. and able to test their own k nowledge. The meth od use d in applicat ion
development is the ADDIE model, which consi sts of analysis, design, development,
implementation, and evaluati on. Fr om the experimental results, it w as found that the appl ication
was successfu lly d eveloped at 94% within the acceptable limit s accor ding to the Syst em Us ability
Scale (SUS). Therefor e, it ca n be conclud ed that KTBM AR is suitable for learning sign language [5].
One of the most cu rrent techno logies that has been demonstra ted to have a beneficial
effect on th e educational process is artificial in telligence technology. In Amrizal and Ain i [6 ], Ric h
and Knight claim that artificial intelligence is a technolog y that ena bles computers to ca rry out
tasks that people do. A nu mber of studies hav e revealed tha t arti ficial intelligence has a significa nt
influence on how students lear n [7], which is r elevant from the perspective of education. In certa in
fields, artificial intelligence is still in its infancy, yet it is still useful to experimen t wi th it. A num ber
of educati onal initiatives, including the usage of IBM Watson, have made use of intelligent tutors.
In recent years, AI resear chers have wor ked to make it possib le for students to lear n new
things through th e "support learni ng" approach. Artificial intelligence technology may r eplicate
human thin king, le arning a ids, and ma ny more uses i n differ ent face ts of training, d emonstrating
ever-improving us ability .
Based on the fi ndings of the research, the implication of using Ka hoot learning media
effectively ca n increase students' English learning outco mes at SDLB B Budi Nur ani in Sukabumi
City. Students' ability to grasp and apply En glish topics impro ves si gnificantly after util izing Kahoot.
Further more, the uti lization of Kahoot can boost student interest and involvemen t in learning [8].
Methodol ogy
Methods and t echniques i n teaching st udents with hearing impairment (hard of hearing
students) a foreign language It is necessa ry to adapt and use the fo llowing teaching methods,
which pr ovide the most complete tr ansmission, perception, reproduction and processing of
educational information in an accessible for m: − visua l, explanatory and ill ustr ave teaching
methods contribute to mastering th e basis of ideas an d concepts about the studied obj ects and
phenomena. Th e project method is base d on the or ganization of collective r esearch activity with
separation of roles and responsibilities, mutual assistance and suppor t from ot her students, an
Proceedings of the 11th International Scient ific Conference
116
interpr eter or assistant will help the st udent cop e with the task; − search-based tra ining methods
allow to develop th e activity of people with hearing impairment and emphasize the most
important parts of information, wh ich will be necessa ry for further integrated professi onal
development in the existing labor market; − the peer-t o-peer method all ows to attract
groupmates of a student with di sabilit y to solve problems to gether, introduce an element of
positive c ompetitiveness in the educational process and in cr ease motivation, academic
perfor mance of all students in the gr oup. Tr aining teaching methods provide repetition and
consc ious consolidating of th e basic skills. When developing training exercise s, teachers sh ould
take into account s tudent's r eal intellect ual abilities and ensure his speech formation, the
disclosu re of his a bility to adapt; − accompanying t eaching methodsinclude providing
comprehensive psy chological and pe dagogical support to a student (de termining the level of his
intellectual abilit ies, creating specia lized didactic mater ial, condu cting r e medial clas ses, etc.).
When implementing this method, we sh ould consider a syste m of real assessment of students’
educational needs; − assessment and reflexive teaching methods co nsist of introduc on of
integrated s ystem assessment, self-asse ssment [9]
One of the most significant advan cements in th is field is the dev elopment of Al-powered
platforms that provide rea l st imulation dialog for language learne r s. First and foremost . Al-
powered platf orms can pr ovide language le ar ners with a r ealistic and immersive conversatio nal
experience. Thr ough the use of natural language proce ssing and machine learning algorithms,
these platfor ms are able to simulate au thentic di alogues and inter actio ns in Eng lish, allowing
students to p articipate in controlled-assi sted environment with their s peaking and list ening skills.
This real s timul ation di alog pl atfor m ca n cr eate a more dy namic and engaging learning exper ience,
as st udents are able to communicate w ith A l- cr eated persons and ge t instant feedback on their
language profici ency [10]. A l can also p rovide personalized a nd adaptive dia log s imulations based
on each studen t's individual needs and learning goals. By analyzing st udents' language profici ency,
learning pace, and area s for improvement, AI-pow er ed platforms can tailor the dialog simulations
to address specifi c language ch allenges and provide ta rgeted suppo r t. This persona lized approach
can enh ance the effectiveness of lang uage l earning, as st udents are able to focus on a r eas that
requir e improvement and make meaningful prog ress in th eir language skills [11].
Apps like Ch ildJourney, HearingF irst, and Aleem analyze the language a nd audiol ogical
indicators o f thousa nds of c hildren and continuously improve their learning models. These
platforms collect data on each ch ild’s hearing le vel, sp eech development, sound discrimination
scor es , and visua l support needs, and the system uses t hat information to recommend the most
effective individual learning path.For example, ChildJour ney uses data analysis t o adjust
vocabulary load according to the child's hear ing age, whi le HearingFirst automatically adapts tasks
by tracking the dynamics of liste ning skills development. The Al eem platfor m is particularly
effective in analyzing err ors made by visually enhanced lex ical materials, video lesso ns, and
chatbots, w hich provides additional suppor t for children with h earing impairments in
understanding sp oken language.
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
117
Despite being d ifferent platforms, Ch ildJourney, Hear ingFirst, an d Aleem shar e three key
criter ia th at make them effective fo r supporting children with hearing impairment i n learning
English:
Data-D riven,
Personalized Learning
They track each child’s responses, progress, listening attempts, and
accur acy.Children receive tasks t hat match their hear ing age , linguis tic
level , a nd auditory abilities . :
Multisensor y,
Auditory-Suppor ted
Instruct ion
Videos wi th clear speech and faci al cuesHigh-quality auditory sti muli
optimized fo r CI/ HA user sVisual sca ffolding (images, ico ns, gestu res ,
captions) Step-by-step auditory–verb al practi ce.C hildren with hear ing
impairment rely on visual reinforc ement to understand
speech.Enhance s speec h per ception, sound discrimination, and wor d
mapping.M akes En glish more acc essible even when auditor y input
alone is ins ufficient.
Progr ess Monitor ing +
Family & Te ach er
Guidance
Built-in too ls a utomatically tr ack listening and language
growth.Par ents receive recommendations, home-practice act ivities ,
and feedback. Teachers/Specialists can adjust goals based on real
perfor mance data.Children with hearing loss progress fa ster when
family involvement is strong.Ear ly detection of difficulties allows for
timely intervention.Ensures systematic auditory training and
consisten t home supp ort.
Unique Features of Each Platfor m for Children with Hearing L oss
ChildJourney HearingFir st Aleem
Designed specifically for
children with co chlear
implants or hearing
aids.Includes auditory-verbal
therapy (AV T)
modules.Pr ovides
individualized list ening goals
based on hearing age.O ffers
parent guida nce and daily
listening routin es.
