Vol.:(0123456789)
Educa ion and In o ma ion Technologies
h ps://doi.o g/10.1007/s10639-025-13585-7
A e uni e si y eache s eady o gene a i e a i icial
in elligence? Unpacking acul y anxie y in heCha GPT e a
DomingoVe ano‑Taco on e1 · AliciaBolí a ‑C uz1 · Sil iaSosa‑Cab e a1
Recei ed: 7 Feb ua y 2025 / Accep ed: 16 Ap il 2025
© The Au ho (s) 2025
Abs ac
This s udy in es iga es he ole o echnology‐ ela ed anxie y in shaping uni e si y
eache s’ beha io al in en ion o adop Cha GPT. Th ee dis inc ypes o anxie y
a e examined: (a) anxie y abou he u u e o he academic p o ession, (b) anxie y
ega ding he pe sonal misuse o Cha GPT, and (c) anxie y conce ning nega i e
impac s on s uden lea ning. A s uc u ed ques ionnai e was adminis e ed o 249
acul y membe s om Spanish public uni e si ies. Da a we e analyzed using Pa ial
Leas Squa es S uc u al Equa ion Modeling (PLS-SEM) o assess bo h he di ec
e ec s o each ype o anxie y on beha io al in en ion and he media ing oles o
e o expec ancy (EE) and pe o mance expec ancy (PE). Resul s indica e ha anxi-
e y abou s uden lea ning exhibi s a signi ican nega i e di ec e ec on beha io al
in en ion and an indi ec e ec h ough pe o mance expec ancy. Simila ly, anxie y
ela ed o he misuse o Cha GPT is nega i ely associa ed wi h beha io al in en ion,
wi h signi ican media ion h ough bo h EE and PE. In con as , anxie y conce n-
ing he u u e o he academic p o ession does no show a s a is ically signi ican
ela ionship wi h beha io al in en ion. The indings unde sco e he impo ance o
add essing speci ic psychological ba ie s—pa icula ly hose linked o conce ns
o e s uden lea ning and echnology misuse— o acili a e Cha GPT in eg a ion in
highe educa ion. The s udy sugges s ha e ec i e implemen a ion s a egies should
combine echnical aining wi h a ge ed in e en ions aimed a managing echnol-
ogy- ela ed anxie y, enhancing e hical p ac ices, and imp o ing pe cep ions o he
ool’s u ili y and ease o use.
Keywo ds Gene a i e a i icial in elligence· Anxie y· Technology adop ion·
Highe educa ion· Teache s
Ex ended au ho in o ma ion a ailable on he las page o he a icle
Educa ion and In o ma ion Technologies
1 In oduc ion
Gene a i e a i icial in elligence (GAI) ools like Cha GPT a e apidly ans o m-
ing he landscape o highe educa ion. These echnologies challenge adi ional
academic p ac ices by in oducing capabili ies ha go a beyond p e ious inno-
a ions. Cha GPT, o ins ance, can gene a e human-like ex , o e pe sonalized
u o ing, and au oma e in ica e educa ional asks (Pasupule i & Thiyyagu a,
2024). Unlike ea lie ools, i s in luence is no limi ed o assis ing in isola ed
asks; a he , i has he po en ial o undamen ally eshape pedagogical ela ion-
ships, ins uc ional s a egies, and e en he co e oles o uni e si y eache s.
Conce ns abou he displacemen o diminishing alue o uni e si y eache s is
a psychological and p o essional challenge ha can a ec he adop ion o his
echnology. This ans o ma i e powe compels uni e si ies o econside how
echnology in eg a es in o he eaching–lea ning p ocess, p esen ing bo h oppo -
uni ies and challenges o acul y (Hende son & Co y, 2021; Jain & Raghu am,
2024).
While signi ican esea ch has explo ed echnology adop ion in educa ion,
he e is a no able lack o ocus on he psychological dimensions o inco po a ing
ools like Cha GPT. Resea ch on Cha GPT adop ion has p edominan ly ocused
on unde g adua e s uden s (e.g., Pasupule i & Thiyyagu a, 2024; S zelecki &
ElA abawy, 2024), lea ing uni e si y eache s as a ela i ely unde s udied g oup.
This gap is e iden in he lack o esea ch, pa icula ly empi ical s udies, examin-
ing acul y engagemen wi h Cha GPT. While some ecen s udies ha e explo ed
his opic, hey do no speci ically ocus on he uni e si y con ex (Al Da ayseh,
2023; Choca o e al., 2023). This s udy explo es he anxie y expe ienced by uni-
e si y eache s in adop ing GAI ools and in es iga es he di e en ypes o anxi-
e y acco ding o hei unde lying cause. In addi ion, p e ious wo k has add essed
anxie y in echnology adop ion (e.g., Chiu & Chu chill, 2016; Duong e al., 2024;
Gunasinghe & Nanayakka a, 2021; Lakhal & Khechine, 2021 and Mac Callum
e al., 2014). Howe e , acco ding o he li e a u e e iew conduc ed, he e is no
e idence ha he a ious causes o anxie y ha e been empi ically add essed. Spe-
ci ically, his s udy examines h ee c i ical kinds o anxie y ela ed o he adop-
ion o GAI echnologies: (1) conce ns abou how Cha GPT may d i e signi ican
p o essional changes, including shi s in uni e si y eache s’ oles and esponsi-
bili ies; (2) ea s abou uni e si y eache s’abili y o e ec i ely manage and use
Cha GPT in hei own wo k; and (3) uni e si y eache s’ app ehensions ega ding
i s po en ial impac on s uden s’lea ning ou comes, such as diminished e o o
inc eased dependence on a i icial in elligence (AI) ools. Add essing hese kinds
o anxie y is c ucial, as hey highligh p e iously unexplo ed ba ie s ha uni e -
si y eache s ace in adap ing o hese dis up i e echnologies.
Two o hese kinds o anxie y, namely he p o essional changes and he impac
on s uden lea ning, a e pa icula ly no ewo hy because, o he bes o ou knowl-
edge, hey ha e no been s udied in an academic con ex . By explo ing hese
issues, his s udy con ibu es o li e a u e by illing a gap in he unde s anding
o how eache s pe cei e and espond o GAI echnologies. These conce ns go
Educa ion and In o ma ion Technologies
beyond echnical usabili y o encompass deepe p o essional and e hical chal-
lenges, such as ea s o de alua ion o he eache s’s ole and skep icism abou he
long- e m e ec s o AI in eg a ion on s uden engagemen and lea ning ou comes.
To s udy how echnology is adop ed, as is he case wi h his wo k, li e a u e
uses in en ion models, including he Uni ied Theo y o Accep ance and Use o
Technology (UTAUT). UTAUT is a well-known amewo k o analyzing echnol-
ogy adop ion, especially in business and educa ional se ings (Xue e al., 2024).
