Problem
Research questions and friction points this paper is trying to address.
empirical thinking
software engineering education
hypothesis-driven inquiry
student engagement
AI coding assistants
Harnessing Hype to Teach Empirical Thinking: An Experience With AI Coding Assistants
🤖 AI Summary
This study addresses the persistent challenge in software engineering education wherein students often struggle to grasp empirical methods and hypothesis-driven research thinking under traditional theoretical instruction, resulting in low engagement and motivation. To counter this, the authors propose an innovative one-semester seminar course centered on popular AI programming assistants, integrating authentic development tasks with inquiry-based learning to guide students in conducting small-scale empirical studies. Leveraging AI tools, experimental design, classroom observations, and questionnaire surveys, the course demonstrably enhanced student engagement and critical thinking. Participants not only proactively questioned the limitations of AI tools but also effectively developed the empirical research competencies necessary to evaluate claims about emerging technologies.
📝 Abstract
Software engineering students often struggle to appreciate empirical methods and hypothesis-driven inquiry, especially when taught in theoretical terms. This experience report explores whether grounding empirical learning in hype-driven technologies can make these concepts more accessible and engaging. We conducted a one-semester seminar framed around the currently popular topic of AI coding assistants, which attracted unusually high student interest. The course combined hands-on sessions using AI coding assistants with small, student-designed empirical studies.
Classroom observations and survey responses suggest that the hype topic sparked curiosity and critical thinking. Students engaged with the AI coding assistants while questioning their limitations -- developing the kind of empirical thinking needed to assess claims about emerging technologies. Key lessons: (1) Hype-driven topics can lower barriers to abstract concepts like empirical research; (2) authentic hands-on development tasks combined with ownership of inquiry foster critical engagement; and (3) a single seminar can effectively teach both technical and research skills.
Innovation
Methods, ideas, or system contributions that make the work stand out.
AI coding assistants
empirical thinking
hype-driven learning
student-designed studies
critical engagement
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