Mihai, Lau ențiu; Mănescu, Leona do-Geo; Vasilescu, Lau a; Băndoi, Anca; Si niko ,
Ca alina So iana
A icle
A sys ema ic analysis o new app oaches o digi al
economic educa ion based on he use o AI echnologies
Am i ea u Economic
P o ided in Coope a ion wi h:
The Bucha es Uni e si y o Economic S udies
Sugges ed Ci a ion: Mihai, Lau ențiu; Mănescu, Leona do-Geo; Vasilescu, Lau a; Băndoi, Anca;
Si niko , Ca alina So iana (2024) : A sys ema ic analysis o new app oaches o digi al economic
educa ion based on he use o AI echnologies, Am i ea u Economic, ISSN 2247-9104, The
Bucha es Uni e si y o Economic S udies, Bucha es , Vol. 26, Iss. 65, pp. 201-219,
h ps://doi.o g/10.24818/EA/2024/65/201
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Challenges o Compe ence-O ien ed Educa ion in he Con ex
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Vol. 26 • No. 65 • Feb ua y 2024 201
A SYSTEMATIC ANALYSIS OF NEW APPROACHES TO DIGITAL
ECONOMIC EDUCATION BASED ON THE USE OF AI TECHNOLOGIES
Lau ențiu Mihai1, Leona do-Geo Mănescu2, Lau a Vasilescu3,
Anca Băndoi4 and Că ălina Si niko 5
1)2)3)4)5) Uni e si y o C aio a, Romania
Please ci e his a icle as:
Mihai, L., Mănescu, L.G., Vasilescu, L., Băndoi, A.
and Si niko , C., 2024. A Sys ema ic Analysis o New
App oaches o Digi al Economic Educa ion Based on
he Use o AI Technologies. Am i ea u Economic,
26(65), pp. 201-219.
DOI: h ps://doi.o g/10.24818/EA/2024/65/201
A icle His o y
Recei ed: 29 Sep embe 2023
Re ised: 19 No embe 2023
Accep ed: 20 Decembe 2023
Abs ac
Since he s a o he global COVID-19 pandemic, mos highe educa ion ins i u ions ha e
been o ced o exchange he adi ional eaching en i onmen o online educa ion, and many
chose o con inue o use digi al educa ion pla o ms a e i s end, especially h ough he use o
a i icial in elligence (AI) applica ions and echnologies. Ou esea ch ep esen s a sys ema ic
li e a u e e iew o a numbe o 60 scien i ic pape s, aiming o s udy how he concep o digi al
economic educa ion based on a i icial in elligence is app oached in he scien i ic li e a u e,
how a i icial in elligence applica ions a e used in digi al economic educa ion, and which a e
he c i ical success ac o s and he challenges ha his domain is acing. Ou indings ha e
shown ha mos esea che s de ine digi al educa ion as he use o echnology o suppo
educa ional ac i i ies, while highligh ing a i icial in elligence and i s di e en applica ions as
an essen ial elemen o cu en digi al educa ion, which has he po en ial o undamen ally
ans o m he economic p ocesses. The la ge-scale adop ion o e-lea ning sys ems based on
a i icial in elligence is in luenced by echnology, by hei supe io capabili ies in e ms o
cohe en ly co ela ing he lea ning and s udying p ocesses, by he eache s’ us in he esul s
gene a ed by hese echnologies and by cul u al ac o s, while acing se e al challenges ela ed
o he use s’ esis ance o change, digi al compe ences, he sys ems’ accessibili y, as well as
inancial issues. Fu he mo e, based on his esea ch endea ou , a model sys em o
co ela ions and elemen s has been de eloped, speci ically o he digi al economic educa ion
based on a i icial in elligence. This model includes bo h he success ac o s and he unique
challenges inhe en in he pa icula applica ion a eas.