The model iden i ies he ac o s ha in luence whe he people will use echnology
o no , such as social in luence, acili y condi ions, pe o mance expec ancy and
e o expec ancy (Fa ooq e al., 2017; Venka esh e al., 2003). Social in luence
e e s o he ex en o which indi iduals pe cei e ha impo an o he s (e.g., col-
leagues, supe iso s, pee s) expec hem o use he echnology. Facili a ing con-
di ions e e s o he deg ee o which indi iduals belie e ha o ganiza ional and
echnical in as uc u e suppo s hei use o he echnology. Pe o mance expec-
ancy is de ined as he deg ee o which using echnology will p o ide bene i s o
use s when pe o ming ce ain ac i i ies. E o expec ancy is he belie ha a
speci ic echnology will be easy o use. UTAUT p o ides a s uc u ed app oach
o examine how anxie y a ec s echnology adop ion. I highligh s how psycho-
logical ba ie s can in luence how uni e si y eache s e alua e he use ulness and
ease o use o AI-d i en ools. This pape ocuses on wo o he UTAUT a i-
ables: pe o mance expec ancy and e o expec ancy. Gi en ha his s udy aims
o examine how echnology- ela ed anxie y a ec s uni e si y eache s’beha io al
in en ion o adop Cha GPT, he pe o mance expec ancy and e o expec ancy
a iables a e he mos di ec p edic o s o beha io al in en ion. This is because
hey di ec ly e lec use s’pe cep ions o a echnology’s use ulness and ease o
use (Venka esh e al., 2003). Conside ing ha anxie y is likely o in luence hese
cogni i e e alua ions by al e ing bo h pe cei ed bene i s and expec ed e o ,
ocusing on pe o mance expec ancy and e o expec ancy allows o cap u e he
co e mechanisms h ough which anxie y a ec s echnology adop ion. Fu he -
mo e, he concep ualiza ion o anxie y in his s udy speci ically add esses he
emo ional and cogni i e ba ie s ha shape uni e si y eache s’e alua ions o he
usabili y and e ec i eness o Cha GPT. P io li e a u e sugges s ha anxie y may
dis o pe cep ions o a echnology’s ease o use and i s po en ial o imp o e pe -
o mance (e.g., Chiu & Chu chill, 2016; Gunasinghe & Nanayakka a, 2021). In
con as , o he UTAUT dimensions, such as social in luence and acili a ing con-
di ions, a e less di ec ly ela ed o hese psychological p ocesses, especially in
he au onomous con ex o highe educa ion. On he o he hand, uni e si y each-
e s ypically ope a e in en i onmen s whe e indi idual expe ise and p o essional
au onomy educe he impac o ex e nal social p essu es and a iable acili a ing
condi ions. In such se ings, he p ima y conce ns ocus on whe he a new ech-
nology inc eases p oduc i i y and whe he i can be seamlessly in eg a ed in o
exis ing eaching p ac ices.
Based on he abo e a gumen s, his esea ch has wo objec i es. Fi s , i aims
o iden i y and analyze he ypes o anxie y ha in luence uni e si y eache s’
adop ion o Cha GPT, wi h a ocus on i s no el aspec s o p o essional ans-
o ma ion and s uden - ela ed impac s. Secondly, i explo es how he ypes o
Educa ion and In o ma ion Technologies
anxie y indi ec ly a ec beha io al in en ion (BI) h ough he expec ancy o e o
(EE) and he expec ancy o pe o mance (PE).
Uni e si y eache s’ pe cep ions a e cen al o he success o ailu e o ech-
nology in eg a ion in educa ion (Liu e al., 2020). Teache s se e as he p ima y
agen s o implemen a ion, b idging he gap be ween ins i u ional s a egies and
class oom p ac ices. Thei conce ns—whe he ega ding p o essional iden i y,
echnological complexi y, o pedagogical impac —canno be o e looked. Failu e
o add ess hese issues isks aliena ing uni e si y eache s, c ea ing esis ance o
adop ion, and unde mining he po en ial bene i s o GAI echnologies.
This s udy’s con ibu ions a e bo h heo e ical and p ac ical. Theo e ically,
i ad ances he unde s anding o he psychological and p o essional ba ie s o
adop ing GAI ools by ocusing on p e iously unexplo ed kinds o uni e si y
eache s’ anxie y. P ac ically, i o e s ac ionable insigh s o highe educa ion
ins i u ions, enabling hem o design a ge ed in e en ions ha add ess uni e si y
eache s´ conce ns and ensu e a smoo he in eg a ion o Cha GPT. By ocusing
on how EE and PE media e hese ypes o anxie y, he esea ch highligh s spe-
ci ic ac o s ha ins i u ions can le e age o encou age adop ion while minimiz-
ing esis ance.
2 Li e a u e e iew
2.1 Anxie y andin en ion oadop Cha GPT byuni e si y eache s
Anxie y is de ined as an emo ional esponse ha nega i ely in luences an indi-
idual’s in en ion o engage in ce ain beha io s (Bandu a, 1986). In he con ex
o echnology adop ion, i can mani es as a empo a y eeling o unease, ea , o
discom o ega ding he implica ions o using a echnology (Debasa e al., 2023;
Duong e al., 2024; Gunasinghe & Nanayakka a, 2021; Venka esh e al., 2012),
and esea ch has consis en ly shown ha such anxie y can be a signi ican ba ie
o adop ing new echnologies (Gunasinghe e al., 2019; Holzmann e al., 2020;
Lakhal & Khechine, 2021; Maican e al., 2019).
This pape explo es anxie y in a mo e comp ehensi e manne han is com-
mon in li e a u e. This app oach allows us o examine how indi idual, e hical,
and p o essional conside a ions shape he adop ion o GAI in highe educa ion.
Speci ically, he s udy in es iga es he anxie y expe ienced by uni e si y eache s
when adop ing echnology and ocuses on he causes o his anxie y. The kinds o
anxie y s udied in his pape a e ela ed o (a) he po en ial impac o Cha GPT on
he academic p o ession, (b) he challenges associa ed wi h using his echnologi-
cal ool, and (c) he impac o Cha GPT on s uden lea ning ou comes. Toge he ,
hese elemen s cap u e he in e play be ween eache s’ pe sonal expe iences and
he b oade e hical and s uc u al implica ions o echnology in hei p o essional
con ex s. I is wo h no ing ha , o hese h ee kinds o anxie y, he i s wo a e
no el in he a ea o echnology adop ion by uni e si y eache s.
Educa ion and In o ma ion Technologies
2.1.1 Anxie y abou he u u e o heacademic p o ession (ANXP)
The de elopmen o AI is expec ed o ans o m—and, in some cases, h ea en—
ce ain jobs, bo h quan i a i ely and quali a i ely (Dwi edi e al., 2023; Wang &
Wang, 2022). Educa o s, in pa icula , may exp ess conce n ha ools like Cha GPT
could eplace human in elligence (Hazzan-Bisha a e al., 2025; Sampson, 2021).
Resea ch by Fel en e al. (2023) highligh s ha uni e si y eache s in disciplines
such as English, li e a u e, and his o y a e among hose mos a isk om he ise o
GAI echnologies.
Cha GPT has demons a ed i s abili y o c ea e assignmen s, gene a e assessmen
ques ions, g ade a ious ypes o s uden wo k, and p oduce lea ning ma e ials.
These capabili ies may lead uni e si y eache s o ede ine hei p o essional oles.
In his e ol ing landscape, eache s will need o ocus mo e on moni o ing and c i i-
cally e alua ing he ou pu gene a ed by GAI ools (Hu e al., 2025).
