In e na ional Jou nal o In o ma ion Sciences and Techniques (IJIST) Vol.15, No.1/2/3/4/5, Sep embe 2025
DOI : 10.5121/ijis .2025.15501 1
DEVELOPMENT OF AN INNOVATIVE
E-LEARNING SYSTEM
H is ina Dimo a Popo ska 1, Tome Dimo ski 1 and Filip Popo ski 2
1 Facul y o In o ma ion and Communica ion Technologies, Uni e si y, S . Klimen
Oh idski, Bi ola, Macedonia
2 Facul y o Technical Sciences, Uni e si y, S . Klimen Oh idski, Bi ola, Macedonia
ABSTRACT
The apid e olu ion o digi al echnologies is eshaping he landscape o educa ion, in oducing e-lea ning
as a p ominen and iable way o knowledge deli e y. Lea ning is also a challenge ha can be ela ed o
in o ma ion echnology and da a collec ion. Wi h he ad en o new echnologies comes he eme gence o
new ways o lea ning ha will ha e in e ac i e aining as a basis. These modes o lea ning a e called e-
lea ning and a e ime and place independen . I can be seen ha in ecen yea s, in he ield o educa ional
echnology and in he ield o a i icial in elligence, i is expec ed o p o ide educa ional se ices ha will
help s uden s. Wi h his in mind, he aim o his pape is o explo e e-lea ning sys ems and hei modules,
wha is inno a i e in hose sys ems and o gi e a sugges ion on wha needs o be upg aded in o de o ge
an inno a i e e-lea ning sys em. The pape i sel also explo es how AI u o s can be used in hose e-
lea ning sys ems.
KEYWORDS
e-lea ning, e-lea ning sys ems, inno a i e sys ems, AI u o s.
1. INTRODUCTION
Mode n e-lea ning sys ems ep esen a signi ican ad ancemen compa ed o con en ional
educa ional models, o e ing g ea e lexibili y, accessibili y, and con inuous lea ning wi hou
spa ial o empo al limi a ions. Unlike adi ional app oaches, e-lea ning p o ides a ich selec ion
o digi al esou ces and pe sonalized con en , enabling s uden s o lea n a hei own pace and
acco ding o hei indi idual needs [1].
One o he p ima y objec i es o e-lea ning is o help s uden s de elop ele an skills and deepe
unde s anding, he eby acili a ing mo e e ec i e achie emen o hei educa ional ou comes.
This aspec ep esen s a c ucial ad an age o mode n e-lea ning sys ems and should be
emphasized in bo h he in oduc ion and discussion, as i highligh s he ans o ma i e ole o
echnology in educa ion [2].
This s udy aims o iden i y he equi emen s and challenges o exis ing e-lea ning sys ems,
ocusing on ac o s ha in luence use in e ac ion wi h he pla o ms. Fu he mo e, i analyzes he
applica ion o a i icial in elligence as a ool o enhance hese sys ems, h ough he de elopmen
o inno a i e sys ems and in eg a ion o AI u o s, which aim o p o ide dynamic, adap i e, and
pe sonalized lea ning expe iences [3].
P e ious esea ch indica es ha he in eg a ion o a i icial in elligence can signi ican ly imp o e
con en accessibili y, mo e e ec i ely iden i y s uden s’ lea ning needs, and enhance he quali y
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o in e ac ion be ween s uden s and ins uc o s. In doing so, i lays he ounda ion o a new
gene a ion o educa ional pla o ms ha no only suppo he lea ning p ocess bu also ac i ely
con ibu e o he de elopmen o compe encies essen ial o con empo a y socie y [3].
