Factors affecting ChatGPT adoption among Bangladeshi university students with the moderating role of social influence
The integration of artificial intelligence (AI) into classrooms has revolutionized academic learning, presenting both opportunities and obstacles for learners’ advancement. The study aims to explore the factors of Extended technology acceptance model (TAM) by adding external variables such as information quality (IFQ), interaction quality (ITQ), and system quality (SQ) from DeLone & McLean’s theory. The data were collected from university students, and the analysis was conducted using partial least squares structural equation modeling (PLS-SEM). The result of the study shows that IFQ and ITQ have a positive influence on perceived usefulness (PU) and perceived ease of use (PEU), respectively. Additionally, PU and PEU are positively related. Moreover, the moderating role of social influence (SI) is true in this study. Theoretically, the study integrates the extended TAM model. Our study was able to contribute to our existing knowledge of the primary antecedents of the TAM model by integrating DeLone & McLean’s theory to understand the attitude (ATT) of students toward ChatGPT in the case of Bangladesh. The research can be an insightful direction for academicians, marketers, and educators who want to capitalize on ChatGPT and promote the usage of AI among students for their productive learning.
Authors
- Mohammad Abdullah Al Mamun (ORCID: https://orcid.org/0000-0003-4414-7277)
- Kazi Omar Siddiqi (ORCID: https://orcid.org/0009-0001-5156-6405)
- Tipon Tanchangya (ORCID: https://orcid.org/0009-0009-2365-4959)
- Kamron Naher
- Sagata Chakma
- Farzana Rashid
- Umme Hany Arju
- Sahin Alam
Institutions
- North China University of Water Resources and Electric Power (CN)
- Uttara University (BD)
- Green University of Bangladesh (BD)
- Comilla University (BD)
- Presidency University (BD)
- University of Chittagong (BD)
- University of Rajshahi (BD)
Publication Details
- Journal
- Discover Education
- Published
- 2026-09-24
- DOI
- https://doi.org/10.1007/s44217-026-02075-8
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00