Fo ins ance, AI-d i en bo s a e being p esen ed as al e na i es o human u o s,
wi h he no able ad an age o being accessible o s uden s a any ime. In some
cases, hese ools can e en p oduce esul s compa able o hose o human ins uc o s
(Edwa ds & Cheok, 2018; Ilie a e al., 2023; Li e al., 2024). Cha GPT’s abili y o
o e s uden suppo , add ess ques ions ins an ly, and p o ide pe sonalized u o ing
may educe he signi icance o eache s’ oles in he educa ional p ocess (Bae e al.,
2024).
The in eg a ion o GAI ools in o educa ion may, he e o e, equi e eache s o
acqui e new compe encies o adap e ec i ely o hese echnologies (Dwi edi e al.,
2023; Sampson, 2021; Van Dis e al., 2023). This shi and he apid pace o echno-
logical change may lead eache s o eel less e ec i e, less use ul in hei oles, and
in some cases, ea job displacemen . This si ua ion, ha can cause discom o and
anxie y among uni e si y eache s, is al eady becoming a eali y (Bae e al., 2024;
Zhang & Aslan, 2021).
2.1.2 Anxie y abou misusing Cha GPT (ANXU)
Academic in eg i y has a signi ican ly nega i e di ec e ec on uni e si y eache s’
adop ion o Cha GPT (Bin-Nashwan e al., 2023). This sugges s ha highe le els o
academic in eg i y among academics co espond o lowe use o Cha GPT in hei
wo k. This aligns wi h conce ns abou echnology anxie y, a eeling o app ehension
ha a ises when indi iduals ace he possibili y o using new echnologies (Gelb ich
& Sa le , 2014).
While Cha GPT has demons a ed alue in gene a ing educa ional and esea ch
ma e ials, i s use aises signi ican unce ain ies (Dowling & Lucey, 2023; Hu e al.,
2025). Fo ins ance, ques ions abou whe he i is necessa y o disclose Cha GPT
usage, how such disclosu e migh a ec he legi imacy o he ma e ials p oduced,
and conce ns o e au ho ship pe sis (Bae e al., 2024; Tho p, 2023). These doub s
a e pa icula ly salien o uni e si y eache s, who may ques ion he e hical implica-
ions, accu acy, and po en ial epu a ional isks associa ed wi h using Cha GPT in
eaching and esea ch (Bae e al., 2024; Else, 2023; Hu e al., 2025; Yu, 2024). The
Educa ion and In o ma ion Technologies
in e play be ween academic in eg i y and echnology anxie y unde sco es he com-
plex challenges eache s ace in in eg a ing GAI in o hei p o essional p ac ices.
2.1.3 Anxie y abou s uden lea ning (ANXS)
In he ligh o Cha GPT’s demons a ion o i s abili y o gene a e ex , a deba e has
a isen as o whe he AI ools, and Cha GPT in pa icula , should be es ic ed in
academic se ings. Conce ns such as s uden plagia ism, he c ea ion o ake con-
en , and legal ami ica ions a e cen al o hese discussions. Uni e si y eache s
ha e exp essed conce ns abou main aining academic in eg i y and ensu ing e ec-
i e s uden lea ning, as e lec ed in he limi ed academic esea ch a ailable (e.g.,
Bae e al., 2024; Co on e al., 2023; Dwi edi e al., 2023; Ga cía-Peñal o, 2023;
Sulli an e al., 2023).
A pa icula conce n is ha s uden s may become o e ly elian on Cha GPT,
po en ially comp omising hei abili y o comple e academic asks independen ly.
De ec ing whe he s uden s ha e used Cha GPT o assignmen s p esen s a signi i-
can challenge due o he ool’s abili y o closely mimic human-gene a ed con en
(Dwi edi e al., 2023). This abili y complica es adi ional app oaches o assessing
o iginali y and con ibu es o uni e si y eache s’conce ns abou he po en ial e o-
sion o he au hen ici y o he lea ning p ocess.
As a esul o hese conce ns, uni e si y eache s may be eluc an o inco po-
a e Cha GPT in o hei class oom p ac ices (Jain & Raghu am, 2024), based on
he belie ha he ool may unde mine he co e p inciples o educa ion and hinde
meaning ul s uden engagemen (Bae e al., 2024; Yu, 2024).
Acco dingly, he ollowing hypo hesis is p oposed:
H1 Anxie y has a di ec and signi ican nega i e associa ion wi h he in en ion o
use Cha GPT by uni e si y eache s (BI).
H1a Anxie y ega ding he impac ha Cha GPT may ha e on he academic p o-
ession (ANXP) has a di ec and signi ican nega i e associa ion wi h he in en-
ion o use Cha GPT by uni e si y eache s (BI).
H1b Anxie y ega ding he misuse o echnology (ANXU) has a di ec and signi -
ican nega i e associa ion wi h he in en ion o use Cha GPT by uni e si y each-
e s (BI).
H1c Anxie y ega ding he s uden lea ning (ANXS) has a di ec and signi ican
nega i e associa ion wi h he in en ion o use Cha GPT by uni e si y eache s
(BI).
2.2 Media ing e ec s on he ela ionship be weenanxie y andin en ion
In he p e ious sec ion, i was a gued ha echnology- ela ed anxie y is bo h di ec ly
and nega i ely ela ed o he in en ion o use Cha GPT. In his sec ion, he indi ec
e ec o anxie y on beha io al in en ion is analyzed h ough he EE and PE a i-
ables. Fo in en ion models, like UTAUT, hese wo a iables a e c i ical.
Educa ion and In o ma ion Technologies
2.2.1 Media ing e ec o e o expec ancy (EE) on he ela ionship be weenanxie y
andin en ion ouse Cha GPT (BI)
E o expec ancy (EE) is de ined as he deg ee o which indi iduals pe cei e a
echnology as easy o use. In he con ex o his s udy, EE e e s o he ex en o
which academics pe cei e Cha GPT as an accessible and use - iendly ool ha can
be seamlessly in eg a ed in o hei eaching p ac ices. This includes an assessmen
o he complexi y o he sys em, he pe cei ed ease o di icul y o i s ope a ion,
and he amoun o e o equi ed o e ec i ely use Cha GPT wi hin an educa ional
se ing. The impo ance o EE in in luencing BI has been highligh ed by p e ious
esea ch. Li e a u e shows ha he ease o use o echnology (Xue e al., 2024), pa -
icula ly GAI ools (Jain & Raghu am, 2024) and Cha GPT speci ically (Hidaya -u -
Rehman & Ib ahim, 2024), is a c i ical ac o o uni e si y eache s in de e mining
hei willingness o adop such inno a ions. In his con ex , he pe cep ion o ease
o use (de ined as he deg ee o which eache s belie e he echnology minimizes
e o ) is pa amoun in shaping hei in en ion o in eg a e hese ools.
The in luence o anxie y on EE has been ex ensi ely documen ed in he li e a-
u e. Fo example, Gunasinghe and Nanayakka a (2021) epo ha echnology-
ela ed anxie y nega i ely a ec s use s’pe cep ions o echnological usabili y. Simi-
la ly, Chiu and Chu chill (2016) and Mac Callum e al. (2014) ind ha eache s
who expe ience ele a ed le els o anxie y when using echnology as a lea ning and
eaching ool a e less likely o pe cei e such echnology as use - iendly. This dimin-
ished pe cep ion o usabili y subsequen ly inhibi s he likelihood o adop ion. Anxi-
e y exace ba es pe cep ions o complexi y and ein o ces conce ns abou he e o
equi ed o lea n and use he echnology e ec i ely.
