PromptTutor: Effects of an LLM-Based Chatbot on Learning Outcomes and Motivation in Flipped Classrooms
Yuhao Zhang, Eng Lieh Ouh, Adam Ho, Siaw Ling Lo, Kar Way Tan, Feng Vankee Lin · 2025
This study explores the integration of a Large Language Model (LLM) based chatbot, PromptTutor, into flipped classrooms (FC) for undergraduate Computer Science (CS) education. PromptTutor is designed to provide personalized, immediate feedback to support student learning in FC by incorporating reflective learning and scaffolding strategies. The traditional FC typically lacks this immediate feedback during the pre-class learning phase, risking decreased student motivation according to existing literature. This study examines if students improve in learning outcomes and motivation after using PromptTutor. Through a controlled crossover experiment with 50 students, the study demonstrates statistically significant improvements in students' quiz performance and motivation compared to traditional FC. Our work underscores the potential of LLM-based tools in addressing FC challenges, offering actionable insights for educators and institutional leaders in technology-enhanced learning environments.