Enhancing student engagement and learning outcomes in higher education through AI-supported flipped classrooms: A mixed-methods study

Cam Ai Tran (), Hung Tran Van (), Ha Thu Thi Nguyen (), Phuong Ba Le () and Trung Tran ()

Edelweiss Applied Science and Technology, 2025, vol. 9, issue 8, 913-924

Abstract: The integration of Artificial Intelligence (AI) in education has opened new opportunities for enhancing teaching models, notably the flipped classroom (FC). This study investigates the impact of an AI-supported flipped classroom model on student engagement and learning outcomes among university students in Vietnam. A mixed-methods approach was adopted, in which quantitative data were collected through pre- and post-tests, and qualitative insights were obtained via in-depth interviews. The AI tools used included automated video summarization, intelligent quiz generation, and personalized feedback systems integrated into the learning management system (LMS). Quantitative results from 210 undergraduate students revealed statistically significant improvements in academic performance and learner satisfaction. Specifically, the experimental group’s post-test scores improved by an average of 2.1 points, compared to a 1.2-point improvement in the control group (p < .001), and emotional engagement increased by 16% over baseline. Thematic analysis of qualitative data highlighted increased motivation, self-regulated learning, and positive attitudes toward AI-enhanced instruction. The study concludes that the integration of AI in FC models fosters active learning, autonomy, and deeper engagement, contributing to improved educational effectiveness in higher education.

Keywords: Artificial intelligence; Flipped classroom; Higher education; Personalized learning; Student engagement; Vietnam. (search for similar items in EconPapers)
Date: 2025
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