Behavioural Intention in University Teachers' Adoption of Artificial IntelligenceA TAM-UTAUT Perspective from Shenyang, China
TL;DR
Behavioural intention is examined as the link between university teachers' and administrators' evaluations of AI and their subsequent use of it and the sequence from appraisal to intention, from intention to use, and from use to educational or administrative outcomes is clarified.
Abstract
Universities increasingly have access to artificial intelligence, but access alone says little about whether these tools become part of everyday academic work. This article examines behavioural intention as the link between university teachers' and administrators' evaluations of AI and their subsequent use of it. It brings the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Theory of Planned Behavior into conversation with research on AI literacy, perceived risk and organisational support. Performance expectancy, effort expectancy, social influence, AI literacy and risk perceptions are expected to shape intention, while facilitating conditions affect both intention and the likelihood that intended use becomes sustained practice. The article distinguishes between two possible consequences of adoption: changes in teaching quality and changes in management efficiency. Neither consequence can be inferred from usage alone; each depends on the task, the quality of human review and the institutional arrangements surrounding the tool. Against the policy and organisational background of Shenyang, the article sets out propositions and measurement priorities for a later empirical study. Its main contribution is to clarify the sequence from appraisal to intention, from intention to use, and from use to educational or administrative outcomes.