The Effectiveness of a Generative AI-Based Literature Module on Motivation and Self-Efficacy among Higher Vocational Students: A Quasi-Experimental Study

Shenlong Tang

Education Insights, 2025, vol. 2, issue 9, 67-73

Abstract: This study focuses on applying generative AI technology in literature teaching in higher vocational colleges. It aims to explore its impact on students' motivation and self-efficacy. Using a quasi-experimental research method, 120 students from higher vocational colleges participated in the study. The experimental group received instruction through a generative AI-based module, while the control group followed a traditional teaching model for 10 weeks. Data analysis showed that the experimental group achieved significantly greater improvements in motivation and self-efficacy than the control group (p < 0.05), and also outperformed their own pretest results (p < 0.05). These findings indicate that a literature module based on generative AI can effectively stimulate the motivation of higher vocational students and enhance their self-efficacy, providing new ideas and a practical basis for reforming literature teaching in higher vocational colleges.

Keywords: generative AI; literature module; higher vocational students; motivation; self-efficacy; quasi-experimental study (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:axf:eiaaaa:v:2:y:2025:i:9:p:67-73

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