Research on the reconstruction and practice path of big data course teaching mode driven by generative artificial intelligence technology
Hao Sun
Communication University of China, Nanjing
DOI: https://doi.org/10.59429/esta.v13i1.13384
Keywords: generative AI; big data course; teaching model reconstruction; practical path; human-machine collaboration
Abstract
This paper explores the pedagogical transformation of big data courses through generative AI, first examining traditional teaching challenges: content-industry mismatch, inadequate alignment between practice and real-world scenarios, and limitations in instructional implementation and evaluation systems. It then proposes a restructuring framework: clarifying the division of responsibilities between human and machine collaboration, developing a dynamically evolving curriculum system based on knowledge progression, and implementing precision teaching with multidimensional assessment through student analytics. Finally, case studies from Beijing No.11 School and Khan Academy demonstrate generative AI applications in data tracking, knowledge delivery, and personalized instruction, offering actionable insights for advancing big data course reform.
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