AskNow: An LLM-powered Interactive System for Real-Time Question Answering in Large-Scale Classrooms

Abstract: In large-scale classrooms, students often struggle to ask questions due to limited instructor attention and social pressure. Based on findings from a formative study with 24 students and 12 instructors, we designed AskNow, an LLM-powered system that enables students to ask questions and receive real-time, context-aware responses grounded in the ongoing lecture and that allows instructors to view students' questions collectively. We deployed AskNow in three university computer science courses and tested with 117 students. To evaluate AskNow's responses, each instructor rated the perceived correctness and satisfaction of 100 randomly sampled AskNow-generated responses. In addition, we conducted interviews with 24 students and the three instructors to understand their experience with AskNow. We found that AskNow significantly reduced students' perceived time to resolve confusion. Instructors rated AskNow's responses as highly accurate and satisfactory. Instructor and student feedback provided insights into supporting real-time learning in large lecture settings.