The impact of coercive, normative, and mimetic Stress on Chinese teachers' continuance intention to use generative AI: An integrated perspective of the Expectation-Confirmation Model and Institutional Theory

TL;DR

This study explores how institutional pressures and individual evaluations influence Chinese teachers' continued use of generative AI, highlighting the roles of confirmation, usefulness, satisfaction, and institutional influences.

Contribution

It integrates the Expectation-Confirmation Model with Institutional Theory to analyze factors affecting teachers' sustained AI use, combining quantitative and qualitative methods.

Findings

Confirmation, usefulness, and satisfaction significantly influence continuance intention.

Institutional pressures (coercive, normative, mimetic) also impact ongoing AI use.

Teachers pragmatically use AI for tasks but remain cautious about content reliability.

Abstract

This study investigates Chinese teachers' continuance intention to use generative artificial intelligence (AI) by integrating the Expectation-Confirmation Model with Institutional Theory. A sequential explanatory mixed-methods design was employed. Questionnaire data from 437 teachers were analysed using structural equation modelling, followed by semi-structured interviews with 15 teachers to further interpret the findings. The results indicate that confirmation, perceived usefulness, and satisfaction play important roles in shaping teachers' continuance intention, while institutional pressures, including coercive, normative, and mimetic influences, also contribute to continued use. Qualitative findings further reveal that teachers often use generative AI pragmatically to support tasks such as lesson preparation and idea generation, while simultaneously exercising caution and critically evaluating the reliability of AI-generated content. These findings highlight the combined influence of individual evaluations and institutional contexts on teachers' sustained engagement with generative AI in education.