2. E-LEARNING
Lea ning is he p ocess whe e in o ma ion is ob ained. Many people lea n om ins uc o s o
h ough he use o in o ma i e sou ces such as guides, menus, newspape s, e c. [4]. E-lea ning
can be said o be a ype o lea ning ha is pa o he In e ne ne wo k [5]. E-lea ning has been
de ined as compu e assis ed lea ning since he 1960s, bu i s adop ion and popula i y began wi h
he popula iza ion o he In e ne . Since i s in oduc ion, e-lea ning has apidly e ol ed in he
ield o echnology and he me hods i uses. E-lea ning is he p ac ice o using in o ma ion and
communica ion echnology o c ea e a lea ning expe ience ha can be o mal, o ganized, and
c ea ed wi h su icien eedom wi hou any bounda ies [6]. E-lea ning is a p ocess whe e a se o
lessons a e p o ided on digi al de ices such as compu e s, able s o any memo y de ices ha
suppo i . I is an in e ac i e lea ning expe ience in which con en is a ailable online and
p o ides eedback on he s uden 's lea ning ac i i ies [7]. One o he main goals o e-lea ning is
o de elop skills and unde s anding o help s uden s achie e hei lea ning goals [8].
3. E-LEARNING SYSTEMS
T adi ional e-lea ning sys ems a e i s appea ing on he Uni e si y Ne wo k and on he In e ne
o suppo and in es in schools and companies. Such sys ems con ain six pa s in hei
in elligence ne wo k in as uc u e, such as IP, applica ion usage and de elopmen , con en
c ea ion, con en managemen , lea ning managemen , deli e y, and de elopmen [9]. Also
a ailable a e he in eg a ion o da a, ideo and oice, mul icas echnology, secu i y, handling,
s o age, dis ibu ion o con en in in elligen in as uc u e acili ies.
Figu e 1. F amewo k o a adi ional e-lea ning sys em
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4. E-LEARNING SYSTEMS
E-lea ning sys ems based on a i icial in elligence (AI) echniques allow app op ia e con en o
he use o be de e mined acco ding o Le el 7 use unde s anding. De eloping an AI-based e-
lea ning sys em equi es a holis ic app oach and a ho ough analysis o da a and da a sou ces.
Such eques s should be a ailable in he da abases o he sys em i sel . Mu aza p oposes a model
o an e-lea ning sys em ha con ains a se o equi emen s and hen p esen s a holis ic amewo k
o e-lea ning. Thei se up amewo k is designed o be an example o an in elligen e-lea ning
sys em ha in eg a es componen s in o de o i s de e mine he use 's le el o lea ning and hen
p opose ma e ials [10].
As a subse o AI, machine lea ning (ML) is also eme ging as a powe ul ool in e-lea ning
sys ems. In such sys ems, MU is used as a con en ional app oach o moni o ing use
pe o mance. The e a e se e al MU echniques used o c ea e such sys ems. Such echniques a e
Bayesian Knowledge T acing (BCT), which uses a echnique called he Ma ko p ocess ha is
equipped o each skill so ha u u e pe o mance can be p edic ed based on he use 's esponse
his o y [11].
MU's algo i hms along wi h AI echniques enable he c ea ion o e-lea ning sys ems ha can
accu a ely p edic and display ma e ials o use s. Such applica ion o hese echnologies no only
in e-lea ning sys ems, bu also in o he sys ems is a majo inno a ion ha o e s an imp o ed use
expe ience in di e en usage ci cums ances.
5. LIMITATIONS OF E-LEARNING SYSTEMS
Despi e he conside able ad an ages o e ed by con empo a y e-lea ning sys ems, se e al
limi a ions hinde hei ull po en ial. T adi ional pla o ms o en p o ide a uni o m lea ning
expe ience ha does no adap o indi idual s uden s’ abili ies, lea ning s yles, and p e e ences.
Con en accessibili y can be inconsis en , making i di icul o loca e ele an ma e ials o
ecei e imely and ac ionable eedback. In e ac ion wi h ins uc o s is equen ly limi ed,
educing oppo uni ies o engagemen , guidance, and pe sonalized suppo . Mo eo e , exis ing
sys ems may inadequa ely moni o lea ne s’ p og ess o ail o p o ide insigh s ha help close
lea ning gaps.
