Harnessing Hype to Teach Empirical Thinking: An Experience With AI Coding Assistants
arXiv:2604.01110v1 Announce Type: new 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
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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.
Comments: Accepted to FSE'26 (Education Track)
Subjects:
Software Engineering (cs.SE)
Cite as: arXiv:2604.01110 [cs.SE]
(or arXiv:2604.01110v1 [cs.SE] for this version)
https://doi.org/10.48550/arXiv.2604.01110
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Marvin Wyrich [view email] [v1] Wed, 1 Apr 2026 16:36:13 UTC (3,636 KB)
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