Keywo ds: A i icial In elligence (AI), digi al economic educa ion, sys emic model
ega ding digi al economic educa ion based on AI
JEL Classi ica ion: D83, I21, I23, O33
Co esponding au ho , Lau ențiu Mihai – e-mail: [email p o ec ed]
This is an Open Access a icle dis ibu ed unde he e ms o he C ea i e Commons
A ibu ion License, which pe mi s un es ic ed use, dis ibu ion, and ep oduc ion in
any medium, p o ided he o iginal wo k is p ope ly ci ed. © 2024 The Au ho (s).
AE
A Sys ema ic Analysis o New App oaches o Digi al Economic Educa ion
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202 Am i ea u Economic
In oduc ion based on he cu en s a e o knowledge
A i icial in elligence ep esen s a c i ical elemen o he con empo a y su ge o eme ging
echnologies, which, la ely, ha e signi ican ly ans o med he landscape o economics
educa ion. A i icial in elligence (AI) e e s o he abili y o a so wa e applica ion o execu e
asks commonly a ibu ed o in elligen beings (Salas Pilco and Yang, 2022), comp ising
se e al b anches, including digi al communica ion, machine lea ning, big da a analysis and
p ocessing, and na u al language p ocessing (Chen e al., 2020). The apid expansion o his
echnology is p og essi ely eshaping he way indi iduals in e ac , communica e, eside,
acqui e knowledge, and engage in p o essional ac i i ies.
A i icial in elligence has a ious applica ions wi hin he ealm o digi al economic
educa ion. Fo example, AI has been included in se e al educa ional echnologies, including
cha bo s (Kasneci e al., 2023), in elligen u o ing sys ems, and au oma ed assessmen
so wa e (Hwang and Tu, 2021). Acco ding o Chen e al. (2020), AI-based sys ems o e
inc eased oppo uni y o all indi iduals in ol ed in he p ocess o economics lea ning and
aining. P e ious s udies ha e demons a ed he bene i s o inco po a ing AI in o economics
educa ion, such as enhanced collabo a ion among s uden s, cus omised lea ning expe iences,
e icien scheduling o lea ning ac i i ies (Cha e jee and Bha a cha jee, 2020), adap i e
eedback on lea ning p ocesses (Salas Pilco and Yang, 2022), educed adminis a i e bu den
o eache s (Xu and Ouyang, 2022), and au oma ion o exam e alua ion and o he
educa ional asks speci ic o economics educa ion (Maslo a e al., 2020).
This pape ocuses on AI in Educa ion (AIED), which encompasses he use o a i icial
in elligence echnologies, including in elligen u o ing sys ems, cha bo s, digi al assis an s,
and o he digi al au oma ion componen s ha con ibu e o he ad ancemen and
enhancemen o digi al economic educa ion (Micu e al., 2021; Bea man e al., 2022). AIED
possesses signi ican po en ial o enhancing lea ning, eaching, e alua ion, and
adminis a ion in economics highe lea ning ins i u ions, o e s he oppo uni y o cus omise
and adap he economics educa ional con en o he speci ic equi emen s o s uden s, while
suppo ing academics in he educa ional p ocess, making i a signi ican eme ging echnology
in he ield o digi al economic educa ion (Felix, 2021; Ooi e al., 2023).
The cu en esea ch add esses AIED as a cen al elemen in op imising eaching-lea ning
p ocesses, yielding signi ican bene i s in pe sonalising he educa ional expe ience (Felix,
2021). AIED applica ions demons a e he capaci y o analyse subs an ial olumes o da a
gene a ed du ing he lea ning p ocess, disce ning pa e ns and adap ing con en based on
indi idual lea ne s' needs. This adap abili y and cus omisa ion o ins uc ion ep esen a no able
ad an age o employing AIED, con ibu ing o he op imisa ion o le els o knowledge
assimila ion (Chen e al., 2022). Thus, he use o AI in digi al educa ion opens subs an ial
pe spec i es o enhancing he e iciency and ele ance o he educa ional p ocess in he cu en
con ex cha ac e ised by accele a ed echnological ad ancemen s (Celik e al., 2022).