Evidence-based learning
resourc es focu sed on
Listening and Sp o ken
Language (LSL). Strong video-
based instruct ion with clear
articul ation.Emphasizes
parental coaching and early
intervention. Supports
building listening
environments in dai ly life.
AI-powered adaptiv e
technology for English
language learning. Analyzes
pronunci ation and list ening
challenges using ma ch ine
learning.Adjus ts speech rate,
vocabulary difficulty, and
visual cues.Suitable for
school-age d deaf /HoH
learners developing second-
language skills
Conclus ion
In conclusion , a r tificial int e lligence is a p owerful tool that has opened a new era o f language
learning a nd teachin g. It not only increases th e effectiveness of tr aditional methods, b ut also
personalizes the lear ning proce ss, adapti ng it to the pace and level of each learner. With the h elp
of AI technologies, co rrecting gr ammatical errors, expanding voca bulary, improving speaking skills,
and developing list ening skills hav e become much easier and m ore interesting than e ver before.
The over all analysis indicates that AI -b ased platforms offer significant sc ientific and practical
advantages in teaching foreign l anguages to ch il d r en w ith hea ring impairments. Their ability to
personalize instruction , e nhance auditory a cc es s through multisensory input, and involve families
in syst ematic language support contributes to a more effective learning experience c ompared to
traditional methods.The comparison of Ch ildJourney, HearingFirst, an d Al eem shows that AI
technologies not only acco mmodate hear ing-re lated differences b ut also create lear ning
conditions in which children ca n meaningfully develop listening, sp eaking, and co mprehension
Proceedings of the 11th International Scient ific Conference
118
skills. Ther efore, t he hypothesis of the resea rch—that sy stematic use of AI will l ead to noticeable
improvement in f oreign language acquisition amo ng hard-of-hearing ch ildren—is strongly
supported by both theoretical evidence and practical implications.Thus, AI serves as a
transfo rmative tool that r eshapes foreign l anguage educa tion f or l e arner s with hea ring
impairments, ensuring gr eater accessibility, inclusivity, and long-term developmental
outcomes.T he most important thing is that in order to u se artificial intelligence ef fect ively, it must
be combined w ith a pur poseful appr oach and t he r ight met hodology. On ly t hen will AI become a
reliable companion that teaches language quickl y, efficiently, and in real-li fe situat ions .
References:
1. Godwin-Jones, R. (2018). "Emerging Technologies: Artificial Intelligence in L anguage
Learning. " Language Learning & T echnology , 22(2), 4-2 0.
2. T. Sookpatdhee, “The art s use to bui ld s kills for hearing impai red,” The Golden Teak: Humanity
and Social Sci ence Journal (GTHJ.), vol. 23, no. 2, pp. 1–13, May–Aug 20 17
3. Domagała-Zyśk, E. (E d.): English as a for eign language for deaf and hard of hearing per sons in
Europe. Wydawnictwo KUL, 2013
4. Affandi, A. (2018). Teaching EFL to Deaf and Ha r d Heari ng (DHH) Students: A Lesson from Two
Special Needs Senior Hi gh Schools. Un iversitas Teknokrat Ind onesia, 45
5. Mobile Learning for M anually Cod ed M alay Sig n Language Us ing Augmented Rea lity. Abdul
Razak & Senan, 2 022
6. Amrizal, V., & Aini, Q. (2013) . Kecerdasan Buatan. Jakarta: Halaman Moeka
Publishi ng
7. Groff, J. S. (2017). Personalized learning: The sta te of th e field & f uture di recti ons.
Center for Cur riculum Redesign, 47
8. HOW ARTIFICIAL INTELLIGENCE CAN BE EFFE CTIVE FOR TEACHING ENGLISH TO HEA RING
IMPAIRED LEARNERS. October 2023. Susiy anti Rusyan
9. Specifics of teaching a foreign language to students with hearing impairment (hard of hearing
students) /Artemenkova, Artemenko, Kalashnikova, 2019
10. Woo, J., & Choi, H. (2021). Ar tificial intelligence in compu ter-assist ed language learni ng: A
syst ematic review.
11. Wang R. Research o n the Ar tificial Intelligence Pr omoting English Lear ning Chan ge.
Proceedings of th e 3rd Inter national Conference on Economics a nd Management, Education,
Humanities and Social Sciences (EMEHSS 2019). Suzhou, Ch ina. Advan ces in Social Science,
Educatio n and Humaniti es Research, vol. 325.
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
119
A R T I F I C I A L I N T E L L I G E N C E A S A T O O L F O R
D E V E L O P I N G C O M M U N I C A T I V E
C O M P E T E N C E I N F O R EI G N L A N G U A G E
L E A R N E R S
Tolk yn Di ldab ek
First -year mast er's stud ent
Nabid ulli n S. Aib olat
PhD, Senio r Lectur er
Abai Kaz akh National Pe dagogical Univ ers it y
(Almaty , Kazak hstan)
This paper ex amines the eff ecveness of arfici al int elligence technologies in dev eloping
communica ve competence among f or eign language learner s. The study provides an overview of
major theorecal per specves on communic ave compet ence, hig hlighng its linguis c,
sociolingu is c, discour se , and s trat egic components. The liter atur e review demonstr ates that AI
supports per sonalized lea rning , crea tes int erac ve language en v iron ments, and off er s rapid,
accurat e f e edback. In the empirical part, ChatGPT , ELSA [6] Speak, Du olingo [4 ], and Grammarly
[5] wer e u sed, an d impro vemen ts in speaking , list ening, r eading, and wring were analyz ed usi ng
a mix ed-methods approa ch . The results indi ca te si gnificant sk ill enhancement, reduced speaking
anxiety , incre ased mova on, and gre at er learner autonom y . Over all , the study con firms that AI is
an eff ecve and accessi ble t ool f or en hancing communicav e competence.
K eywor ds: Arficial int elligence, communicav e competence, language learning , adap ve
learning, AI tools
В д анной рабо те исс лед уется эффекти вность применения техно ло гий искусственног о
инте ллекта в развитии коммуника ти вной компет енции учащихся, изучающих иностранный
язык. Представлен обзор основ ных теоретических под х одов, раскрывающих языковой,
социо лингвистически й, дискурси вный и стратег иче ский к омпоненты к омпетенции.
Литер атурный обзор показывает , что ИИ обеспечивает персонализированное обучение,
формирует интерактивную языковую среду и быстро корректирует ошибки. В прак тической
част и применялись пла тформы Cha t GPT , ELSA Speak, Duo lingo и Gr ammarly; на осн ове
смешанного мето да были оценены у лучш ения навыков говорения, ау диров ания, чтения и
письма. Р ез у ль та ты свидет ельствую т о значите л ьном прогрессе, снижении речевог о ст рах а и
повышении мотивации. Исс ледован ие подтв ерждает , что ИИ является эфф ективным и
доступным инструмент ом в обучении иностр анному языку .
