Nexus between generative AI engagement, quality and expectation formation: an application of expectation–confirmation theory
Open accessAbstract
Purpose: Generative Artificial Intelligence (Gen-AI) has provided new opportunities and challenges in using educational environments for students’ interaction and knowledge acquisition. Based on the expectation–confirmation theory, this paper aims to investigate the effect of different constructs associated with Gen-AI on engagement, satisfaction and word-of-mouth. Design/methodology/approach: We collected data from 508 students in the UK using Qualtrics, a prominent online data collection platform. The conceptual framework was analysed through structural equation modelling. Findings: The findings show that Gen-AI expectation formation and Gen-AI quality help to boost Gen-AI engagement. Further, we found that active engagement positively affects Gen-AI satisfaction and positive word of mouth. The mediating role of Gen-AI expectation confirmation between engagement and the two outcomes, satisfaction and positive word of mouth, was also confirmed. The moderating role of cognitive processing in the relationship between Gen-AI quality and engagement was found. Originality/value: This paper extends the Expectation-Confirmation Theory on how Gen-AI can enhance students’ engagement and satisfaction. Suggestions for future research are derived to advance beyond the confines of the current study and to capture the development in the use of AI in education.
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Most research on GenAI use in educational settings has revealed that students who found it to be useful or helpful were more satisfied with the tool.
“Most research on GenAI use in educational settings has revealed that students who found it to be useful or helpful were more satisfied with the tool”
From Exploring the Role of Generative AI as a Research Assistant in Undergraduate Sociology Research Methods (2026) · cites this paper as Nguyen et al., 2025
Prior research has explored how students' initial expectations of GenAI influence later evaluations and use patterns.
“Prior research has explored how students' initial expectations of GenAI influence later evaluations and use patterns”
From Exploring the Role of Generative AI as a Research Assistant in Undergraduate Sociology Research Methods (2026) · cites this paper as Nguyen et al., 2025
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- Authors
- Nguyen, M., Mehrotra, A., Malik, A., & Pandey, R.
- Affiliations
- Jaipuria Institute of Management (IN)
- UNSW Canberra (AU)
- IMS Ghaziabad (IN)
- Corresponding author
- Mehrotra, Ankit
- Venue
- Journal of Enterprise Information Management
- Publisher
- Emerald
- Published
- 2025-03-04
- Volume
- 38
- Issue
- 3
- Pages
- 798-820
- ISSN
- 1741-0398 (ISSN-L)
- 1758-7409
- OpenAlex
- W4408138651
- Cited by
- 16
- References
- 89
- Citations by year
- 2026: 10 · 2025: 6
- FWCI
- 16.64
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- Locations
- Journal of Enterprise Information Management (publishedVersion)
- Griffith Research Online (submittedVersion, other-oa)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Keywords
- generative AI, artificial intelligence in education, student engagement, expectations formation, expectation confirmation theory, student satisfaction, word of mouth, cognitive processes, technology acceptance
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