Thus, by conduc ing a sys ema ic e iew o he ele an li e a u e published in he las ou
yea s (2020-2023), ou pape aims o con ibu e o he ongoing esea ch on AIED. Ou
esea ch endea ou ocused on answe ing ou esea ch ques ions: (1) How is he concep o
digi al economic educa ion based on AI p esen ed in he ecen li e a u e; (2) How is AI used
in digi al economic educa ion? (3) Wha a e he c i ical success ac o s in luencing he use
o a i icial in elligence applica ions? (4) Wha a e he challenges ha he use o AI
applica ions in digi al economic educa ion is acing?
Challenges o Compe ence-O ien ed Educa ion in he Con ex
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Vol. 26 • No. 65 • Feb ua y 2024 203
In o de o answe he esea ch ques ions, his s udy will discuss on he gene al ea u es o
AIED, he AI’s impac on he economics lea ning p ocess, he ac o s which a ec he
adop ion o hese echnologies, he mos used AIED applica ions as well as he challenges
ha hese echnologies ha e o o e come in o de o be adop ed on a la ge scale.
Consequen ly, he pape is s uc u ed in o wo main sec ions: Resea ch Me hodology which
e e s o sea ch que y used in he Web o Science da abase, he inclusion and exclusion
c i e ia, he quali a i e assessmen and he coding p ocess, and Resul s and Discussion which
includes: he s uc u e on ca ego ies o he pape s included in he analysis, he concep o
economics digi al educa ion based on AI, he use o AI in economics educa ion, c i ical
success ac o s a ec ing he use o AI applica ions, and he challenges which economics
digi al educa ion based on AI is acing and inally, he conclusions and ecommenda ions
o mula ed conside ing he esea ch esul s a e p esen ed.
1. Resea ch Me hodology
1.1. Sea ch que y used in he Web o Science da abase
In o de o ul il ou esea ch objec i e and o answe he ou esea ch ques ions, we ha e
conduc ed a comp ehensi e sea ch o pape s ha we e ela ed o AIED, using he Web o
Science Da abase. The sea ch que y used he ollowing s ing ((TS=“e-lea ning” OR
TS=“digi al economics educa ion” OR TS=“online economics lea ning”) AND (TS=“digi al
ools” OR TS=“AI” OR TS = A i icial In elligence”)), which yielded 12,962 esul s.
In o de o conduc a i s s age analysis, we ha e used VOSViewe so wa e, which has
gene a ed se e al bibliome ic maps, based on which we concluded ha he jou nals which
ha e published he mos pape s on he subjec o AIED a e Educa ion and In o ma ion
Technologies (416 pape s), ollowed by Educa ion Sciences (370 pape s) and In e na ional
Jou nal o Eme ging Technologies in Lea ning (175 pape s).
A he same ime, he mos ci ed jou nal (as o July 2023) is Educa ion and In o ma ion
Technologies (2926 ci a ions), ollowed by Compu e and Educa ion (2245 ci a ions),
Educa ion Sciences (1980 ci a ions), In e na ional Jou nal o Eme ging Technologies in
Lea ning (1209 ci a ions), and In e ac i e Lea ning En i onmen s (1128 ci a ions).
Las ly, he mos ci ed pape s ha add ess he opic o digi al economic educa ion based on
a i icial in elligence un il July 2023 (Figu e no.1) a e Radian i e al. (2020) (419 ci a ions),
Köenig e al. (2020) (244 ci a ions), Wa e meye e al. (2021) (310 ci a ions), and Almaiah
e al. (2020) (308 ci a ions).