The p oposed inno a i e sys em, enhanced wi h an AI u o , di ec ly add esses hese
sho comings. By deli e ing pe sonalized lea ning pa hways and adap ing con en in eal- ime
based on indi idual pe o mance, he sys em ensu es ha s uden s engage wi h ele an esou ces
a he igh momen . The AI u o acili a es con inuous in e ac ion, p o iding guidance,
moni o ing p og ess, and sugges ing a ge ed in e en ions o close lea ning gaps. This app oach
ans o ms he educa ional expe ience om a s a ic, one-size- i s-all model in o a dynamic,
adap i e, and lea ne -cen e ed en i onmen . Consequen ly, in eg a ing a i icial in elligence ools
wi hin e-lea ning sys ems no only mi iga es exis ing limi a ions bu also enhances he o e all
quali y and e ec i eness o online educa ion.
6. CURRENT RESEARCH IN THE FIELD
Acco ding o he esea ch and in e es o esea che s on his opic, we can see di e en ypes o
e-lea ning sys ems ha a e based on di e en echnologies.
Mu aza and o he s. In hei esea ch, hey c ea ed an e-lea ning amewo k based on 5 modules
whe e hey expec an answe o hei 4 esea ch ques ions ha a e ela ed o he key ac o s o e-
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lea ning and he bene i s o AI in he same. They se a se o equi emen s and challenges, and
hen p esen a holis ic amewo k o lea ning. The esul s hey ecei e mee hei equi emen
and expec a ion ha he p oposed amewo k answe s he esea ch ques ions ha we e asked a
he ou se [11].
Figu e 2. P oposed a chi ec u e [11]
Alexand a and o he s analyze he di e en echniques o applying ag based ecommenda ions o
e-lea ning sys ems. They use he anking me hod as he mos app op ia e model based on enso
ac o iza ion echniques o ob ain e icien esul s om he ecommenda ions. The au ho s
p esen an in elligen u o ing sys em used o p og amming and p esen i as a ecommenda ion
o lea ning esou ces. Thei esea ch ocuses on choosing a agging echnique ha can lead o
be e ecommenda ions. They c ea e an a chi ec u e o a sys em called P o us ha has i e
componen s. To analyze he esul s, hey use he algo i hms PageRank and FolkRank whe e hey
compa e he esul s and no e ha hei sys em has con ibu ed o e-lea ning [12].
Figu e 3. P o us sys em a chi ec u e [12]
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Mus a a and o he s ind he mos app op ia e lea ning pa h and con en o a gi en s uden ha
aligns wi h hei p o ile and lea ning achie emen . Thei pape sugges s se e al me hods wi h
a ying le els o pe o mance in e ms o accu acy and quali y o adap a ion. The au ho s di e
om o he s in ha hey combine a con en based il e ing echnique and a machine lea ning
algo i hm based on he s uden 's mo i a ion. They c ea e a sys em ha consis s o se e al
modules and es hem using ma hema ical o mulas. They used a speci ic da abase o 400
s uden s o es hem and he esul s ob ained indica e ha he le el o mo i a ion du ing he
adap a ion p ocess has a high po en ial o imp o ing pe o mance and quali y in e-lea ning
sys ems [13].
Figu e 4. Adap a ion Sys em P ocess [13]
Nikola and o he s in hei esea ch, c ea ed an e-lea ning pla o m ha aims o p o ide a solu ion
o c ea ing and main aining cou ses called Di a. The e-lea ning pla o m is an online pla o m
ha aims o help Roma adul s lea n o use IT ools. To achie e his goal, hey use a a ie y o
echnologies o de elop i . The backend is buil using Flask, MySQL and Phusion Passenge is
used as he applica ion se e . The pla o m consis s o se e al co e modules [14].
Figu e 5. Di a Pla o m [14]
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Ba ada i, D. and o he s p oposed a neu oadap i e AI u o ha uses eal- ime EEG signals o
adjus di icul y, s yle, and pace o lea ning. Pilo es ing (n=24) showed inc eased engagemen ,
al hough lea ning gains we e no ye signi ican [15].
Wang, R. and o he s de eloped an AI ool o suppo ing human u o s. In a andomized
con olled ial (900 u o s, 1 800 s uden s), s uden s augh wi h Tu o CoPilo achie ed
signi ican ly highe mas e y (+4 pe cen age poin s o e all; +9 pp o lowe -achie ing s uden s)
[16].
Thomas, D. and o he s p oposed h ee quasi-expe imen s in eal class ooms. Hyb id human-AI
u o ing signi ican ly imp o ed lea ning ou comes, especially among s uden s wi h lowe p io
achie emen [17].
