Instructional framework for using ChatGPT to aid interdisciplinary courses

Abstract

This paper explores using the AIGC tool ChatGPT to enhance interdisciplinary teaching in colleges and universities. Interdisciplinary courses, crucial for nurturing well-rounded talents, face challenges such as teachers' limited interdisciplinary knowledge, outdated teaching resources, and students' difficulties grasping complex concepts. ChatGPT offers extensive knowledge, instant response, and personalized learning to address these issues, supporting teachers with interdisciplinary teaching resources, instructional design, and assessment tools while providing students with customized learning materials. The proposed Interdisciplinary Practice Teaching Solution, comprising four core modules, facilitates the organic integration of interdisciplinary learning. A practical project, "Portfolio Analysis of Stock Funds," is used as a case study to demonstrate ChatGPT-aided interdisciplinary teaching. It showcases its effectiveness in cultivating students' abilities to deconstruct projects, clarify concepts, provide targeted hints, and critically validate and integrate projects. Experimental data confirm the framework's excellent performance across various indicators.

Ähnliche Arbeiten