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A Sys ema ic Analysis o New App oaches o Digi al Economic Educa ion
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204 Am i ea u Economic
Figu e no. 1. Bibliome ic analysis ega ding he mos ci ed pape s
on he opic o AIED
1.2. Inclusion and exclusion c i e ia and quali y assessmen
In o de o e ine ou sea ch, only esea ch a icles, con e ence p oceedings, and e iew pape
(12,843 pape s), published a e 2020 (6,212 pape s) we e included, om h ee Web o
Science ca ego ies: Educa ion Educa ional Resea ch, Educa ion Scien i ic Disciplines and
Social Issues o Educa ion Special (2,379 pape s), ha ha e been w i en in English (2,604
pape s). Mo eo e , we ha e excluded all he pape s ha ha e been published in medical
jou nals, esul ing in 1,887 pape s. Finally, we limi ed ou sea ch only o open access pape s,
which yielded a inal numbe o 915 a icles. The decision o limi he sea ch o open access
a icles was made based on conside a ions o accessibili y, open access a icles being
a ailable o all indi iduals in e es ed in a speci ic hema ic a ea, enabling hem o ead and
analyse he con en wi hou es ic ions.
Mo ing o wa d, 183 pape s we e alloca ed o each o he i e au ho s. A e eading he
i les and he abs ac s, hose a icles which we e conside ed i ele an o ou esea ch we e
excluded. In o de o be conside ed ele an , he pape s should ha e ocused on a i icial
in elligence used as a digi al educa ion ool. The e we e excluded pape s which we e pu ely
echnical, ocused on p og amming, o ocused on echnical, humani ies, o heal hca e.
Du ing his i s quali y assessmen s age, 143 a icles we e iden i ied ha me he selec ion
c i e ia.
Among hem, each o he i e au ho s ho oughly ead 30-31 pape s, conduc ing a c i ical
analysis o each a icle, using hei expe ience as e iewe s o a ious scien i ic jou nals.
Du ing his second s age o quali y assessmen , we elimina ed he pape s which we e ound
inconclusi e, poo ly w i en, employed ques ionable me hods o in which he indings we e
no ho oughly p esen ed and discussed, eaching a inal numbe o 59 ele an a icles.
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Vol. 26 • No. 65 • Feb ua y 2024 205
Finally, we ha e included one mo e pape (Zawacki-Rich e e al., 2019) in ou analysis,
al hough i was published be o e 2020, because i was being ci ed in many o he a icles
included in he inal po olio by July 2023 (409 ci a ions). The e o e, 60 pape s we e used
in his cu en esea ch (Figu e no. 2).
Figu e no. 2. PRISMA sample design diag am o sys ema ic e alua ion
Sou ce: adap ed a e Bond e al., 2020, p.9
1.3. The coding p ocess
This s age aimed o code he 60 a icles in o ou ca ego ies: digi al educa ion based on AI,
he use o AI in digi al educa ion, and c i ical success ac o s he challenges his a ea is acing.
The au ho s independen ly coded he selec ed a icles, ini ially coding he i s 10 pape s
based on he ou ca ego ies. A e es ablishing and es ing he coding me hodology, ele an
in o ma ion was ex ac ed o u he analysis. O he a iables included he jou nal, he
publica ion yea , he pape ype, and he digi al ool ype (Table no.1). All au ho s
pa icipa ed in he inal coding p ocess, coding 12-13 pape s, and eached a consensus
ega ding he ambiguous indings.
2. Resul s and discussion
2.1. The s uc u e o he pape s included in he s udy
Ou sys ema ic e iew encompasses a o al o 60 esea ch pape s, which ha e been classi ied
in o ou gene al ca ego ies (Table no. 1). Thus, ou sample consis o 22 pape s ca ego ised
as “The concep digi al economics educa ion based on AI”, 24 pape s included in he ca ego y
“The use o a i icial in elligence in digi al economic educa ion”, 5 pape s ca ego ised as
“C i ical success ac o s a ec ing he use o A i icial In elligence applica ions in digi al
economic educa ion” and 7 pape s included in he ca ego y “Challenges acing he use o
a i icial in elligence applica ions in economic educa ion”. Mo eo e , one pape was ound
o be ele an o bo h he “The concep o e-lea ning” and “C i ical in luence ac o s”
ca ego ies, while ano he pape was included in bo h he “C i ical in luence ac o s” and
“Challenges” ca ego ies.