7. PROPOSE AN INNOVATIVE E-LEARNING SYSTEM
In his pa o he s udy, we will de elop a p oposed model o an inno a i e e-lea ning sys em.
Ou model con ains ou s anda d modules, h ee inno a i e ones and a new module ha will
ea u e AI echnology.
The s anda d modules in he inno a i e sys em a e: he Use Managemen Module, he Ca ego y
Managemen Module, he Language Managemen Module and he Use Managemen Module.
The use managemen module has he unc ionali y o each use o c ea e hei own accoun , edi
ha accoun in cou ses and dele e use accoun s. The ca ego y managemen module is asked
wi h c ea ing lis s o cou se ca ego ies, adding, edi ing, dele ing i one is no needed. The
language managemen module will allow you o c ea e a language, edi he language and allow
a chi ing in he app op ia e language. The cou se managemen module is asked wi h c ea ing an
app op ia e cou se and enabling i s edi ing.
The inno a i e modules in ou sys em a e: a da a module, an adap i e lea ning module and an
adap i e module. The da a module is esponsible o s o ing he s uden 's p o ile and assessmen
da a. I also s o es lea ning con en and assessmen ques ions. The esul s o he assessmen s a e
used by he adap i e module o calcula e he le el o adap abili y o he s uden . The adap i e
module is asked wi h de e mining he use 's le el o knowledge ha is announced o he sys em
i sel . This module will use a sequen ial machine lea ning algo i hm ha will be ained o
s uden in e ac ion o i s assess he s uden 's la en s a es o knowledge and de e mine wha le el
o knowledge he lea ne is [11]. The adap i e module de e mines he lea ning mode o he
s uden . Fi s , he le el o knowledge o he s uden himsel is assessed and he e o e his module
will be able o de e mine he le el o di icul y a which he s uden needs o lea n h ough he e-
lea ning sys em.
An AI u o module o e s mo e unc ionali y bu will also connec o o he modules. I p o ides
an enhancemen o he use expe ience o e-lea ning. An AI-assis ed module can assess he
use 's cu en le el o unde s anding and skills and make a sugges ion o a cou se ha he use
should o wan s o use. This module can also be linked o an adap i e module whe e hey will
adjus he weigh and con en based on he use 's p og ess and lea ning s yle. This module will
p o ide a quick way o e ie e cus omized in o ma ion ha will be ob ained based on he use 's
esponses, whe e hey will ecei e ad ice o addi ional esou ces o imp o e he use 's
knowledge. Use s can ask ques ions o he AI u o a any ime, whe e he AI p o ides an answe
o solu ion o he app op ia e ques ion. I a use makes a mis ake no ma e wha pa , his module
can guide hem and help hem co ec he e o s ep by s ep. Wi h he help o AI, he module can
also gi e mul imodal esponses, i.e. using a ious esou ces such as images, ideos, ex . Based
on he use 's choice, his module can p o ide cus omized sugges ed lea ning esou ces, and ocus
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he use on a pa icula cou se. This module may also ha e unc ionali y such as gi ing
in e ac i e ins uc ions, i.e. s ep by s ep explana ions in he a eas o coding, ma hema ical
p oblems, o language lea ning. Use s will be able o in e ac wi h an AI u o / eache in na u al
language in he o m o dialogue, and he AI can also ansla e in o di e en languages. One e y
impo an ea u e o his module is accessibili y, i.e. he main commands whe e use s who ha e
physical o isual impai men s can in e ac wi h he sys em using oice. The op ions o e ed by
his module can allow use s wi h disabili ies o ully engage in lis ening o he cou ses.
Figu e 6. P oposed Inno a i e E-Lea ning Sys em
8. CONCLUSIONS
This s udy highligh s he signi ican ole o e-lea ning sys ems and he applica ion o a i icial
in elligence, wi h a pa icula ocus on he de elopmen o an inno a i e module. The key inding
demons a es ha he in eg a ion o an AI u o enables pe sonalized and adap i e lea ning
pa hways, enhances in e ac ion be ween use s and he pla o m, and op imizes he e iciency o
knowledge acquisi ion. By le e aging AI-d i en adap abili y, he sys em no only ailo s lea ning
ma e ials o he indi idual needs o lea ne s bu also p o ides imely eedback and guidance ha
a e c i ical o main aining lea ne mo i a ion and p og ess.