Mo eo e , in he speci ic con ex o Cha GPT and o he GAI ools, anxie y may
a ise om ea s ha hese echnologies could po en ially displace he ole o he uni-
e si y eache , comp omise he quali y o he lea ning p ocess o s uden s, o lead
o e o s due o misuse. Such conce ns may ein o ce he pe cep ion ha he ool is
inhe en ly di icul o use, u he educing EE. As a esul , uni e si y eache s who
expe ience heigh ened anxie y a e mo e likely o nega i ely e alua e he usabili y o
Cha GPT and o he GAI ools, educing hei willingness o adop hese inno a ions
(Mac Callum e al., 2014).
In his con ex , echnology- ela ed anxie y, by al e ing uni e si y eache s’ pe -
cep ions o usabili y, plays a signi ican ole in de e mining hei in en ion o adop
new echnologies. These a gumen s, suppo ed by exis ing empi ical e idence, lead
o he o mula ion o he ollowing hypo hesis:
H2 E o expec ancy (EE) media es he ela ionship be ween he in en ion o use
Cha GPT by uni e si y eache s (BI) and anxie y.
H2a E o expec ancy (EE) media es he ela ionship be ween he in en ion o
use Cha GPT by uni e si y eache s (BI) and anxie y ega ding he impac ha
Cha GPT may ha e on he academic p o ession (ANXP).
H2b E o expec ancy (EE) media es he ela ionship be ween he in en ion o
use Cha GPT by uni e si y eache s (BI) and anxie y ega ding he misuse o
echnology (ANXU).
Educa ion and In o ma ion Technologies
H2c E o expec ancy (EE) media es he ela ionship be ween he in en ion
o use Cha GPT by uni e si y eache s (BI) and anxie y ega ding he s uden
lea ning (ANXS).
2.2.2 Media ing e ec o pe o mance expec ancy (PE) on he ela ionship
be weenanxie y andbeha io al in en ion (BI)
Pe o mance expec ancy (PE) is de ined as he deg ee o which using echnology
will p o ide bene i s o use s when pe o ming ce ain ac i i ies, which in his
s udy e e s o he deg ee o which academics belie e ha using Cha GPT would
help hem o a ain gains and inc ease oppo uni ies, achie emen s, and p oduc-
i i y in hei eaching p ac ice.
Anxie y ela ed o he use o GAI can nega i ely impac PE, as uni e si y
eache s may pe cei e less u ili y in a echnology ha elici s signi ican conce n.
When he adop ion o GAI echnologies necessi a es p o ound changes in es ab-
lished academic p ac ices and diminishes he pe cei ed alue o he eache ’s
con ibu ion, i can lead o a educed pe cep ion o PE. Uni e si y eache s may
iew such echnologies as less bene icial i hey pe cei e ha hei p o essional
ole is being unde mined o de alued.
Addi ionally, conce ns abou he po en ial o une hical use by s uden s—such
as elying on GAI ools o academic dishones y—o he pe cep ion ha s uden s
a e exe ing less e o in lea ning and becoming o e ly dependen on echnol-
ogy o comple ing academic asks may u he educe he pe cei ed use ulness
o GAI ools. Teache s migh in e p e such dependencies as de imen al o he
o e all educa ional p ocess, he eby diminishing hei belie in he alue o hese
echnologies.
Fu he mo e, anxie y has been ound o nega i ely in luence indi iduals’ pe o -
mance expec a ions ela ed o echnology use (Celik, 2016; Gunasinghe & Nanay-
akka a, 2021; Gunasinghe e al., 2019). This sugges s ha eache s who expe ience
highe le els o anxie y ega ding GAI may be less likely o pe cei e i s u ili y in
imp o ing hei eaching ou comes. Anxie y also a ec s he pe cei ed e o equi ed
o comple e a ask using echnology, as i ampli ies ea s and conce ns abou com-
plexi y and usabili y (Celik, 2016; Gunasinghe & Nanayakka a, 2021). These nega-
i e emo ions—such as wo y, ea , o uneasiness—no only a ec how uni e si y
eache s pe cei e he use ulness o GAI bu also igge wi hd awal beha io s. Fo
ins ance, anxie y can lead o physical wi hd awal, whe e eache s a oid using he
echnology al oge he , o men al wi hd awal, whe e hey engage in nonp oduc i e
asks un ela ed o hei p o essional goals (Huang e al., 2024). Bo h o ms o wi h-
d awal impede e ec i e ask pe o mance and u he ein o ce nega i e pe cep ions
o GAI ools.
Finally, i uni e si y eache s pe cei e ha hey lack su icien con ol o e hei
own use o GAI ools o ques ion whe he hei ou pu s gene a ed wi h hese ech-
nologies a e app op ia ely execu ed, hei pe cep ion o he ool’s u ili y may also
decline (Gunasinghe & Nanayakka a, 2021). These ac o s collec i ely sugges ha
anxie y and associa ed conce ns signi ican ly unde mine he pe cep ion o GAI as a
Educa ion and In o ma ion Technologies
aluable esou ce in he academic con ex , highligh ing he impo ance o add ess-
ing hese psychological ba ie s o p omo e e ec i e adop ion (A paci & Basol,
2020).
Gi en ha he ela ionship be ween PE and BI has been ex ensi ely alida ed
in he li e a u e (Hu e al., 2020; Lee e al., 2024; Xue e al., 2024), he ollowing
hypo hesis is p oposed:
H3 Pe o mance expec ancy (PE) media es he ela ionship be ween he in en ion
o use Cha GPT by uni e si y eache s (BI) and anxie y.
H3a Pe o mance expec ancy (PE) media es he ela ionship be ween he in en-
ion o use Cha GPT by uni e si y eache s (BI) and anxie y ega ding he impac
ha Cha GPT may ha e on he academic p o ession (ANXP).
H3b Pe o mance expec ancy (PE) media es he ela ionship be ween he in en-
ion o use Cha GPT by uni e si y eache s (BI) and anxie y ega ding he misuse
o echnology (ANXU).
H3c Pe o mance expec ancy (PE) media es he ela ionship be ween he in en-
ion o use Cha GPT by uni e si y eache s (BI) and anxie y ega ding he s uden
lea ning (ANXS).
2.3 Cha GPT´s beha io al in en ion anduse beha io
As es ablished in in en ion models, such as hose p oposed by Venka esh e al.
(2003), BI is a c i ical de e minan o echnology use beha io (UB). These models
consis en ly demons a e ha highe le els o BI posi i ely and signi ican ly in lu-
ence ac ual usage beha io .
In he con ex o highe educa ion, he BI-UB ela ionship has been shown o be
pa icula ly s ong, su passing i s p edic i e powe in o he educa ional se ings (S -
zelecki & ElA abawy, 2024; Xue e al., 2024). The ollowing hypo hesis is p oposed:
H4 In en ion o use Cha GPT (BI) by uni e si y eache s is posi i ely, di ec ly,
and signi ican ly associa ed wi h ac ual use o Cha GPT (UB).