Ключевые слова: Иску сс твенный интеллект , коммуника тивная компетен тн ость,
изучение языка, адаптивное обучение, ин ст рументы ИИ
Intr oducon
In the cont ext of moder n glo balization, for eign language proficiency has become one of
the key competencies that enhance an individual’s professional capaci ty and enable effective
international communication. In par ticu lar, English language mast ery is dir ectly ass oci ated wit h
learners’ a cademic and professional development. The p rimary goal of for eign language teachin g
Proceedings of the 11th International Scient ific Conference
120
is to ensure that learners ca n use the language freely in real -life situations, that is, to develop
communicati ve c ompetence. This competence is not limited to mastery of gr ammar and
vocabulary; it r equires the integr ated dev elopment of listening, spea kin g, reading, and writing
skills. Ther efore, identifying effective ap proaches to for eign language t eaching remains a h ighly
relevant issue in co ntemporary educati on.
The digital revolut ion of the 21st ce ntury has in troduced new opportunities in the field of
education. Among the most r apidly developing and widely adopted innovations is artifici al
intelligence (AI). As a universal technology, AI has penetrated numerous spheres of human acti vity,
and in education it is increasingly perceived not only as an auxiliary tool but also as a means of
personalized lear ning. Technologies such as Machine Learning, Natural Language P rocessing, a nd
Speech Recognition hav e helped ov ercome many tr aditional ch allenges in lan guage teaching and
have reshaped instruct ional formats. Today, pl atforms such as ChatGPT, Gr ammarly, Du olingo,
and ELSA Speak are widely used to enhan ce lear ners’ speaking, wr iting, list ening, and
comprehension skil ls.
The relevance of this top ic lies in the significant potential of ar tif icial intelligence to develop
communicati ve competence. Modern learners are no longer passive recipients of inf ormation;
they ar e active agents who construct in dividual learning pathways and engage meaningfully in
communicati ve environments. AI suppor ts these needs by creating per sonalized learnin g
trajector ies, analyzing er rors rapidly , providing imme di ate fe edback, and simulati ng authentic
communicati ve c ontexts. Thus, AI incr ea se s the effectiveness of foreign language acqu isition and
makes the learning pr ocess mor e interactive and engaging.
The sc ientific significa nce of the study lies in the systematic examination of th e role of
artifici al intelligence in imp r oving co mmunicative competence and iden ti fying methodological
approaches to its pedagogical use. Whil e AI has typically been viewed as a n auxiliar y linguistic tool,
this r esearch aims to r eveal its practi cal impact and su bstant iate its methodological potential
within education al contexts.
The pur pose of the stu dy is to analyz e the impact of artific ial intelligence on th e
development of co mmunicati ve competence among foreign language le arner s and to identify
effective str ategies for its integration i nto the learning pr ocess.
To achieve this pur pose, the following objectives wer e defined:
– to analyze th e theoretical foundations of communicative competence;
– to descr ibe the potential of art ificial intelligence technologies in foreign language teaching;
– to examine methods of developing language skills t hrough AI tools;
– to evaluate the eff ectiveness of AI based on empir ical data;
– to develop pedagogica l recommendations based on the findin gs.
The object of the r esearch is the process of f oreign language teaching.
The subject of the research is the influence of artificial intelligence on the d evelopment of
communicati ve competence.
The r esearch hypothesis st ates th at if artificial intelligence techno logies ar e applied
syst ematically and methodol ogically, learners ’ communicative competence will develop more
effectively and r apidly than thr ough traditional methods.
A r eview of previous r esearch sh ows that i nternational sch olars [1], [3], [2] de monstrate
that AI te chnologies enhance language skills and support teachers’ instructional processes. Speech
recognition systems i n pa rticul ar have shown high effectiveness in improving speaking skills.
Kazakhstani r esearchers [8 ], [9] also conf irm the p edagogical v alue of digital tools in language
teaching; however, studies f ocused specifically on AI’s di rect impact on co mmunicicative
competence remain limited. Therefore, this s tudy is both scientificall y and practically valuable.
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
121
Theorecal Foundaons
Communicati ve co mpetence is widely explored in lingu istic and pedagogical literatu re as
one of th e co re outco mes of for eign language education. The theor etical basi s of this concept
originates in Hymes’ work and was lat er expanded by Canale and Swain. According to these
schola rs, ma sterin g a language i s not limited to knowledge of gramma r but r equires th e a bility to
use linguistic norms appro priately in r eal co mmunication. Co mmuni ca tive competence consist s of
linguistic, sociolinguis tic, discourse, strategic, and pragmatic components. The CEFR framework is
also based on th is model and emphasizes interconnected development of language sk ills.
Foreign researchers such as Har mer [11], Br own [1 2], Littlewood [13] argue that the
primar y aim of th e communicative approach is to activate the social and funct ional natur e of
language and prepare lea rner s for r eal communicative s ituations. The literature r epeatedly states
that co mmunicative competence develops not through mechanical drills but thr ough authe ntic or
semi-authentic language environments. This idea aligns naturally with the potential of AI
technologies, as AI can simulate real co mmunicative contexts a ccessible to all learners.
Perspectives on integr ating AI into education var y. Some sc holar s [1], [3] co nsider AI a
transfo rmative stage in language teachi ng. They claim that AI tech nologi es offer pers onalized
learning paths, diagnose err ors insta ntly, and create inter active linguisti c envir onments. According
to th is vi ew, AI is not only an auxiliar y tool but also a factor r eshaping pedagogical framew orks.
Other research ers [14], [ 1 5] h ighlight limitations, arguing that AI cannot fully r eplace human
emotional co mmunication or deep understanding of cu ltural context. Thus, they recommend
using AI as an additional tool. The mos t widely supported approach today is the hybrid model ,
where AI enhances instr uctional quality whi le the t eacher ret ains the rol e o f facilitator, g ui de, and
cultur al mediator.
The effectiveness o f artificial intelligence in language education is explained by se vera l
theoretical fr ameworks.
– Adaptive le ar ning theory: AI algor ithms create personalized le arning tracks based on individual
pace, err ors, and vocabulary level. [ 3]
– Constructiv ism: L earners co nstruct knowledge through acti ve engagement. AI tools like
ChatGPT, Du olingo, and Grammarly stimulate act ive product ion of linguistic content. [10]
– Communicati ve approach: AI to ols create environments that closely resemble r eal
communicati on. [1].
– Digita l pedagogy : AI i s conceptualized as a natur al element of mod ern educati onal ecosystems,
supporting flexi ble, acc essible, and inter active learning. [14], [15].
The literatur e demonstrates that AI technologies enhance all components of
communicati ve competence:
– Speaking: sp ee ch-r ecognition systems i mprove phonetics and intonation;
– Wr iting: NLP algorithms identify and explain errors;
– List ening/Reading: adaptive tasks ad just difficulty based on p erformance;
– Pr agmatics/Sociolinguistics: gener ative AI simulates c ulturally diverse dialogues.
Thus, A I r epresents a universal tool supporting ever y component of communica tive
competence.
Methodology
The methodological fr amework was designed to comp rehensively evaluate the impact of
AI tools on the development of communicative competence among for eign l anguage learners. It
includes th eoretical analy sis, empirical data collection, experimental procedur es, a nd qualitative
and quant itative analysis.
Proceedings of the 11th International Scient ific Conference
128
[5] Swain , M . (19 85) . Co mmunica tive co mpetence: Som e roles of comprehen sible input and
output in its d evelopment. In S. Gass & C. Madden (Eds.) , Input i n Second Language Acquisition
(pp. 235–253). Academic Press.
[6] Krashen, S. (1985). The Input Hypothesis: Issues a nd Implications . Longman.
[7] Xu, R. (2023). Ar tifici al Intelligence and adap tive lear ning in EFL speak ing education.
Comput ers in Human Behavior, 13 9 , 107585.
[8] Wu, Y., & Xu, C. (2022). E xploring the use of chatbots for speaking skill development.
Comput er Assisted Language Learni ng, 35 (7), 1253–1270.
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
129
D E V E L O P I N G F U N C T I O N A L L I T E R A C Y I N
P R I M A R Y S C H O O L S T U D EN T S
Anua rb ek Akmaral Yerk azyk yzy
First -year mast er's stud ent
Nabid ulli n S. Aib olat
PhD, Senio r Lectur er
Abai Kaz akh National Pe dagogical Univ ers it y (Almaty , Kazak hstan)
This ar ticle explores str ategies and pedagogical appr oaches fo r developing fu nctional
literacy in primar y school stu dents. Functional literacy encompasse s the ability to r ead, write,
communicate, and apply knowledge in real-life con texts, making it a crucial foundation for a ch ild’s
academic and so cial developmen t. The study aims to identify effecti ve methods fo r enhancing
funct ional liter acy and analyze inst r uctional pra ctices through the oretical review and qualitative
methodological analysis. Res ul ts highlight the importance of active learning, pr oblem-solving
tasks, multimo da l resources, and in tegrat ed liter acy instr uction acr oss subjects. The findings
demonstrate tha t functional liter acy develops mo st effectively wh en t raditional teaching is
combined with interactive, learner-ce ntered techn iques. The research under scores th e
significa nce of fun ctional literacy for preparing young learners to participate meaningfully in
modern societ y.
Keywords functio nal literacy, pr imary education, reading sk ills, problem-s olving,
communicati on, pedagogy
ФОРМИ РОВАНИЕ ФУНКЦИОН АЛЬНОЙ ГРАМОТНОСТИ У УЧАЩИ ХСЯ НАЧАЛЬНОЙ ШКОЛЫ
В ст атье рассматрив аются стратегии и педагогическ ие подхо ды к развитию
функциональн ой грамотности учащихся начальных кл ассов. Функциональная грамотность
включа е т умение читать, писать, понимать информацию и применять зн ания в жизненных
ситуациях. Цель ис следования — определить эффективные методы развития
функциональн ой грамотности и провести теоретический и ме тодологический анализ
образовательных практик. Результаты показывают, что активное обучение, проблем ные
задания, му льтимодальные ресурсы и межпредметная интеграция играют ключевую роль .
Наиболее высоких результатов удается достичь при сочетании традиционного обучен ия с
интерактивным и и ориентированными на учащегося ме тодами. Функциона льная
грамотность является важным условием подгото вки мл адших школьников к успешному
участ ию в современном обществе.
Ключевые с лова: функциональная грамо тность, начальное обр азование, навыки
чтения, решение проблем, коммуникация, педагогика
Introduction
Funct ional liter acy has become one of the primar y goals of contemporar y education syst ems
worldwide [1]. It refers not only to the ability to read and wr ite but also to the capacity to appl y
acquired knowledge and skills in real-life si tuations. In the context of primary scho ol, fun ctional
literacy for ms the basi s for lifelong learning and supports children’s intellectual, social, and
emotional dev elopment [2]. As societies become increasingly knowledge-based and
technologically ad vanced, the demand for individuals who ca n think critica lly, solve problem s
creatively, and co mmunicate effectively contin ues to gr ow. Therefore, the development of
Proceedings of the 11th International Scient ific Conference
130
funct ional literacy is recognized as a key priority in preparing young learners for successf ul
partici pation in modern society.
In primar y education , functional literacy encompasses several interconnected co mponents:
reading comprehension, wr iting competence, oral communicati on, numeracy, and the ability to
utilize infor mation from v arious so urces. These skills enable students not only to under stand
academic co ntent but a lso to navig ate ev eryday tasks such as following instructions, inter preting
signs, expressi ng their needs, and engaging in collaborative activities. Thus, f unctional liter acy
extends far beyond traditional literacy, forming a holistic framework for de veloping essential life
competencies.
Recent educati onal reforms in many c ountr ies emphasize t he s hift from r ote memorization
to meaningful learning experiences that promote ind ependence and act ive engagement. Within
this paradigm, teacher s a re enco uraged to adopt learner-centered approaches, integr ate real-life
contexts into lessons, and create opportunities for students to apply thei r knowledge in authentic
situatio ns. Such practices help bridge th e gap between th eoretical unders tanding and practical
use, ensur ing that literacy skills a re relevant and transf erable.
Additionally, res earch high lights that functional literacy development in p rimar y school is
influenced by several factors, including teaching methodologies, classroom environment,
availability of learnin g materials, and the extent of par ental involvement [4]. Eff ective str ategies
such as collaborati ve learning, problem-based tasks, multi modal r esource s, and cr oss-curricular
instructi on ha ve been fo und to significantl y enhance st udents’ functional literacy abilities. These
approaches fo ster curiosity, mo tivation, an d ac tive partici pation, which are essential
char acteristics of young learners.
Given the importance of functi onal literacy for aca demic success and personal growth,
exploring effecti ve ways to cultivate these skills has become a cr ucial area of stud y. This r esearch
seeks to identify pedagogical methods that support the devel opme nt of f unctional literacy and to
analyze how instructi onal pr actices can be optimized in the primary school setting [3] . By
examining theoretical fou ndations and r eviewing practi cal teaching appr oaches, the st udy aims to
contr ibute to a deeper understanding of how fu nctional literacy can b e successfully integrated
into modern educatio nal processes.
The M ain Part
Definiti on and Importan ce of Functional Literacy
Funct ional literacy is not just the ability to r ead and write but also the capacity to apply
acquired knowledge and ski lls in real-life situations. In the context of primary educat ion, functi onal
literacy for ms the foundation f or lifelong learning and supp orts c hil dren’s intellectual, so cial, and
emotional development. As soci eties become more know ledge-based and technologica lly
advanced, the demand f or individuals wh o can think cr itica lly, solve problems cr eatively, and
communicate effectively continues to g r ow. Therefore, developing funct ional literacy has become
a key prior ity in preparing yo ung learners for acti ve participation in modern society.
In primar y education , functional literacy encompasses several interconnected co mponents:
reading compr ehension, wr iting skills, oral co mmunication, numeracy, and the ability to utilize
information from various so urces. Th ese skills enable students not on ly to understand academic
content bu t also to navigate everyday tasks su ch as foll owing instr uctions, inter preting si gns,
expressing needs, and e ngaging in co llaborative acti vities. Functional literacy, therefore, go es
beyond tr adit ional liter acy an d is a comprehensive fr amework f or devel opin g essential life
competencies.
Recent educati onal reforms in many c ountr ies emphasize t he s hift from r ote memorization
to meaningful learning experiences that promote independence and active engagement. In this
paradigm, teachers are encour aged t o adopt learner-ce ntered approaches, integrate re al-life
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
131
contexts into lessons, and create opportunities for students to apply thei r knowledge in authentic
situatio ns. Such practices bridge the gap between theo retical und erstanding and practical
application, e nsuring t hat literacy skills ar e relev ant and transferable.
Strategi es for Developin g Func tional Literac y
There are several effective strategies for developing functional literacy in pr imary sch ool
students, whi ch va ry depending on the students' age, development, and context. However, the
following appro aches are widely r ecognized as effective:
Interac tive and Ex periential Learning Methods
In contemp orary education, teaching methods cannot rely solely on one-way information
delivery from the teacher. Active learn ing, problem-solving tasks, group work, and crea tive
assignments provide opportunities for stud ents to engage with the material and practice
funct ional lite racy. Interactive teach ing methods help st udents apply theoretical kn owledge to
real-wor ld context s, improving their critica l thinking and creative pr ob lem-s olving ski lls. For
example, presenting students with p ro blem-based learning tasks and having them solve problems
as a group enhanc es their analytical and collaborative skills.
Use of Multimodal Resour ces
Modern education increasingly utilizes multimedia resources to enrich students' learning
experiences. Tools like videos, imag es, animations, in teractive ma ps, and o nline platforms p rov ide
multiple ways f or st udents to absorb and process information. These resources play a cruci al role
in developing funct ional literacy by enab ling students to engage with c ontent in diffe rent formats.
For instance, pr esenting learning materials through text, video, and audio h elps students deepen
their under standing of a subj ect and improves r et ention.
Cros s-Curricular Teaching
Cross- curricular teaching is an important str ategy for developing fu nctional liter acy, as it
allows s tudents to apply knowledge from one s ubject to another, makin g learning more relevant
and meaningful. For example, integr ating math and literatur e can enable st udents to extr act
numerical data from literary texts, analyze it, and pr esent it in graphs or ch arts. This appr oach
helps students develop a mo r e holistic understanding of content and pr omotes the transf erability
of func tional literacy s kill s across different area s.
Lear ner-Centered Teaching Appr oach
A learner-centered teaching approach focuses on addressing the indi vidual needs and
interests of students, ensur ing that each student is acti vely eng aged in th e learni ng pr ocess. By
tailoring lessons to students' interests, t eachers can enh ance motivati on, fo ster indep endence,
and encour age active partici pation. Allowing st udents to explore topics they ar e pa ssionate ab out,
conduct independent r esearch, and participat e in hands-on lear ning activiti es empowers them to
develop their funct ional liter acy skills. In this approach, the teacher 's role is to guid e and support
students, helpi ng them discover and develop their a bilities.
Factors Influencing the Development of Funct ional Literacy
The development of funct ional literacy is influen ced by several i nternal and external factor s.
These factor s include:
Teacher Profess ional Development
Teachers' pr ofessional competenci es are crucial to the successful development of functi onal
literacy in students [6]. Teachers who ar e well-prepared, not only in their subject areas but also in
innovative teachin g methods and the use of modern techno logies, ca n more effectively foster
funct ional literacy. For insta nce, teacher s who implement differen tiated instruction, wher e
teaching methods are ta ilored to students' var ying abiliti es and lear ning styles, are b etter a ble to
support the developmen t of literacy s kills.
Proceedings of the 11th International Scient ific Conference
132
Parental Invo lvement
Parental involvement in the educational pro cess is a key fa ctor influ encing funct ional liter acy
development. When parents take an active r ole in their childr en's lear ning, it strengthens their
motivation a nd academic achievement. Parents who engage with their childr en’s homework,
discus s les sons at home, and encourage reading or other educa tional activities can positively
influence their chi ldren’s literacy development. A supportive home envir onment co ntributes
significa ntly to a ch ild's overall success in sch ool [7].
Availability of Learning Materials
Access to a variety of learning resources and materials is essential for develo pi ng functional
literacy. Schools th at provide a wide range of high-q uality resources, such as textbooks, online
platforms, and librar ies, create an environment where st udents c an explore and deepen th eir
understanding. Additionally, having access to digital tools and multime dia r esources furt her
enhances the learning experience, allowing students to engage with content in dynamic and
interactive ways .
Discu ssion
Interpr etation of Fin dings
The findings align with global research emphasizing student-centered, interactive teaching
methods for developing fun ctional literacy. Active task s and conte xtual learning appear
particu larly effective [5].
Comparis on with Previous Research
Studies by OECD and educational ps ychologists similarly no te that early development of
funct ional literacy pre dicts academic success and future adaptability .
Limitati ons
Limited sample size in cl assroom obser vations.
Some schools la ck resources for multimodal or digital tools.
Teacher prepar edness varies across r egions.
Suggest ions for Futu re Research
Longitudinal s tudies on functional liter acy progress from Grades 1–4.
Research on digit al literacy t ools in primary education.
Development of national asse ssment instr uments for functional liter acy.
Conclus ion
This research demonstrates that functional literacy develop ment in primar y school requires
a balanced co mbination of active learning, real-life tasks, and mul timodal instructional r esources.
When teachers integrate these approaches systematically, students develop st rong reading ,
writing, communica ti on, and problem-solving skills. The study unde rscores the sc ientific a nd
practi cal importance of f unctional literacy as the foundation for fu ture academic and social
succ ess. Developing funct ional literacy is not only an educational goal but an essential
requir ement for preparing young lear ners to navigate the complexities of modern soci ety.
Further more, t he developmen t of functional literacy is increasingl y relevant in today’s digi tal
age, where access to information and the ability to cri tically evaluate and apply knowledge are
crucial. As the world becomes mor e interconnected throu gh technolog y, students must be
equipped wit h the ability t o process information from diverse so urces, en gage in o nline
communicati on, and solve problems using digi tal tools. This extends beyond tradi tional reading
and writin g to encompas s digital liter acy, which i s essential for participating meaningfully in the
modern wor kforce and society. Thus, an effective functional liter acy pr ogram must include the
integration of techno logy, en s ur ing that students not only master b asic skills but also adapt to the
evolving demands of the digital world.
In additio n, fostering functional literacy requires a collabor ative effor t from teachers,
parents, and the community. Teachers play a central role in cr eating an engaging and su pportive
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
133
learning environment, while parental involvement and community support provide the nece ssary
foundation for students to thrive outside the classroom. By aligning the goals of formal education
with those of families and co mmunities, we can create a more holist ic appr oach to literacy
development that supp or ts students' growth both academically and socially. Ul timately,
developing funct ional literacy is a shared r esponsibility, and by p riori tizing these efforts, we can
equip future gener ations with t he skills needed to succ eed in an ever-changing wor ld.
References
1. OECD (2 013). The PISA 20 12 Assessment: Students and Mon ey: Financial Liter acy Skil ls
for the 21st Century.
2. Beers, S. (200 3). 21st C entury Skills: Rethinking How Students Learn.
3. Gibbons, P. (20 02 ). Scaffolding Langua ge, Scaff olding Learni ng: Teaching ESL Students
in the Mai nstream Classroom.
4. Shulman, L. S. (1987). Knowledge and Teaching: Foundations of the New Reform.
5. Vygotsky, L. S . (1978). Mind in Society: The Development of Higher Psychological
Proces ses.
6. Shulman, L. S. (1987). Knowledge and Teaching: Foundations of the New Reform.
7. Barto n, D., & Hamilton, M. (1998 ). Local Liter acies: Reading an d Wri t ing in One
Community.
Proceedings of the 11th International Scient ific Conference
134
T H E U S E O F A R T I F I C I A L I N T EL LI G E N C E
A N D D I G I T A L T O O L S T O S U P P O R T
M U L T I L I N G U A L P R I M A R Y E D U C A T I O N I N
K A Z A K H S T A N
Elmi ra Iz teleuov a
First -year mast er's stud ent
Nabid ulli n S. Aib olat
PhD, Senio r Lectur er
Abai Kaz akh National Pe dagogical Univ ers it y
(Almaty , Kazak hstan)
The s tudy examines effe ctive methods for developing stu dents’ lexico-grammatical s ki lls in
the context of multiling ual education. The arti cle analyzes methodol ogical approaches aimed a t
enhancing sp eech skills within the process of langu age teachin g. In addition, an exper imental
assessment is conduct ed to dete rmine the effectiveness of the pr oposed techno logies, and its
results are descr ibed from a pr actical perspective. The research find ings are comp lemented by
scientifi c and methodologica l concl usions that co ntribute to impr oving the quali ty of educatio n in
a multilingual e nvironment.
Keywords : multilingual educ ation, lexico-g rammatical aspects, langua ge teaching, sp eech
skills, e xperimental testing
ИСПОЛЬЗОВАНИЕ ИСКУССТВЕННОГО ИН ТЕЛЛЕКТА И ЦИ ФРОВЫХ ИНСТРУМ ЕНТОВ ДЛЯ
ПОДДЕРЖКИ М НОГОЯЗЫЧН ОГО НАЧАЛЬНОГО ОБР АЗОВАНИЯ В КАЗАХСТАНЕ
Исс ледование рассм атривает эффективные способы формирования лексико-
грамматических навыков учащихся в услов иях многоязычного образования. В ст атье
анализируютс я методические подходы, направленные на развити е речевых навыков в
процессе об у чения языкам. Кроме того, пр оводитс я эк спериментальная провер ка для
определения эффекти вности предло женных технологий, и её результаты описываются в
практическом аспекте. Полученные да нные до полняются научно-методическими
выводами, к оторые способствуют повышению качеств а обучения в многоязычной среде.
Ключевые слова: многоязычное об раз ование, лексико-грамматические аспекты,
обучение языку, речевы е навыки, экспериментальное тести рование
Introduction
Kazakhstan has made multilingualism a cornerstone of its education modernization. In the
past deca de the government has pr omoted a “Trinity of Languages” poli cy so that by 2020 all
citizens would speak Kazakh, most would also speak Russian, and many wo ul d learn English[1][2].
By 2019 over 30 schools in Kazakhst an were already offering instr uction in three langua ges, with
plans to expand multilingual p rogra ms to hundreds more[2]. At the sa me time, Kazakhstan is
rapidly adopting dig ital tools: UNESCO notes th at “educational in stitutions acr oss the region are
rap idly adopting digital too ls a nd onl ine l earning,” and governments ar e a cc el er ating effor ts to
integrate AI into education[3]. In response, cl assr ooms – even at the pr imary level – are
increasingly equipped with computers and internet connectivit y. For example, a government
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
135
initiative in 2020 planned to distribute 500,000 home comp uters to disadvantaged students for
remote learning[4 ], r eflecting an early push to digitize educa tion (see image). Over 60% of schools
already had high-speed internet by 20 20[5], a foundation for later AI -enabled programs. These
developments set the stage for exploring how AI- powered te chnologies (machi ne tr anslati on ,
adaptive systems, c hatbots, apps, etc.) can supp ort Kazakhsta n’s multilingual primar y education,
and wha t challenges of equity and cur riculum design ari se when integrating such tools.
Kazakh primary school stude nts usi ng comput ers in cl ass (UNICEF photo ). Kazakhstan h as
invested in classroom connectivity and stud ent devices; for instance, in 2020 the government
equipped 50 0,000 stu dents with co mputers for distance learning[4]. This digi tal infrastr ucture
underpins curr ent efforts to i ntroduce AI and other t echnologies into education.
This article reviews the literatur e o n AI and digital tools for language learning, analy zes how
such technologies ca n support mult ilingual education (e specially in the Kazakh, Russ ian, and
English context of Kazakh schools) , and compar es Kazakhstan’s exper ience with other multilingual
settings. We focus on AI-driven solutions (translation engines, adaptive learning platforms,
conversational agents, etc. ) and digital lan gu age apps, assessing th eir ped agog ical roles and
equity implications. We also present relevant case studies, s uch as Kaza khs tan’s Soyle translation
app and AI-powered chatbots for Kazakh–English learning, al ongsi de analogous in itiatives in
countr ies like Kyrgyzstan and India. In doing s o, we highlight both opportun ities (personalization,
accessi bility, new content) and challenges (low-resource languages, digit al divides, teacher
training) in design ing a curr iculum that fu lly leverag es AI w hile ensur ing fair access for all lear ners.
Methodology
This study is a qualitative review and anal ysis of exist ing r esearch, policy docu ments, and
news repor ts rela ted to AI and multilingu al education in Kazakhstan and compar able contexts.
We conduct ed structured se arches for academic and official so urces on AI in language l earning
(e.g., adap tive learning, MT, chatbots, educat ion al a pps) and on Kazakhstan’ s language policies
and education technology initiatives. Peer-reviewed studies on AI tools in language education
were examined to identify key findings and best pract ices. Government and NGO r eports (e.g.,
UNESCO, UN ICEF) provid ed context on Kazakhst an’s nat ional strategies and pilot projects. Case
examples were se le cted based on rel e vance to primary education and multilingua l settings .