The no el y o he p oposed app oach lies in combining exis ing modules wi h he AI u o ,
which dynamically adap s con en and p o ides ecommenda ions based on indi idual use
pe o mance. This in eg a ion c ea es an in elligen and lea ne -cen e ed en i onmen ha
o e comes he limi a ions o adi ional e-lea ning pla o ms, which o en ely on s a ic con en
deli e y and gene alized lea ning ajec o ies. Unlike con en ional sys ems, he p oposed
amewo k emphasizes in e ac i i y, pe sonaliza ion, and inclusi i y, he eby os e ing a mo e
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engaging and suppo i e lea ning expe ience o di e se lea ne s, including hose wi h speci ic
needs o disabili ies.
Mo eo e , he AI u o en iches he lea ning p ocess by o e ing mul imodal eedback, in e ac i e
p oblem-sol ing assis ance, and accessibili y ea u es such as na u al language in e ac ion and
oice-based commands. These capabili ies ha e he po en ial o signi ican ly educe ba ie s in
educa ion and democ a ize access o knowledge on a global scale. F om a pedagogical
pe spec i e, his ep esen s a pa adigm shi — om passi e con en consump ion o ac i e,
guided, and adap i e lea ning whe e s uden s a e empowe ed o ake owne ship o hei
educa ional jou ney.
Fu u e s eps include igo ous es ing o he sys em in eal-wo ld en i onmen s, bo h wi h and
wi hou he AI u o module, o quan i a i ely assess i s con ibu ion o lea ning pe o mance,
mo i a ion, and use sa is ac ion. Expanding he pilo o include di e se lea ne popula ions will
enable a deepe unde s anding o how cul u al, linguis ic, and cogni i e ac o s in luence sys em
e ec i eness. Oppo uni ies also exis o scaling he sys em o la ge use bases by in eg a ing i
in o exis ing Lea ning Managemen Sys ems (LMS) and Vi ual Lea ning En i onmen s (VLE).
Such in eg a ion could pa e he way o hyb id educa ional models ha blend adap i e AI-d i en
pe sonaliza ion wi h adi ional ins uc ional p ac ices.
In addi ion, u u e esea ch should examine he e hical and p ac ical conside a ions o deploying
AI u o s, including da a p i acy, algo i hmic anspa ency, and po en ial biases in adap i e
ecommenda ions. Es ablishing clea e alua ion amewo ks and benchma ks will ensu e ha he
sys em no only enhances academic ou comes bu also aligns wi h e hical p inciples and p omo es
ai ness.
In conclusion, he p oposed inno a i e e-lea ning sys em p o ides a obus ounda ion o he
nex gene a ion o digi al educa ion pla o ms. I s emphasis on adap abili y, in e ac i i y, and
inclusi i y demons a es how he in eg a ion o a i icial in elligence can ans o m lea ning in o
a mo e e ec i e, equi able, and pe sonalized p ocess. Wi h con inued de elopmen and
e alua ion, such sys ems hold he p omise o eshaping educa ion in he digi al e a and
con ibu ing signi ican ly o li elong lea ning and global knowledge accessibili y.
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AUTHORS
P o . H is ina Dimo a Popo ska is a Mas e o In o ma ion Sciences a Facul y o
In o ma ion Sciences in Bi ola, Macedonia. She is in e es ed in compu e g aphics,
in e ne o hings e c.
P o . Tome Dimo ski is a Doc o o In o ma ion Sciences a Facul y o In o ma ion
Sciences in Bi ola, Macedonia. He is in e es ed in compu e g aphics, in e ne o hings,
da abase e c.
P o . Filip Popo ski is a Doc o o Technical Sciences in G aphic Enginee ing a
Facul y o Technical Sciences in Bi ola, Macedonia. He is in e es ed in compu e
g aphics, isualiza ion, 3d Vi ual eal.
