SEApr 1

Harnessing Hype to Teach Empirical Thinking: An Experience With AI Coding Assistants

arXiv:2604.0111032.8
AI Analysis

This work addresses the problem of making empirical methods more accessible for software engineering students, though it is incremental as it applies an existing educational approach to a new topic.

The study tackled the challenge of teaching empirical thinking to software engineering students by using AI coding assistants as a hype-driven topic, resulting in increased student engagement and development of critical thinking skills through hands-on sessions and student-designed empirical studies.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes