TY - JOUR
T1 - Understanding students’ adoption of the ChatGPT chatbot in higher education
T2 - the role of anthropomorphism, trust, design novelty and institutional policy
AU - Polyportis, Athanasios
AU - Pahos, Nikolaos
N1 - Publisher Copyright:
© 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
PY - 2024/2/16
Y1 - 2024/2/16
N2 - The present research aims to highlight the underlying factors that drive students’ adoption of the ChatGPT chatbot in higher education. This study extends the meta-UTAUT framework by including additional exogenous factors of anthropomorphism, trust, design novelty, and institutional policy. Empirical examination with Structural Equation Modelling among 355 students in Dutch higher education institutions revealed attitude and behavioural intention as significant positive predictors of students’ ChatGPT use behaviour. Institutional policy negatively moderated the effect of behavioural intention on use behaviour. Behavioural intention was significantly and positively influenced by attitude, performance expectancy, social influence, and facilitating conditions. Anthropomorphism, design novelty, trust, performance expectancy, and effort expectancy were unveiled as significant positive antecedents of attitude. The central theoretical contributions of this research include investigating students’ use behaviour instead of behavioural intention, establishing attitude as a core construct, underlining additional antecedents of attitude, and highlighting the importance of institutional policy. The present study contributes to prior research on technology adoption, especially in the area of artificial intelligence in education. The findings yield valuable insights for chatbot designers, product managers, and higher education policy writers.
AB - The present research aims to highlight the underlying factors that drive students’ adoption of the ChatGPT chatbot in higher education. This study extends the meta-UTAUT framework by including additional exogenous factors of anthropomorphism, trust, design novelty, and institutional policy. Empirical examination with Structural Equation Modelling among 355 students in Dutch higher education institutions revealed attitude and behavioural intention as significant positive predictors of students’ ChatGPT use behaviour. Institutional policy negatively moderated the effect of behavioural intention on use behaviour. Behavioural intention was significantly and positively influenced by attitude, performance expectancy, social influence, and facilitating conditions. Anthropomorphism, design novelty, trust, performance expectancy, and effort expectancy were unveiled as significant positive antecedents of attitude. The central theoretical contributions of this research include investigating students’ use behaviour instead of behavioural intention, establishing attitude as a core construct, underlining additional antecedents of attitude, and highlighting the importance of institutional policy. The present study contributes to prior research on technology adoption, especially in the area of artificial intelligence in education. The findings yield valuable insights for chatbot designers, product managers, and higher education policy writers.
UR - http://www.scopus.com/inward/record.url?scp=85185683835&partnerID=8YFLogxK
U2 - 10.1080/0144929X.2024.2317364
DO - 10.1080/0144929X.2024.2317364
M3 - Article
AN - SCOPUS:85185683835
SN - 0144-929X
JO - Behaviour and Information Technology
JF - Behaviour and Information Technology
ER -