Generative Artificial Intelligence Affordances for Learning Satisfaction in higher education

Authors

Wahid Hamad, School of Accounting, Information Systems and Supply Chain, RMIT University, Melbourne, AustraliaFollow
Hepu Deng, School of Accounting, Information Systems and Supply Chain, RMIT University, Melbourne, AustraliaFollow
Mohammad Hossain, School of Accounting, Information Systems and Supply Chain, RMIT University, Melbourne, AustraliaFollow

Abstract

The rapid development of generative artificial intelligence (GenAI) is fundamentally transforming teaching and learning in higher education. How GenAI use affects learning satisfaction from the perspective of technology affordances, however, remains unclear. This study investigates the affordances of GenAI in influencing learning satisfaction in higher education. Drawing on the technology affordance theory and the technology acceptance model, this study provides a structured approach to understanding how GenAI use fulfils learners’ psychological needs for autonomy, competence, and relatedness, thereby influencing learning satisfaction. By examining these aspects, the study advances understanding of GenAI’s role in teaching and learning and lays the groundwork for future empirical validation. Such insights equip stakeholders, including universities, policymakers, and educators, to leverage GenAI in enhancing learning satisfaction.

Recommended Citation

Hamad, Wahid; Deng, Hepu; and Hossain, Mohammad, "Generative Artificial Intelligence Affordances for Learning Satisfaction in higher education" (2025). ACIS 2025 Proceedings. 102.
https://aisel.aisnet.org/acis2025/102