AI-Supported Flipped Classroom in Teaching Business Mathematics: A Classroom Action Research - Tarwiyah Tarwiyah; Anggono Anggono; Noppakao Naphatthalung; Ahmad Saputra; Ari Irawan (ITScience (Information Technology and Science), 2026)
Student learning outcomes in the Business and Economic Mathematics course at Universitas IBBI have shown a declining trend. Interviews revealed that lecturers with monodisciplinary backgrounds face difficulties in integrating mathematical models into economic and business contexts. To address these two interrelated problems, this study aims to improve student learning outcomes by implementing an AI-based flipped classroom. This study employed Classroom Action Research (CAR) involving 28 first-semester accounting students at Universitas IBBI. Data were collected through essay tests that had been validated and reliable, with items discriminating between groups and with difficulty levels appropriate for the groups. Subsequently, the data were analysed using descriptive statistics. The implementation of an AI-based flipped classroom improved student learning outcomes. The average score in Cycle I reached the success indicator and increased further in Cycle II. In addition, students became more capable of solving non-linear equations and interpreting results in economic contexts. This improvement was attributed to guidance in formulating prompts, which enhanced student interaction with ChatGPT. The implementation of an AI-supported flipped classroom effectively improves student learning outcomes while bridging the interdisciplinary gap between mathematical concepts and economic applications. However, the effectiveness of this model depends on students’ AI literacy and consistent access to the learning management system. Future research should employ quasi-experimental methods with larger samples and ensure adequate technical support.