Wi h hese a ionales in mind, a esea ch model was designed o analyze he
di ec e ec o anxie y ypes on in en ion o use Cha GPT (BI), i s indi ec e ec
h ough e o expec ancy (EE) and pe o mance expec ancy (PE), and he BI-UB
ela ionship (Fig.1).
3 Me hod
3.1 Ins umen
To collec he da a o es he o mula ed hypo heses, a ques ionnai e was de el-
oped. The ques ionnai e was di ided in o h ee sec ions: he i s sec ion con ained
an in oduc ion and gene al in o ma ion abou he subjec o he s udy, while he
Educa ion and In o ma ion Technologies
hus con i ming H4. Acco ding o Cohen’s p oposal (Cohen, 1988), BI con ibu es
g ea ly o explaining UB ( 2 ≥ 0.35).
The condi ions es ablished by Ba on and Kenny (1986) o media ion analysis
equi e, i s ly, di ec signi ican ela ions be ween he a iables being media ed and
he media o s. Figu e2 shows he signi ican ela ionship o ANXU wi h EE (β = −
0.186, p < 0.05) and wi h PE (β = − 0.153, p < 0.05), as well as ha o ANXS wi h
EE (β = − 0.159, p < 0.05) and wi h PE (β = − 0.190, p < 0.05). Signi ican e ec s
o EE (β = 0.167, p < 0.05) and PE (β = 0.640, p < 0.001) on BI a e also con i med.
The ANXP ela ionships a e no signi ican .
Fu he mo e, he analysis o indi ec e ec s de e mines whe he he e is media-
ion (Cepeda e al., 2017). As shown in Table6, he simple indi ec e ec o EE on
he ela ions ANXU-BI (β = − 0.031, p < 0.05) and ANXS-BI (β = − 0.027, p <
0.001) a e signi ican and nega i e, indica ing he same di ec ion o he di ec e ec
(pa ial complemen a y media ion). The same occu s wi h he simple indi ec e ec s
o PE in hese ela ionships (β = − 0.098, p < 0.05; β = − 0.122, p < 0.05), hus con-
i ming he complemen a y pa ial media ing e ec . This means ha bo h EE and
PE explain pa o he obse ed ela ionship be ween he di e en kinds o anxie y
and BI (Hai e al., 2017), while anxie y also explains pa o BI, independen ly o
EE and PE. Howe e , he media ing e ec o EE and PE in he ANXP-BI ela ion-
ship is no signi ican , so H2b and H3b a e no con i med. In addi ion, he mul iple
indi ec e ec o EE and PE on ANXU-BI is signi ican , sugges ing ha EE and PE
join ly in luence he ela ionship be ween ANXU and BI, wi h PE (β = − 0.098)
being he p ima y d i e o he media ion (44.29% o he o al e ec ). This phe-
nomenon is also obse ed in he ANXS-BI ela ionship, whe e PE (β = − 0.122)
accoun s o 43.64% o he o al e ec .
To con i m he hypo heses o pa ial media ions, he explained a iance (VAF) is
calcula ed. VAF de e mines he a io be ween he indi ec e ec and he o al e ec
(Ni zl e al., 2016) and i s alue should be be ween 0.2 and 0.8 (Hai e al., 2017).
The calcula ed VAFs (Table7) co obo a e he pa ial media ion o EE and PE in
Table 6 Media ion es
No e: boo s apping based on 10,000 subsamples; ***p < 0.001; **p < 0.05; *p < 0.01; ns: non-signi i-
can
Simple Speci ic indi ec e ec s β 95% CI
H2a ANXP-EE-BI 0.005 ns 0.415 − 0.0150.027
H2b ANXU-EE-BI − 0.031** 1.828 − 0.063–0.008
H2c ANXS-EE-BI − 0.027* 1.559 − 0.059–0.004
H3a ANXP-PE-BI 0.028 ns 0.538 − 0.0530.120
H3b ANXU-PE-BI − 0.098 ** 1.919 − 0.184–0.016
H3c ANXS-PE-BI − 0.122** 2.541 − 0.200–0.043
To al indi ec e ec s β 95% CI
Mul iple ANXP-BI 0.034 ns 0.570 − 0.059 0.134
ANXU-BI − 0.129** 2.246 − 0.227 − 0.036
ANXS-BI − 0.148** 2.736 − 0.236 − 0.059
Educa ion and In o ma ion Technologies
he ANXU-BI ela ionship, and ha o PE in he ANXS-BI ela ionship. This sup-
po s hypo heses H2b, H3b and H3c. The VAF = 0.17 in he ANXS-EE-BI ela ion-
ship indica es ha no media ion occu s due o i s i ele an impac , so H2c is no
con i med.
In e ms o he con ol a iables, he esul s show ha gende has a signi ican
e ec on BI (β = − 0.166, p < 0.05) and on UB (β = − 0.158, p < 0.05). In his
sense, women ha e lowe BI and UB han hei male colleagues. Nei he age no
wo k expe ience ha e a signi ican e ec on BI and UB.
5 Discussion
This s udy se s ou o add ess wo objec i es. Rega ding he i s objec i e, he
exis ence o h ee ypes o anxie y ha may in luence he beha io al in en ion o
adop Cha GPT was explo ed. This beha io al in en ion is a key a iable in UTAUT
model. While p e ious s udies ha e add essed echnological anxie y o echnos ess,
his wo k makes a dis inc e o o de ail he speci ic sou ces o anxie y ha uni e -
si y eache s expe ience when conside ing he use o Cha GPT and, by ex ension,
o he GAI ools. The indings suppo ed ha anxie y di ec ly and nega i ely impac s
eache s’ in en ion o adop he ool. This is especially ue o anxie y abou s uden
lea ning acco ding o p e ious li e a u e (e.g., Co on e al., 2023; Dwi edi e al.,
2023). This means ha , in he con ex o he use o GAI, i has been obse ed ha
when eache s eel anxious abou he possibili y o s uden s misusing his echnol-
ogy ( o example, plagia ism o excessi e dependence on au oma ed answe s), his
anxie y di ec ly educes hei willingness o use he ool in hei classes (Bae e al.,
2024; Sulli an e al., 2023).
A di ec nega i e associa ion was also obse ed be ween anxie y abou uni e si y
eache s’ misusing Cha GPT and beha io al in en ion. This means ha when each-
e s a e a aid ha Cha GPT could p oduce inaccu a e, misused o e en plagia ized
in o ma ion, hey a e less willing o adop i , as he use o GAI gene a ed con en
can comp omise he academic in eg i y o he ma e ials p oduced. This inding is
consis en wi h p e ious wo k ha indica es ha e hical o p o essional doub s abou
echnological ools end o unde mine hei accep ance (e.g., Bin-Nashwan e al.,
2023; Hu e al., 2025).
