Effects of
AI
chatbot‐supported cooperative flipped classroom on student collaboration, self‐regulated learning and academic performance: A mastery learning perspective
Kai Wang, Sihan Qin, Yue Shen, Jianwen Guo, Qianqian Ruan, Tingting Jia Abstract
Despite the increasing application of AI chatbots, few studies have examined the effectiveness of AI chatbot‐supported cooperative‐flipped classrooms in university teaching. Based on mastery learning theory, this study employed a quasi‑experimental design to examine how an AI chatbot‐supported cooperative‑flipped classroom influences students' collaboration, self‐regulated learning and academic performance, and whether students with different prior knowledge levels demonstrate distinct patterns under AI‐supported flipped learning. This study involved 154 junior students from a normal university, including an experimental group ( n = 87) and a control group ( n = 67), who were taught by the same instructor over an 11‐week period. Quantitative data from pretest and posttest scores and self‑report scales were analysed using t ‐tests and ANCOVA, whereas qualitative interview data from 10 experimental group students were analysed using Epistemic Network Analysis to compare collaboration and self‑regulated learning patterns across prior knowledge groups. The results showed that, compared to the control group, the experimental group demonstrated significantly higher posttest scores in collaboration, self‐regulated learning and academic performance. Within the experimental group, students with higher levels of AI chatbot interaction also significantly outperformed those with lower interaction levels in academic performance. Further, Epistemic Network Analysis results revealed that in AI chatbot‑supported flipped learning, students with lower prior knowledge exhibited denser collaboration networks, requiring more cognitive input and more frequent dimension switching to coordinate collaborative processes. In contrast, students with higher prior knowledge demonstrated stronger connections between the seeking, engaging and reflecting dimensions in their self‐regulated learning networks, reflecting more integrated self‐regulatory behaviour. This study provides empirical support for mastery learning theory and demonstrates the effectiveness of AI chatbot‐supported cooperative‐flipped classrooms, offering implications for differentiated teaching based on students' prior knowledge levels.
Flipped classrooms are associated with improvements in students' self‐regulated learning, motivation and academic performance compared with traditional instruction. Group cooperation during pre‐class activities can enhance peer interaction and collaboration, but is often constrained by uneven participation and limited instructional support. AI chatbots have been applied as learning assistants in higher education to provide feedback and learning resources, yet their role in structured pre‐class group cooperation remains insufficiently examined.Practitioner notes
What is already known about this topic
What this paper adds
AI chatbot‐supported cooperative‐flipped classrooms significantly enhance students' collaboration, self‐regulated learning and academic performance compared with traditional group‐based flipped learning. Epistemic network analysis shows that students with different levels of prior knowledge exhibit distinct collaboration and self‐regulation patterns when supported by an AI chatbot. The findings demonstrate that AI chatbots can function as mastery‐oriented scaffolds by guiding task division, clarifying learning goals and supporting feedback during pre‐class group discussions, thereby strengthening students' readiness for subsequent in‐class learning.