Reforming a Deep Learning Course for Data Science Majors: Project-Based Teaching and Generative Artificial Intelligence in an Application-Oriented University_Vol. 3 No. 5 (JHET 2026)_Journal of Higher Education Teaching (ISSN: 3005-5776)

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Reforming a Deep Learning Course for Data Science Majors: Project-Based Teaching and Generative Artificial Intelligence in an Application-Oriented University

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DOI: https://doi.org/10.62517/jhet.202615503

Author(s)

Zimeng Wang1, Junli Zhang2,*

Affiliation(s)

1Electronic Information Engineering, Xi'an University of Posts and Telecommunications, Xi'an, Shaanxi, China 2Xi'an Eurasia University, Xi'an, Shaanxi, China *Corresponding Author

Abstract

Deep learning courses are abstract in theory, long in engineering workflow, and fast in technological change. Organized in the conventional way of lectures, verification labs and a final exam, such a course rarely helps students build complete competence from problem definition to deployment. Project-based teaching is widely adopted, yet it often suffers from superficial tasks, thin process evidence, unclear boundaries for artificial intelligence (AI)-assisted work, and outcomes that are hard to accumulate. Taking the deep learning course for data science majors at Xi'an Eurasia University as the setting, this study brings generative AI into the instructional design and rebuilds the course along five lines: authentic project scenarios, rules for AI use, engineering workflow, learning evidence, and course resources. Projects are organized into four levels from reproducing basic models to transfer, real application and final presentation, each supported by evidence such as prompt records, AI use declarations, experiment logs, model cards and data cards. Several rounds of teaching suggest that students move into complex projects faster, instructors detect misunderstandings earlier, and academic integrity issues become checkable rather than judgemental. The approach offers a workable reference for reforming AI-related courses in the era of generative AI.

Keywords

Generative AI; Project-Based Teaching; Deep Learning Course; Curriculum Reform; Process Evaluation; Application-Oriented University

References

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