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206 Am i ea u Economic
Table no.1. Pape classi ica ion
Va iable
Pe cen
F equency
Va iable
Pe cen
F equency
Publica ion yea
AI applica ions used in he pape
2019
1.67%
1
AI
31.66%
19
2020
41.67%
25
MOOCs, LMSs
46.67%
28
2021
25%
15
Gami ica ion
1.67%
2
2022
23.33%
14
Blockchain
1.67%
1
2023
8.33%
5
VR
1.67%
1
Jou nal
O he s
16.66%
10
In . J. Eme g.
Technol. Lea n.
18.33%
11
Subjec Ca ego y
Educ. In . Technol.
18.33%
11
Digi al educa ion
based on AI
38.33%
23
Educ. Sci.
8.33%
5
AI in digi al
educai on
40%
24
Compu . Educ.
6.67%
4
C i ical success
ac o s
10%
6
Compu . Educ.: A i .
In ell.
5%
3
Challenges
15%
9
O he s
43.34%
2
2.2. The concep digi al economic educa ion based on AI
Digi al educa ion, also e e ed o as online educa ion, e-lea ning, dis ance educa ion, o
dis ance lea ning, encompasses eaching and lea ning p ocesses conduc ed wi hin an online
se ing (El-Sabagh, 2021). O'Neill (2023) de ines e-lea ning as he use o echnology o aid
ins uc ional ac i i ies, wi h he aim o achie ing speci ied educa ional goals wi hou he
need o bo h he lea ne and he ins uc o o be physically p esen in he same a ea, and
includes a ious elemen s, including echnologies, educa ional sys ems, su oundings, and
he p ima y use s, namely s uden s and eache s.
In he las decade, he educa ional en i onmen has unde gone a signi ican shi om he
adi ional s uc u e o a mo e engaging and s imula ing lea ning en i onmen (Bu le -Hende son
and C aw o d, 2020). In his con ex , he global adop ion o digi al echnologies and ools is
ha ing a p o ound impac on he me hods and p ac ises employed in educa ion. Among he many
digi al ools ha can be used in online educa ion, a i icial in elligence ep esen s an inno a i e
and e olu iona y app oach ha acili a es he cus omisa ion o bo h educa o s' and s uden s'
expe iences. Consequen ly, he use o a i icial in elligence in educa ion has he po en ial o
enhance and adap pedagogical p ac ises by di e en o ms o pe sonalised educa ion, in elligen
con en deli e y, au oma ion o educa ional asks, u o ing, and ensu ing inclusi e educa ional
oppo uni ies o s uden s wi h special equi emen s.
In o de o p ope ly implemen an AIED-based pla o m, se e al elemen s need o be conside ed
such as he s uden s’ in ol emen (Bond e al., 2020; The esiawa i e al., 2020; El-Sabagh, 2021;
Chiu e al., 2021; Ng e al., 2023), digi al li e acy (Falloon, 2020; Köenig e al., 2020; Muamma
e al., 2023), sa is ac ion (Gi ay, 2021; Shams e al., 2021; Zhao e al., 2021), o e all s uden s s’
pe o mance (Bu le -Hende son and C aw o d, 2020; Rakic e al., 2020; Rajabalee and San ally,
Challenges o Compe ence-O ien ed Educa ion in he Con ex
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Vol. 26 • No. 65 • Feb ua y 2024 207
2021), and local ac o s such as echnological esou ces and in e ne connec i i y (An hony e
al., 2020; Khalil Awan e al., 2021; Llo e -I les e al., 2022).
