Artificial intelligence-supported flipped learning in information technology education: quasi-experimental evidence on programming performance, learning autonomy, reflective learning, and digital competence

A quasi-experimental study investigated the impact of lecturer-guided, AI-supported flipped learning in undergraduate Information Technology programming education. The research involved 120 students, comparing an AI-integrated flipped learning approach (n=60) with a traditional flipped classroom (n=60). The AI integration involved orchestrating multiple AI tools across pre-class, in-class, and post-class activities, emphasizing continued lecturer guidance, student reasoning, and responsible AI use.

Why it matters

This research provides empirical insights into integrating Artificial Intelligence tools within established educational frameworks, specifically flipped learning. It offers a structured approach to leveraging AI in technical education while maintaining critical human oversight and promoting responsible usage. The findings can inform strategic decisions regarding technology adoption, curriculum development, and pedagogical innovation in higher education and professional training.

Key insights

• The study focused on the pedagogical integration of multiple AI tools within a flipped learning framework in IT programming education.
• AI tools were orchestrated across various learning stages: pre-class preparation, in-class practice, and post-class reflection.
• A core tenet of the AI integration was the maintenance of lecturer guidance, promotion of student reasoning, and emphasis on responsible AI use.
• The methodology employed a classroom-based non-equivalent groups quasi-experimental design.
• The study involved 120 undergraduate Information Technology students in a Programming Techniques course.
• One group experienced lecturer-guided AI-supported flipped learning, while the control group used a traditional flipped classroom without planned AI support.

Source

Frontiers in Education — https://www.frontiersin.org/articles/10.3389/feduc.2026.1907387