Table 7 Indi ec e ec s’ and o al e ec s’ a iance accoun ed (VAF)
H2b H2c H3b H3c
E ec s ANXU
→
BI ANXS
→
BI E ec s ANXU
→
BI ANXS
→
BI
Di ec β = − 0.091 β = − 0.131 Di ec β = − 0.091 β = − 0.131
EE Indi ec β = − 0.031 β = − 0.027 PE Indi ec β = − 0.098 β = − 0.122
EE To al β = − 0.122 β = − 0.158 PE To al β = − 0.189 β = − 0.253
VAF 0.254 0.17 VAF 0.518 0.48
Educa ion and In o ma ion Technologies
Howe e , no signi ican associa ion was ound be ween anxie y ela ed o p o-
ound changes in eaching asks and he po en ial de alua ion o he eaching p o es-
sion as i is cu en ly concei ed. A plausible explana ion o his inding is he high
le el o job secu i y p e alen among mos eache s in he Spanish public uni e -
si y sys em (Minis e io de Uni e sidades, 2024). Unde Spanish legisla ion, each-
e s who ha e ob ained s able posi ions gene ally enjoy pe manen con ac s ha a e
p o ec ed by law. This legal amewo k g ea ly diminishes conce ns abou possible
layo s o o ced obsolescence due o echnological ad ancemen s. Consequen ly,
al hough some eache s migh eel app ehensi e abou how a i icial in elligence
could ede ine hei oles, hese conce ns do no seem o signi ican ly a ec hei
o e all in en ion o adop new echnologies; hei employmen s a us is sa egua ded.
Addi ionally, he s abili y a o ded by hese posi ions may os e a p o essional en i-
onmen in which eache s can expe imen wi h inno a ions and na iga e pedagogi-
cal shi s wi hou ea o immedia e p o essional epe cussions. Such ce ain y e ec-
i ely mi iga es any anxie y oo ed in he idea ha GAI migh displace o d as ically
educe hei ole, which explains why his pa icula o m o anxie y does no ha e a
signi ican e ec on hei in en ion o use Cha GPT.
Fu he mo e, uni e si y eache s pe cei e hemsel es no only as echnically
capable o adap ing o and mas e ing new a i icial in elligence-based ools, bu also
as b inging unique human quali ies ha dis inguish hem om GAI (Chan & Tsi,
2024). Thei abili y o os e c ea i i y, demons a e empa hy, and engage in c i ical
hinking enables hem o p o ide sophis ica ed insigh , e hical judgmen , and pe -
sonalized guidance ha echnology alone canno eplica e. These dis inc ly human
a ibu es make hei ole in highe educa ion essen ial, ensu ing ha GAI unc ions
as a complemen a he han a eplacemen in academic and pedagogical con ex s
(Dwi edi e al., 2023).
The second objec i e aimed o analyze how e o expec ancy and pe o mance
expec ancy media e he ela ionship be ween he kinds o anxie y and beha io al
in en ion. To he bes o ou knowledge, hese media ion ela ions ha e no been
add essed in p e ious esea ch. Howe e , bo h e o expec ancy and pe o mance
expec ancy a e a iables speci ic o UTAUT and hei di ec e ec on bo h beha io-
al in en ion and use beha io ha e been widely alida ed (Fa ooq e al., 2017).
In his wo k, no media ion e ec was ound o anxie y ela ed o changes a ec -
ing he p o ession. Al hough uni e si y eache s may conside he e o expec ancy
o he pe o mance expec ancy, hese pe cep ions do no explain how p eoccupa-
ion wi h p o essional ans o ma ion a ec s (o no ) he in en ion o use Cha GPT.
These esul s sugges ha anxie y abou changes in he eaching p o ession is no a
de e mining ac o in he decision o use echnology such as Cha GPT. As wi h he
di ec ela ionship, i is expec ed ha con ex ual ac o s such as job secu i y and he
egula o y amewo k, as well as he in insic cha ac e is ic o uni e si y eache s o
be able o adap o change, will mean ha his ype o anxie y will no ha e an indi-
ec ela ionship wi h beha io al in en ion.
Rega ding anxie y abou eache s’ misuse o Cha GPT, as p e iously men ioned,
nega i ely and di ec ly in luences hei in en ion o use i . In addi ion, i uni e si y
eache s a e wo ied because hey belie e ha Cha GPT may gene a e e o s o
achie e poo esul s, hey a e mo e likely o pe cei e ha e icien ly mas e ing his
Educa ion and In o ma ion Technologies
ool equi es a lo o e o (e o expec ancy) and o hink ha i is no use ul in
hei eaching (pe o mance expec ancy), which will lowe hei in en ion o use i
(Gunasinghe & Nanayakka a, 2021). The e o e, bo h e o expec ancy and pe o -
mance expec ancy a e media o s in he ela ionship be ween eache misuse anxie y
and in en ion o use Cha GPT.
Finally, eache s’ anxie y ela ed o s uden misuse o Cha GPT, in addi ion o
ha ing a di ec and nega i e ela ionship wi h eache beha io al in en ion, indi-
ec ly a ec s eache in en ion o use h ough pe o mance expec ancy, bu no
h ough e o expec ancy. The e o e, his ype o anxie y also has an indi ec e ec
h ough pe o mance expec ancy. Tha is, he g ea e he eache s’ anxie y gene a ed
by he possibili y o misuse by s uden s, he lowe he expec a ion o good pe o -
mance wi h Cha GPT by eache s, and hus he lowe he in en ion o use i . Since
pe o mance expec ancy is one o he mos in luen ial ac o s in echnology adop-
ion acco ding o he UTAUT model (Fa ooq e al., 2017; Venka esh e al., 2003),
he educ ion o his pe cep ion leads o a lowe in e es in using he ool. Howe e ,
he e ec o his same ype o anxie y on in en ion o use he ool h ough pe cei ed
ease o use is i ele an , so e o expec ancy canno be conside ed a media ing a i-
able in his ela ionship.
5.1 Implica ions
The esul s o his s udy o e ele an implica ions o bo h heo e ical and p ac ical
aspec s. F om a heo e ical pe spec i e, his wo k explo es he adop ion o GAI in a
g oup ha has ecei ed limi ed esea ch a en ion: uni e si y eache s. Gi en he sig-
ni icance o his g oup in implemen ing new eaching ools and me hodologies, i is
c ucial o unde s and hei mo i a ions and in e es s ega ding he adop ion o GAI.
A salien conce n among uni e si y eache s is he po en ial implica ions o GAI
adop ion o he u u e o hei p o ession, i s misuse, and he subsequen impac on
s uden lea ning. This s udy add esses his conce n by examining he h ee ypes o
anxie y ha shape he adop ion o GAI in academic se ings. The indings o his
s udy suppo he no ion ha echnology- ela ed anxie y hinde s he in en ion o
adop and subsequen ly implemen GAI in uni e si y class ooms. Mo eo e , a sig-
ni ican heo e ical implica ion o his wo k is ha when examining he ole o anxi-
e y in echnology adop ion, i is essen ial o conside he concep in a mul i ace ed
manne , as anxie y can s em om di e se causes. As a icula ed in he pape , he
in luence o anxie y on echnology adop ion a ies ac oss di e en ypes. No ably,
he s udy unde sco es he no ion ha he impac o anxie y on echnology adop-
ion is ope a ing bo h di ec ly and indi ec ly h ough o he a iables, such as e o
expec ancy and pe o mance expec ancy. These esul s ein o ce he con ibu ions o
he UTAUT model, by showing how a ec i e ac o s can impac he expec a ion o
pe o mance o a g ea e ex en han he expec a ion o e o .
