Learning Satisfaction as a Key Mechanism in Higher Vocational Students’ Continuance Intention to Use Generative AI for Computer Course Learning

Learning Satisfaction and GAI Continuance Intention

DOI

10.2991/978-94-6239-766-8_43How to use a DOI?

Keywords

generative artificial intelligence; learning satisfaction; continuance intention; computer course learning; higher vocational education; computing education

Abstract

This study examines higher vocational students’ continuance intention to use generative artificial intelligence (GAI) in computer course learning. Drawing on the Technology Acceptance Model and continuance-use research, it tests whether perceived usefulness, perceived ease of use, and learning engagement affect continuance intention through learning satisfaction. Data from 320 students in Heilongjiang Province, China, were analyzed using structural equation modeling and bootstrap mediation analysis. The results show that perceived usefulness, perceived ease of use, and learning engagement significantly enhance learning satisfaction, which has the strongest direct effect on continuance intention and mediates all three antecedent effects. Perceived usefulness does not directly affect continuance intention, whereas perceived ease of use retains a small but significant direct effect. The findings suggest that continued GAI use depends on whether students’ perceptions and engagement are translated into satisfying, task-oriented learning experiences.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Jinhua Huang
AU  - Choat Inthawongse
AU  - Noppadol Amdee
PY  - 2026
DA  - 2026/09/04
TI  - Learning Satisfaction as a Key Mechanism in Higher Vocational Students’ Continuance Intention to Use Generative AI for Computer Course Learning
BT  - Proceedings of the 2026 6th International Conference on Education, Information Management and Service Science  (EIMSS 2026)
PB  - Atlantis Press
SP  - 406
EP  - 413
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6239-766-8_43
DO  - 10.2991/978-94-6239-766-8_43
ID  - Huang2026
ER  -