Se e al au ho s a gue ha he concep o e-lea ning is closely associa ed wi h s uden
engagemen (Bond e al., 2020; The esiawa i e al., 2020; Chiu e al., 2021; El-Sabagh, 2021;
Ng e al., 2023), which is d i en by mo i a ion, which is, in u n, in luenced by he s uden s’
au onomy, compe ency, and ela edness. Thus, he e is a need o enhance s uden
in ol emen in e ms o beha iou , a ec , and cogni ion, which should be a p ima y ocus
o educa o s (Ng e al., 2023). Bond e al. (2020) e ealed ha he mos o en iden i ied
a iables a e beha iou al, a ec i e, and cogni i e engagemen . El Sabagh (2021) highligh ed
ha s uden s’ engagemen is closely ela ed o he pe sonalisa ion o he lea ning p ocess
acco ding o hei indi idual lea ning s yles, which also posi i ely in luences hei academic
pe o mance. AI applica ions ha e an essen ial ole in his adap i e app oach o e-lea ning,
which aims o p omo e di ec lea ning, acili a e knowledge de elopmen , and enhance he
o e all lea ning expe ience (The esiawa i e al., 2020; El Sabagh, 2021).
Ano he elemen unde discussion is he le el o s uden sa is ac ion which is in luenced by
he pla o ms’ quali y (Dangaiso e al., 2020; Shams e al., 2022), design (Gi ay, 2021) and
accessibili y (Shams e al., 2020), as well as he way hey a e implemen ed (Almusha a and
Kha o, 2020). The esiawa i e al. (2020) and Gi ay (2021) sugges h ee undamen al
elemen s which in luence he quali y o an AI based e-lea ning sys em: quali y o eaching
s a , he lea ning managemen sys em’s quali y, and con en quali y. S uden s’ engagemen
and sa is ac ion ha e been shown o be closely ela ed, as highligh ed by Rajabalee e al.
(2020), while Rakic e al. (2020) indica e a no ewo hy co ela ion be ween s uden s'
academic pe o mance and he u ilisa ion o AI as a digi al educa ion ool.
Se e al pape s examined he educa o s’ expe ience wi h AI-based e-lea ning pla o ms, as
well as hei pe cep ion ega ding hei e iciency as a lea ning ins umen , highligh ing
se e al d awbacks, such as limi ed ime a ailable o eache s o enhance hei digi al li e acy
(Köenig e al., 2020; Khalil Awan e al., 2021), inadequa e aining (Zhao e al., 2021; Ng e
al., 2023), and imp ope managemen o echnical issues (Dhillon and Mu ay, 2021;
C an ield e al., 2021).
The accele a ed adop ion o e-lea ning sys ems based on a i icial in elligence has led o he
ecogni ion o he impo ance o educa o s’ digi al compe ence (Falloon, 2020; Köenig e al.,
2021; Zhao e al., 2021). In hei wo ks, Ng e al. (2023) and Muamma e al. (2023) ha e
discussed he DigCompEdu amewo k, a guiding p inciple o educa o s in e ec i ely
in eg a ing esou ces and designing AI-based lea ning p og ammes. The model includes
se e al elemen s such as in e ac ion, digi al esou ces (including AI applica ions), eaching
and lea ning, assessmen , empowe ing s uden s, and enabling lea ne s’ digi al p o iciency
(Ng e al., 2023), while aiming o e alua e he academic communi y’s ICT p o iciency and
hei cu en digi al and AI ela ed compe ences (Muamma e al., 2023).
2.3. The use o AI in digi al economics educa ion
Ou esea ch has shown ha se e al ypes o digi al ools can be used in o de o p ope ly
implemen an e-lea ning sys em, among which AI is highligh ed as ha ing he po en ial o
ans o m he educa ional p ocess. Hillmay e al. (2020) iden i ied i e ca ego ies o
AI-based digi al educa ion ools: exe cise and p ac ice p og ammes, u o ing sys ems,
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hype media sys ems, in elligen u o ing sys ems and simula ions, he las wo being he mos
e ec i e. Bon ield e al. (2020), discusses o he ou ypes o AI applica ions: sma
campuses, digi al assis an s, massi e open online cou ses (MOOCs), and Lea ning
Managemen Sys ems (LMSs).