Comparative insights were drawn from cases in other post-Sov iet and multilingual nations (e.g.,
Kyrgyzstan’s Kyrgyz lang uage AI model, India’s national tr ansl ation platform). Our goal is a
comprehensive sy nthesis rather than empirica l data col lection, so no new da ta analysis was
perfor me d beyond literature review.
Literatur e Review
AI and Languag e Learning Tools: Modern AI to ols can aid lan guage inst ruction in several
ways. Mach ine tr anslation (M T) engines now often use neural network s t o provide r eal-time
translation of text and speech. Adaptive learning s ystems ta ilor content to individual student
needs using algorit hms that adjust difficulty based on per formance. Conversational agents or
chatbots ca n simulate i nteractive dialogue p rac tice in a tar get lang uage. Languag e-learning apps
(such as Duolingo or Ling) incorp orate gami fication and sp aced repetition, often powered by A I
(voice recognition fo r pronunciation, personalization of exercises). Emerging techno logies like
speech recognition ca n give immediate feedback on pronunci ation, and ev en a ugmented/virtual
reality (VR) s cenarios ca n immerse learners in a new-language environment.
Key categories of A I/digital tools used in language education include:
Mach ine Trans lation & NLP Tools: Platforms that automatically trans late text or spe ech
between languages. Rece nt advances with large la nguage models (LLMs) an d bilingual evaluation
metrics mean MT can now produce surpr isingly accu rate output for many language pairs. F or
instance, Kazakhs tan’s new Soy le App uses a n AI-based model trained on Kazakh and other
languages to translate automatically[6] .
Proceedings of the 11th International Scient ific Conference
136
Adaptiv e L earning Systems: Intel ligent tutor ing systems or platforms (often web or app-
based) that adjust lesson content and pacing to each learner’ s level, offer ing personalized pr act ice
and feedback. Stud ies show adaptive systems can help tailor instruction to diverse le arners’
needs[7].
Convers ational Agents / C hatbots: AI-driven chatbots th at converse with students i n th e
target language. Research f inds chat bots ca n reduce l anguage lear ners’ anxiety, impr ove speak ing
practi ce, and boos t confi dence [8]. For example, a r eview of AI chatbots for E nglish learning noted
learners experienced less spea king anxi ety and gr eater engagement when p r acti cing with bo ts[8].
Languag e Learning Apps: Mobile or web apps (e.g . , Duolingo, Mango, Ling) that ga mify
vocabulary and grammar practice, often em ploying AI to personalize lesso n s. Duolingo itself uses
AI (incl uding GPT-4 ) to create features like “Ex plain My Answer” and simulated conver sation
practi ce[9][10]. Such app s ca n su pplement clas sroom instr uction wit h interactive exercises and
immediate feedback.
Speech an d Pr onunciation Tools: Applicat ions that use speech-to-text to ch eck
pronunci ation, or text-to-speech for listening practice. For instance, tools like Goog le’s sp eech
recognizer (used in edu cational apps like ELSA or SpeechAce) can provide formative feedback on
a learner’ s accent.
Educational Content Creation: Generative AI (e.g., ChatGPT, Ba rd) can hel p teachers
produce language learning ma terials (e.g., vocabular y lists, grammar exercise s, example
sentences) o r generate simpler versions of t exts for learners. However, ensuring content accuracy
and appropr iateness remains a co ncern.
These categori es overlap – for exa mple, an app might inco rp orate ma chine trans lation,
chatbots, an d adaptive algo rithms. In general, AI can expedite content creation (e.g., auto-
generating stor ies or quiz zes), adapt resources to learners’ levels, and simulate realisti c language
use. A sys tematic review found that AI conv ersational agents and writing assist ants can provide
“feedb ack in real ti me” and support learners b y giving pronunci ation help and lowering
anxiety[11] . However , the same r eview warned that many of these advances favor widely sp oken
languages: “Low -resource langua ges like Kaza kh ar e underr epresented” in AI dat asets, an d
disparities in infrastr ucture (as in parts of Eastern Europe or Centr al Asia) can limit access to
mobile/gamified learning [12][13 ].
Multilingual Ed ucation and AI : M ultilingual education ( MLE) means using mor e th an one
language o f instruction or pr oviding instruction in students’ fir st languages. In Kazakhstan, sc hools
often teach in Kazakh and/or Russia n, with English introduced early. Researc h on MLE emphasizes
that suppor ting lea r ners’ home la nguages improves comprehension and learning outco mes. For
example, UNESCO highlights that lear ners whose f irst language matches school instr uction have
higher literacy r ates[14]. A I tools can potentially r einforce ML E by automating tra nslation or
offering content in multiple languages. For instance, MT ca n deliver textbook excerpts or digital
content in a student’s nat ive language . H owe ver, experts ca ution tha t AI alone won’t r esolve MLE
challenges – thoughtful integration and te acher facilitation r emain essential [15].
Several studies have begun examining best practices for AI in mult ilingual co ntexts. An
Edutopia ca se study noted that AI tools (l ike Per plexity.ai or MagicS chool.ai) can generate
simplified texts a nd mentor examples, which multilingual st udents then st udy in their home
language to deepen under standing (e.g . tr anslating AI-generated En glish co ntent into a native
tongue)[16 ][17]. Tools lik e these cou ld be adapted for Kazakh-Russian-E nglish tr ilingual
education. An industry blog recommends th at teachers use multilingual video capti oning and AI-
driven translation to improve comprehension and equity, while still guidin g students to criti cally
evaluate AI content[18] .
Benefits and Limitations: In general, AI offers personalized learning at scale. Chatbo ts a nd
adaptive systems have been sh own t o enhance motivation, engagement, and langu age skills in
«Research Retr ieval and Academic Letters» (December 1 1-12, 202 5). Warsaw, Pol and
137
contr olled studies[8]. Language apps l ike D uolingo effectively use AI to ta ilor drills to individual
progre ss, and the latest GP T-4–powered featur es pr ovide near-re a listic conversation
practi ce[9][10]. Machine tr anslation to ols, while imperfect for low-resource langu ages, are
steadily improv ing. Kazakhstan’s Soyle App, for example, now sur passes Goo gle and Yandex on
Kazakh translation quality[19].
However, research undersco res risk s: low -r e sour ce languages lag behind in AI
development[12], and reliance on dat a-hungry models can exacer bate inequities. For insta nce,
AI-driven mobile l earning may widen rural-u rban gaps if connecti vity is uneven[13]. Additionally,
algorithms ca n contain cultur al bias es, and ch ildren’s data privacy must be safeguard ed (UNICEF
urges AI guidelines to pro tect child ren’s r ights)[ 20]. Tea ch ers thus must remain central: AI shoul d
augment, not replace, skilled instr uction[3][20 ].
