Published Online:March 2026
Product Name:The IUP Journal of Information Technology
Product Type:Article
Product Code:IJIT010326
DOI:10.71329/IUPJIT/2026.22.1.7-36
Author Name:G Sunil Choudhary and G Yamuna
Availability:YES
Subject/Domain:Engineering
Download Format:PDF
Pages:7-36
The paper extends technology acceptance research by examining how psychological and social factors shape faculty members’ intention to adopt generative artificial intelligence (GenAI) ChatGPT in higher education. The data was collected from 342 professors at a public university and its affiliated colleges in Chennai, India. The proposed model integrates perceived usefulness (PU), perceived ease of use (PEOU), perceived trustworthiness (PT), technological self-efficacy (TSE), and social influence (SI), and it is tested using partial least squares structural equation modeling (PLS-SEM). The results reveal that PU directly influences behavioral intention (BI), while PEOU operates indirectly through PT and TSE. PT emerged as the strongest predictor, followed by TSE. SI positively moderates the relationship between PEOU and BI. These findings demonstrate that GenAI adoption among faculty is governed by a dual psychological mediation pathway through trust and self-efficacy rather than by direct functional appraisals alone. This constitutes a formal theoretical extension of the technology acceptance model (TAM) for generative AI contexts, repositioning trust as the primary mediating mechanism through which the faculty evaluate and commit to AI-supported teaching practice.
Generative artificial intelligence (GenAI) has begun to influence teaching and learning in higher education. ChatGPT and similar platforms are currently used to design lessons, generate course materials and support student learning, which is changing the traditional classroom dynamics (Mollick & Mollick, 2023).