2025/06/22 by Neha Rani, Rani, Neha, Majumder, Sharan +4
Computer Science · #Artificial Intelligence (cs.AI) #Computers and Society (cs.CY) #Emerging Technologies (cs.ET) #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Online Learning and Analytics
paper · pdf · doi:10.48550/arxiv.2506.18941
openalex publication_date 2025/06/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Lucrative career prospects and creative opportunities often attract students to enroll in computer science majors and pursue advanced studies in the field. Consequently, there has been a significant surge in enrollment in computer science courses, resulting in large class sizes that can range from hundreds to even thousands of students. A common challenge in such large classrooms is the lack of engagement between students and both the instructor and the learning material. However, with advancements in technology and improvements in large language models (LLMs), there is a considerable opportunity to utilize LLM-based AI models, such as conversational artificial intelligence (CAI), to enhance student engagement with learning content in large classes. To explore the potential of CAI to support engagement, especially with learning content, we designed an activity in a software Engineering course (with a large class size) where students used CAI for an in-class activity. We conducted a within-subject investigation in a large classroom at a US university where we compared student engagement during an in-class activity that used CAI tool vs. one without CAI tool. The CAI tool we used was ChatGPT due to its widespread popularity and familiarity. Our results indicate that CAI (ChatGPT) has the potential to support engagement with learning content during in-class activities, especially in large class sizes. We further discuss the implications of our findings.