Kazakhstan’s La nguage Education Land scape
Kazakhstan’s multilingual educ ation system is in trans ition. After independence in 1991,
Kazakh became the state lang uage, but Russian r ema ined dominant in ma ny schools and cities. In
the 2010s the government launche d a bold “Trinity of L anguages” ca mpaign: all students sh ould
learn Kazakh and English in addition to Russian[1]. By 2020, offici al targets envisioned 100% of
Kazakhs speaking Kazakh and 95% speaking Russian, with 25% also fluent in English[1]. Schools
like the el ite Nazarba yev Intelle ct ual Schools implement tr ilingual instr u ction (e.g. science in
English, math in Kazakh) to pr epare stu dents for global integration. Over 201 9–202 0, Kazakhstan
planned to conv ert hundreds of ordin ary schools to trilin gual instru ction and to tr ain En glish-
teaching sp ecialists, signaling a systemic shi ft [ 2 ]. These r eforms co incide with broader
digitalization: the ministr y ha s moved textbooks o nline and plans to integrate AI into cur ricula by
202 6[21][22].
Technology Infrastr ucture: Cr ucially, Kazakhstan has invested heavily in edtech
infrastruct ure. By late 2025 nearly all schools (over 99%) h ave internet acce ss, and learning
management systems (LMS) have been adopted nationw ide[23] . For example, the “Day of AI”
initiative delivered tr ansl ated AI literacy lessons to every Kazakhstani sc hool. These steps a im to
ensure that when AI t ools (l ike intelligent tutors or t r anslation apps) are deploye d, they hav e the
connectivi ty to reach students. However , challenges persist : many r emote sch ools st ill rely on
basic 3G connections, and only about a thi rd of te ach ers report hav ing advanced digital skills[24].
Addressing this, the gove r nment and p artners (e.g., UN agencies, tech a ccelerators) are runnin g
teacher tr aining programs.
Curr ent AI/Digital Initi ativ es: Kazakhstan’s tech ecosystem now incl udes several language-
AI initiatives. N otable examples include:
Soyle App: Developed by the Institute of Smar t Systems and AI (ISSAI) at Nazarbayev
University, Soyle is a speech/text translator supporting Kaz a kh, Russian, English, a nd Turkish[6]. It
uses a loca l LLM (“Kazak h foundati onal s peech model”) and emphasizes on-device data secu rity.
In benchmar ks , Soyle outperf orms Google and Yandex on Kazakh t ext[19]. This tool can help
teachers qu ickly translate content or provide bilingual p rompts.
SoilesA I Chatbot: Qazaq AI (a non-profit s tartup) has launch ed a n English -language
learni ng chatbot fo r na tive Kazakh speakers[25 ]. This reflects a “bi-di rectional” approach t o tech
(not jus t teaching Kazakh, but also using Kazakh to learn other lang uages). Such ch atbots can let
Kazakh-speaking chi ldren pr actice English conv ers ation i n a sa fe environment.
Other Kazakh AI P latforms: Local co mpanies and research labs have created AI stacks for
Kazakh – for example, Tegeuri n AI offers tools like te xt-to-s peech (with K azakh pronunci ation) and
morphological analysis[26] , while ISSAI’ s offline suite ( Oylan, MangiS oz, TiSync) provides
translation, subti tles, and even cr ea tive imag e generati on in Kazakh[27 ]. Initiatives like BilimA I
and Ertegi AI focus on ed ucation (e. g. generating fairy tales in Kazakh[28]). These platforms are
relatively new and m ostl y experimental, b ut they demo ns t rate an ecosystem of supportive tools.
Proceedings of the 11th International Scient ific Conference
144
skills—l istening, sp eaking, readin g, and writing—wh ile also enhancing students’ creativity,
linguistic thinking, and c ommu ni cation co mpetence.
The aim o f this stud y is to theoretically demonstr ate effecti ve wa ys of using Ch atGPT to
develop language skills in pr imary school students.
The ob jectives in clude:
1. Descr ibing the potential of ChatGPT in language learning;
2. Analyzing methods for creating tasks f or children;
3. Presenting str ategies to incr ease students’ motiv ation;
4. Offering theoretical recommendations for integrating AI t ools into th e lea r ning
process.
The sub ject o f the s tudy is t he use of ChatGPT in the pr ocess of learning English by primary
school st udents. The o bject is the methods for dev eloping language ski lls in primar y sch ool
students. Th e hyp othes is is that integrating ChatGPT into the learning process positively
contr ibutes to the effective and engaging development of stu dents’ lang uage skills.
Main par t
The use of ChatGPT to develop languag e skills in pr imary sch ool st uden ts is an essential
component of modern ed ucational met hodolog y. Th is AI system all ows childr en to perform
language activi ties interact ively and provides tasks tailored to in dividual levels, personalizing the
learning process. ChatGPT is considered an effective tool for gradually developing listening ,
speaking, reading, and writing s kills. Thr ough AI, ch ildren acq uire new vocabulary and phrases,
practi ce dialogues, learn sentence struct ure, and develop text an alysis ski lls. Additionally, Cha tGPT
fosters cr eativity, logica l thinking, and l inguistic reasoning.
A key feature of using ChatGPT in primar y education is its ability to automatically pr ovide
individualized tasks a nd exerci ses.
Language Skill T ask T ype E xpected Out come
Liste n ing Audio ex ercises, dialogues Impr oved compr ehensio n
Speaking Sen tence cons trucon, role-pla y Fl uency and confidence
Re ad ing T ext analysis, Q&A Comprehen si on and a naly sis
W ring Essay s, leer s, ex ercises Grammar and expr essi on
For example, if a stu dent str u ggl es to co nstruct sen tences on a specifi c topic, the syst em
offers additiona l examples, qu estions, or dialogue options. This approach increases m otivation as
each stud ent ca n wor k at th eir own pace and level. Mor eover, Ch atGPT tra cks each student’s
progre ss and provides feedback to the teacher , enabling more effective planning of the learning
process. Teachers ca n use this information to a s sess student per formance, cr eate individualized
learning p aths, and organize group activiti es.
Another advantage of using ChatGPT is th e increased interactivity and engagemen t in
lessons. Ch ildren c an perfor m langu age a ctivities su ch as co nversation, text analysis, vocabular y
expansion, and applying grammar rules through game-based elements. This method encourages
active p artici pation and enhances interest in language le arning. ChatGPT also pro vides c r eative
tasks that dev elop students’ thinking sk ills, suc h as sto rytelling, writing let ter s, expressing
opinions, or co mposing short essays.
AI also improves t ime management and learning effici ency. Ch atGPT allows students to
repeat exercises or adjust di fficulty levels, which is particu larly use ful in lar ge cl asse s where
teachers c annot de vote individual attention to every student. M oreover, ChatGPT is accessi ble
[Document text truncated for crawler view.]