2025
NOVEMBER
NEW RENAISSANCE
INTERNATIONAL SCIENTIFIC AND PRACTICAL CONFERENCE
VOLUME 2 | ISSUE 11
289
ARTIFICIAL INTELLIGENCE (AI) AND ENGLISH LANGUAGE TEACHING:
AFFORDANCES AND CHALLENGES
Abdusama o a Shahnoza
Sama qand S a e Ins i u e o Fo eign Languages
Facul y o Fo eign Languages and Li e a u e
5 h cou se, G oup 2115
Isma o a Makhzuna Sha ka o na
Scien i ic supe iso .
h ps://doi.o g/10.5281/zenodo.17691764
Abs ac . A i icial In elligence (AI) is inc easingly ans o ming English language
eaching (ELT) by p o iding inno a i e ools o pe sonalized lea ning, au oma ed assessmen ,
and class oom managemen . This s udy explo es he a o dances o AI in ELT, including enhanced
lea ne au onomy, adap i e eedback, eal- ime pe o mance acking, and imp o ed eaching
e iciency. I also examines he challenges associa ed wi h AI in eg a ion, such as echnical
limi a ions, da a p i acy conce ns, eache eadiness, and e hical conside a ions. By syn hesizing
indings om cu en li e a u e, his pape p o ides a comp ehensi e analysis o AI applica ions
in ELT, highligh ing p ac ical implica ions o eache s and lea ne s [1; 19-p].
Keywo ds: A i icial In elligence, English Language Teaching, ELT, Adap i e Lea ning,
Language Educa ion, AI Tools, A o dances, Challenges, Technology in Educa ion.
In oduc ion
English language eaching has unde gone p o ound ans o ma ion due o echnological
ad ancemen s. AI, encompassing machine lea ning, na u al language p ocessing, and in elligen
u o ing sys ems, has become an inc easingly in luen ial componen in mode n language educa ion.
By p o iding adap i e eedback, pe sonalized con en , and au oma ed assessmen , AI ools
ha e he po en ial o e olu ionize bo h eaching and lea ning p ocesses [3; 50-p]. This pape
in es iga es he a o dances o AI in ELT, examining i s po en ial bene i s, challenges, and
implica ions o eache s and lea ne s. I also aims o p o ide insigh s in o e ec i e in eg a ion
s a egies ha maximize pedagogical ou comes.
Li e a u e Re iew
Recen s udies e eal ha AI applica ions in ELT a e di e se and apidly expanding.
In elligen u o ing sys ems o e pe sonalized lea ning pa hways, adap ing con en based
on s uden pe o mance and lea ning s yle [5; 104-p]. Cha bo s and i ual assis an s p o ide
lea ne s wi h au hen ic con e sa ional p ac ice ou side he class oom, enhancing luency and
communica ion con idence. AI-powe ed au oma ed w i ing e alua ion sys ems suppo g amma
and ocabula y de elopmen by p o iding ins an eedback. Speech ecogni ion and p onuncia ion
ools allow lea ne s o e ine o al skills, making language p ac ice mo e in e ac i e and engaging.
Despi e hese bene i s, esea che s highligh po en ial challenges, including o e - eliance
on echnology, algo i hmic bias, e hical dilemmas, and insu icien eache aining. The li e a u e
emphasizes he impo ance o eache media ion o ensu e educa ional quali y and add ess AI
sys em limi a ions. S udies also indica e ha combining AI ools wi h adi ional ins uc ional
me hods can op imize lea ning ou comes and main ain lea ne engagemen [1; 100-p].
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Me hodology
Pa icipan s: This s udy syn hesizes da a om mul iple ELT con ex s, including seconda y
schools, highe educa ion ins i u ions, and online language lea ning pla o ms. Pa icipan s
e e enced in he s udies include lea ne s aged 12–25 and language ins uc o s wi h a ying le els
o echnological p o iciency.
Quan i a i e Da a: Quan i a i e da a om p io s udies include p e- and pos -in e en ion
language es sco es, usage s a is ics om AI applica ions, equency o lea ne in e ac ions wi h
cha bo s and adap i e pla o ms, and imp o emen s in lea ne pe o mance me ics.
Quali a i e Da a: Quali a i e da a encompass obse a ions o class oom p ac ices,
in e iews wi h eache s and s uden s, and su eys on pe cep ions o AI ools in language lea ning.
These da a p o ide insigh s in o he pe cei ed e ec i eness, engagemen , and use
sa is ac ion associa ed wi h AI-assis ed ELT.
Da a Analysis: A comp ehensi e heo e ical and compa a i e analysis was conduc ed,
in eg a ing quan i a i e and quali a i e indings. Key hemes include he e ec i eness o AI in
enhancing pe sonalized lea ning, lea ne engagemen , eache e iciency, and challenges ela ed o
e hical implemen a ion and echnical in eg a ion.
Findings
AI in eg a ion in ELT o e s nume ous bene i s. Pe sonalized adap i e lea ning pla o ms
enable s uden s o p og ess a hei own pace, ocusing on a eas equi ing imp o emen . Cha bo s
and con e sa ional agen s acili a e con inuous language p ac ice, p o iding immedia e eedback
and e o co ec ion. Teache s epo ha AI sys ems educe adminis a i e asks, allowing mo e
ime o ins uc ional planning and s uden in e ac ion. Mo eo e , AI applica ions suppo
inclusi e educa ion by accommoda ing di e se lea ning needs and s yles.
Challenges emain, including he need o p o essional de elopmen o ensu e eache s can
e ec i ely use AI ools, e hical conce ns ega ding da a p i acy and bias, and he isk o educed
c i ical hinking i lea ne s ely solely on au oma ed sys ems. E ec i e in eg a ion equi es
balancing AI-d i en ins uc ion wi h eache -led guidance and adi ional class oom ac i i ies.
Discussion
AI can signi ican ly enhance pedagogical e ec i eness in ELT when implemen ed
hough ully. I acili a es pe sonalized ins uc ion, eal- ime eedback, and inc eased engagemen ,
allowing eache s o ailo ins uc ion o indi idual lea ne needs. Howe e , AI is no a
eplacemen o eache s; a he , i should unc ion as a complemen a y ool. S a egic
implemen a ion, ongoing aining, and e hical guidelines a e c i ical o ensu ing AI bene i s
lea ne s wi hou comp omising educa ional quali y. Fu u e s udies should ocus on long- e m
impac s, scalabili y o AI solu ions, and bes p ac ices o hyb id eaching models.
Conclusion
AI ep esen s a ans o ma i e app oach o English language eaching, o e ing inno a i e
ools ha enhance lea ning and eaching p ocesses. While i p esen s challenges such as echnical
cons ain s, e hical conside a ions, and he need o eache eadiness, i s po en ial bene i s a e
subs an ial. Success ul in eg a ion equi es ca e ul planning, p o essional de elopmen , and
alignmen wi h cu iculum goals. Con inued esea ch and p ac ical expe imen a ion will help
de elop bes p ac ices o AI-suppo ed ELT.
2025
NOVEMBER
NEW RENAISSANCE
INTERNATIONAL SCIENTIFIC AND PRACTICAL CONFERENCE
VOLUME 2 | ISSUE 11
291
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