The advent of generative artificial intelligence (GenAI) is transforming the concept of the research-teaching nexus, and specifically its “research-based teaching” version, i.e. teaching through research, where teaching is carried out through involving students in doing research. Taking as its starting point the literature on the research-teaching nexus, this chapter shows that the democratization of generative AI requires a distinction to be drawn between GenAI-substitutable and GenAI-proof research tasks. The chapter examines the implications of this distinction for pedagogy and uses an example drawn from the field to illustrate the point. The results suggest directions for teaching delivery and knowledge assessment in research-based teaching built on GenAI-proof tasks. Further research is called for into reference principles for pedagogy in this field.

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Updating the Research-Teaching Nexus Framework in the Age of Generative AI: Prioritizing GenAI-Proof Research Tasks

  • Bérangère Laroudie,
  • Guy Tchibozo

摘要

The advent of generative artificial intelligence (GenAI) is transforming the concept of the research-teaching nexus, and specifically its “research-based teaching” version, i.e. teaching through research, where teaching is carried out through involving students in doing research. Taking as its starting point the literature on the research-teaching nexus, this chapter shows that the democratization of generative AI requires a distinction to be drawn between GenAI-substitutable and GenAI-proof research tasks. The chapter examines the implications of this distinction for pedagogy and uses an example drawn from the field to illustrate the point. The results suggest directions for teaching delivery and knowledge assessment in research-based teaching built on GenAI-proof tasks. Further research is called for into reference principles for pedagogy in this field.