Generative Artificial Intelligence Empowering Inquiry-Based Learning: Strategy and Challenges

Abstract

This paper explores the potential and challenges of generative artificial intelligence in empowering inquiry-based learning. Generative artificial intelligence can build personalized learning resources, promote collaborative learning, conduct learning evaluation and feedback, and establish a human-computer collaborative inquiry-based learning model. However, we should also be vigilant against drawbacks such as over-reliance, information bias, academic misconduct, and lack of deep learning. To meet the challenges, this paper proposes strategies such as including content that generative artificial intelligence cannot complete, strengthening process evaluation, formulating clear guidelines for the use of generative artificial intelligence, and improving students' understanding of generative artificial intelligence tools to promote the effective implementation of inquiry-based learning.