F om he poin o iew o p ac ical applica ion, signi ican implica ions can also be
d awn. Uni e si y eache s’ de elopmen p og ams should ocus on eaching he p ac i-
cal applica ions o GAI ools, which can educe usage anxie y, and how o use hem
e hically and esponsibly wi hou comp omising academic in eg i y (Yu, 2024). Such
Educa ion and In o ma ion Technologies
aining p og ams mus include s a egies o add ess anxie y s emming om conce ns
o e s uden s’ misuse o hese ools and hei po en ial e ec s on lea ning ou comes.
Fo ins ance, hese p og ams could demons a e how o c ea e and implemen s uden -
o ien ed codes o conduc . E e y aining ini ia i e should inco po a e a p ac ical com-
ponen , allowing uni e si y eache s o e lec on and implemen GAI ools in hei own
disciplines.
An analysis o he sociodemog aphic a iables e ealed no ewo hy di e ences in
he adop ion o GAI ools. The esul s indica e ha while age and wo k expe ience did
no signi ican ly in luence beha io al in en ion o use beha io , gende eme ged as a
signi ican ac o . Speci ically, emale eache s exhibi ed lowe le els o beha io al
in en ion compa ed o hei male coun e pa s. These di e ences sugges ha emale
eache s may expe ience unique ba ie s o conce ns ega ding he adop ion o GAI
echnologies. In ligh o hese indings, i is impe a i e ha educa ional guidance and
aining in e en ions be ailo ed o add ess hese gende -speci ic challenges. Ta ge ed
in e en ions could include dedica ed aining sessions, men o ship p og ams, and
esou ces ha ocus on bo h enhancing echnical p o iciency and mi iga ing anxie y
associa ed wi h he use o GAI ools. Such ailo ed suppo is likely o inc ease o e all
uni e si y eache s’ con idence and p omo e a mo e balanced and e ec i e in eg a ion
o hese eme ging echnologies in o he academic en i onmen .
Addi ionally, ini ia i es should be unde aken o encou age e lec ion on he app o-
p ia e use o GAI ools in he academic con ex . I is c ucial o he uni e si y commu-
ni y o be awa e o bo h he oppo uni ies and isks associa ed wi h hese echnologies.
Sha ing bes p ac ices, case s udies, and esea ch indings can accele a e he adop ion
and implemen a ion o GAI in highe educa ion (Bin-Nashwan e al., 2023). Rega d-
ing he isks, a ge ed ac ions should be di ec ed owa d uni e si y eache s who, due
o p io nega i e expe iences, a e eluc an o adop hese ools. Such eache s mus
be made awa e o he ull ange o unc ionali ies hese ools o e , so ha e en i hey
choose no o apply hem in hei cou ses, hey unde s and how o he s, including s u-
den s, migh u ilize hem (Hazzan-Bisha a e al., 2025).
Ins i u ional leade s should also p omo e collabo a ion and knowledge sha ing
among s akeholde s wi hin he GAI educa ional communi y (Jain & Raghu am, 2024).
Collabo a i e ini ia i es can os e inno a ion and d i e he de elopmen o ad anced
GAI solu ions ailo ed o he speci ic needs o academia (Zhang & Aslan, 2021). These
e o s will no only enhance he in eg a ion o GAI bu also ensu e ha i s implemen a-
ion aligns wi h he b oade objec i es o highe educa ion.
Finally, i is essen ial o es ablish a clea amewo k o ully le e age he oppo uni-
ies o e ed by GAI. Ins i u ions should de elop and dissemina e explici guidelines o
he use o GAI among membe s o he academic communi y, p o ide comp ehensi e
aining on hese guidelines, and ensu e hei adhe ence h ough consis en moni o ing
(Bae e al., 2024).
5.2 Limi a ions and u u e esea ch lines
This s udy p esen s limi a ions ha should be add essed in u u e esea ch.
Fi s , i adop s a c oss-sec ional design, which limi s he abili y o cap u e how
Educa ion and In o ma ion Technologies
pe cep ions o pe o mance expec ancy, e o expec ancy, and anxie y e ol e
o e ime. Fo ins ance, as eache s ecei e mo e aining and exposu e o GAI
ools, hei echnological li e acy is likely o imp o e, po en ially educing usage
anxie y and inc easing pe o mance expec ancy and e o expec ancy. This lon-
gi udinal s udy would p o ide a mo e dynamic unde s anding o hese ela ion-
ships and o e deepe insigh s in o how aining and expe ience shape beha io al
in en ion o adop GAI ools. Speci ically, his esea ch would p o ide insigh s
in o he long- e m e ec s o a ge ed in e en ions and he e olu ion o pe cep-
ions as eache s become mo e amilia wi h hese echnologies. Addi ionally, his
s udy could use a mixed-me hods design o assess bo h quan i a i e di e ences
and quali a i e pe cep ions, he eby p o iding a ge ed insigh s o he design o
specialized aining p og ams.
Addi ionally, he s udy ocuses exclusi ely on a sample o Spanish public uni-
e si y eache s, limi ing he gene alizabili y o he indings o o he cul u al and
ins i u ional con ex s. While he esul s p o ide aluable insigh s in o his speci ic
se ing, compa a i e s udies wi h samples om di e en coun ies and educa ional
sys ems a e needed o assess he uni e sali y o he iden i ied pa e ns and o
explo e cul u al nuances in he adop ion o GAI ools. Compa a i e s udies could
unco e how cul u al and o ganiza ional di e ences shape anxie y, pe o mance
expec ancy, e o expec ancy, and beha io al in en ion ega ding GAI adop ion.
Fo example, a c oss-cul u al s udy could be conduc ed in uni e si ies wi h e y
di e en egula o y and cul u al en i onmen s. In his sense, i could cla i y he
ela ionship be ween anxie y and he adop ion o Cha GPT and he pe cep ion
o job secu i y shown by he pa icipan s. This esea ch could be applied in pub-
lic and p i a e uni e si ies, o in uni e si ies in coun ies wi h di e en le els o
de elopmen , o be ween uni e si ies wi h di e en posi ions in academic ank-
ings (e.g., Shanghai).
In es iga ing he ole o ins i u ional policies on he adop ion o GAI ools is c i -
ical. Fu u e esea ch could examine how he cla i y, dissemina ion, and en o cemen
o uni e si y egula ions in luence eache s’ con idence and beha io ega ding GAI
use. In his sense, i would be use ul o ca y ou a compa a i e analysis o uni e si-
ies wi h di e en le els o policy cla i y, dissemina ion and en o cemen ega ding
he use o GAI. Such esea ch should examine how ins i u ional egula o y ma u i y
a ec s acul y con idence and usage pa e ns, po en ially highligh ing bes p ac ices
ha enhance adop ion a es ac oss di e se academic se ings. Addi ionally, in es i-
ga e how he b oade o ganiza ional cul u e and leade ship p ac ices wi hin uni e -
si ies in luence eache s’ anxie y and he adop ion o GAI ools. This s udy migh
ocus on how suppo i e leade ship and a cul u e o inno a ion can mi iga e esis -
ance and p omo e e ec i e echnology in eg a ion.
Uni e si y eache s’ conce ns abou he e hical implica ions o GAI usage
wa an u he explo a ion. Resea ch should examine how eache s’ e hical
app ehensions, such as ea s o academic dishones y o he e osion o academic
in eg i y, a ec he in eg a ion o hese ools in o hei eaching p ac ices. This
s udy could employ a mixed-me hods app oach o iden i y he speci ic e hical
dilemmas ha d i e uni e si y eache s’ anxie y and p opose amewo ks o
add essing hem.