Lizcano e al. (2020) highligh ed he exis ence o a numbe o o he blockchain-based
applica ions, which enable he decen alised alida ion o s uden s' acquisi ion o economics
compe encies, ensu ing ha hei aining aligns wi h he p e ailing job landscape and he
ma ke demands. Radian i e al. (2020) ocuses on i ual eali y economics educa ional
applica ions, which a e shown o be an excellen educa ional ins umen o highe educa ion
bu a e s ill in an expe imen al s age. Abdulaziz Alsuhbhi e al. (2020) deal wi h he opic o
in oduc ion o game elemen s in economics lea ning sys ems, which includes he use o
le els, expe ience poin s, badges, dashboa ds, p og ess ba s, con en unlocking, and leade
boa ds. Fu he mo e, Mhlanga and Moloi (2020) aimed o s udy he use o AI echnologies in
he economics educa ional sec o and hei indings sugges ha he COVID-19 pandemic
de e mined he de elopmen o i ual lea ning pla o ms, he use o educa ional applica ions
and websi es, he es ablishmen o STEM digi al schools, bu also a widesp ead ansi ion o
dis ance lea ning.
Bea man e al. (2022) de ined a i icial in elligence used as a digi al educa ion ool (AIED)
as a digi al echnology capable o e olu ionising con en ional educa ion, o e ing mo e
dynamic and enhanced educa ional app oaches using highly pe sonalised, scalable, and cos -
e ec i e al e na i e solu ions. Xu and Ouyang (2022) de ined AIED as an eme ging
in e disciplina y domain ha uses AI applica ions o ans o m educa ional design and
enhance s uden lea ning. Acco ding o Lame as and A nab (2022), AIED co e s he
de elopmen , implemen a ion, and assessmen o ools, pedagogical models, ins uc ional
amewo ks, e hical conside a ions, and eaching s a compe encies. Chen e al. (2020) s a es
ha he de elopmen and execu ion o AIED echnologies in ol es he collabo a ion o
sys em designe s, da a scien is s, p oduc designe s, s a is icians, linguis s, cogni i e
scien is s, psychologis s, educa ion expe s, and nume ous o he p o essionals. Felix (2021)
highligh s cos and ime sa ing as wo main signi ican ad an ages o AIED, which is
pa icula ly ele an in he cu en economic clima e cha ac e ised by limi ed inancial
esou ces and he need o e ec i e ime managemen . Using AI o assume some aspec s o
he educa ional p ocess has he po en ial o minimise sala y cos s, while allowing acul y
membe s o ocus on o he a eas, such as eache -s uden in e pe sonal ela ionship o
academic esea ch which con ibu es o hei p o essional epu a ion.
Kasneci e al. (2023) as well as Chen e al. (2020) discussed se e al AIED sys ems, such as
na u al language p ocesso s, collabo a i e obo s, la ge language models, and cha bo s,
designed o ei he assis eache s in hei asks o ope a e au onomously, ca ying ou
ac i i ies simila o hose o an educa o . Xu and Ouyang (2022) a gue ha AI has he
po en ial o se e as an educa ional ool, unc ioning as a u o o ins uc o , hus al e ing he
dynamics o he ins uc o -s uden ela ionship, shi ing he pa adigm om an ins uc o -
cen ed o a s uden -cen ed app oach.
Huang (2021) iden i ied h ee key compe encies ha s uden s need o de elop o p ope ly
bene i om AIED: knowledge compe ence, eam compe ence, and lea ning compe ence.
Huang’s (2021) indings show a nega i e co ela ion be ween eamwo k compe ence and
human- ool collabo a ion compe ence and AI cou se con en s, howe e , being con adic ed
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