Educa ion and In o ma ion Technologies
The eme gence o GAI ools aises impo an ques ions abou how hese echnolo-
gies a e ans o ming he eaching p o ession. Fu u e s udies should del e deepe in o
he e ol ing oles and esponsibili ies o eache s in esponse o hese dis up i e ech-
nologies, as well as how hese changes in luence p o essional iden i y and pedagogical
s a egies. Consequen ly, a mo e exhaus i e examina ion o he ela ionship be ween
his pa icula kind o anxie y and beha io al in en ion is impe a i e, pa icula ly
in ligh o he absence o subs an ial indings in his s udy. A comp ehensi e unde -
s anding o he mechanisms unde lying he di ec in luence o his kind o anxie y on
beha io al in en ion could po en ially e eal no el ac o s o media o s ha shape his
ela ionship.
Addi ionally, u u e esea ch could explo e whe he di e en ypes o uni e si y
eache s-such as hose wi h di e en a eas o expe ise o academic disciplines, hose
a di e en s ages o hei ca ee s, hose wi h di e en le els o expe ience wi h GAI
ools, o hose o di e en gende s-exhibi di e en le els o beha io al in en ion. In
pa icula , examining gende di e ences could p o ide aluable insigh s in o how pe -
cep ions, a i udes, o le els o anxie y owa d GAI ools may a y by gende . Unde -
s anding hese di e ences would allow o he de elopmen o mo e e ined and equi-
able s a egies o p omo e he esponsible and e ec i e in eg a ion o GAI ools ac oss
di e en segmen s o he academic communi y.
By add essing hese limi a ions and pu suing hese esea ch di ec ions, u u e s ud-
ies can p o ide a mo e comp ehensi e unde s anding o he complex in e play be ween
anxie y, pe cep ions o GAI ools, and beha io al in en ion, he eby in o ming mo e
e ec i e s a egies o hei in eg a ion in o highe educa ion.
6 Conclusions
This s udy examines how anxie y in luences uni e si y eache s’in en ions o adop
GAI ools like Cha GPT. By analyzing h ee dis inc ypes o anxie y—conce ns abou
p o essional change, wo ies abou s uden lea ning, and ea s o misusing Cha GPT—
he esea ch deepens he unde s anding o he psychological ba ie s o GAI adop ion
in highe educa ion. The indings o his s udy indica e ha eache s’ anxie y nega i ely
impac s beha io al in en ion, p ima ily by educing pe o mance and e o expec an-
cies, especially conce ning s uden misuse and eliance on inaccu a e GAI ou pu s. In
con as , eache s’ anxie y abou he impac o Cha GPT on he academic p o ession
did no signi ican ly a ec beha io al in en ion.
These esul s highligh he need o a comp ehensi e adop ion s a egy ha goes
beyond echnical aining. I is c ucial o add ess anxie y h ough e hical awa eness,
academic in eg i y ini ia i es, and clea demons a ions o he ool’s e ec i eness in
imp o ing pe o mance. The enhancemen o con idence in GAI ools, as well as he
p omo ion o hei esponsible and p oduc i e use, is only possible h ough he combi-
na ion o hese measu es.
Educa ion and In o ma ion Technologies
Appendix
Scales used
Va iable Desc ip ion
ANXP1 I am conce ned ha Cha GPT and o he a i icial in elligence sys ems may make me less use-
ul as a eache
ANXP2 I am a aid ha Cha GPT and o he a i icial in elligence sys ems will eplace eache s
ANXU1 I am a aid o using Cha GPT
ANXU2 I am a aid o misuse he in o ma ion I gene a e wi h Cha GPT
ANXU3 I am hesi an o use Cha GPT o ea o making mis akes ha I can’ co ec
ANXU4 I am in imida ed by using Cha GPT
ANXS1 I wo y ha my s uden s may use Cha GPT in hei assignmen s wi hou me being awa e o i
ANXS2 I ea ha my s uden s’lea ning will be o poo e quali y i hey use Cha GPT
ANXS3 I am conce ned ha my s uden s will pu less e o in o lea ning i hey use Cha GPT
BI1 I will con inue o use Cha GPT o he o eseeable u u e
BI2 I will ecommend Cha GPT o my pee s and iends
BI3 I ha e a posi i e pe cep ion o Cha GPT
BI4 I in end o use o con inue using Cha GPT o eaching pu poses
BI5 I in end o use o con inue o use Cha GPT in he esea ch se ing
EE1 I can easily in e ac wi h Cha GPT
EE2 I is easy o me o use Cha GPT
EE3 Cha GPT does no equi e much e o
EE4 I is easy o me o unde s and he di e en possibili ies o using Cha GPT
PE1 Cha GPT is use ul o my academic ac i i y
PE2 Cha GPT helps me o do my wo k be e
PE3 Cha GPT helps me o ge my wo k done as e
PE4 Cha GPT helps me o be mo e p oduc i e
UB F equency o use
Au ho con ibu ions Concep ualiza ion: Domingo Ve ano-Taco on e, Alicia Bolí a -C uz.
Da a cu a ion: Alicia Bolí a -C uz, Domingo Ve ano-Taco on e, Sil ia Sosa-Cab e a.
Fo mal analysis: Alicia Bolí a -C uz, Domingo Ve ano-Taco on e, Sil ia Sosa-Cab e a.
In es iga ion: Domingo Ve ano-Taco on e, Alicia Bolí a -C uz.
Me hodology: Sil ia Sosa-Cab e a, Alicia Bolí a -C uz.
W i ing – o iginal d a : Domingo Ve ano-Taco on e, Alicia Bolí a -C uz, Sil ia Sosa-Cab e a.
W i ing – e iew & edi ing: Domingo Ve ano-Taco on e, Alicia Bolí a -C uz, Sil ia Sosa-Cab e a.
Funding Open Access unding p o ided hanks o he CRUE-CSIC ag eemen wi h Sp inge Na u e.
This wo k did no ecei e any ex e nal unding o ins i u ional suppo .
Da a a ailabili y The da a used in his s udy a e a ailable upon eques om he co esponding au ho .
We a e commi ed o ensu ing anspa ency and acili a ing he ep oducibili y o ou esea ch. Resea ch-
e s in e es ed in accessing he da a used in his s udy may con ac he co esponding au ho ega ding
a ailabili y and access.
Educa ion and In o ma ion Technologies
Code a ailabili y No Applicable.
Decla a ions
Compe ing in e es s The au ho s decla e ha hey ha e no compe ing in e es s.
Open Access This a icle is licensed unde a C ea i e Commons A ibu ion 4.0 In e na ional License,
which pe mi s use, sha ing, adap a ion, dis ibu ion and ep oduc ion in any medium o o ma , as long
as you gi e app op ia e c edi o he o iginal au ho (s) and he sou ce, p o ide a link o he C ea i e
Commons licence, and indica e i changes we e made. The images o o he hi d pa y ma e ial in his
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use is no pe mi ed by s a u o y egula ion o exceeds he pe mi ed use, you will need o ob ain pe mis-
sion di ec ly om he copy igh holde . To iew a copy o his licence, isi h p://c ea i ecommons.o g/
licenses/by/4.0/.
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