ChatGPT from the Perspective of Computational Education: Connotation, Theme, Reflection, and Challenge

doi:10.16382/j.cnki.1000-5560.2023.07.009

Abstract

Abstract:

The advancement of artificial intelligence technology, represented by ChatGPT, has driven the transformation and upgrading of data-intensive paradigms in the era of computational education, and pushed computational education towards a critical period of development. This article first explores the value connotation of the generative artificial intelligence model represented by ChatGPT, in order to reveal the essence of promoting the upgrading of computational education paradigm through the advancement of artificial intelligence. Secondly, we explore the emerging educational research themes of teacher-student-machine knowledge generation through social network analysis and data mining, and analyze the multi-agent research of teacher student machine in the school field from four aspects: technological breakthroughs, student learning, teacher teaching, and school education based on the core domain relationship graph to jointly promote the in-depth development of computational education research, which outlines a diversified research landscape of human-machine integration driven by strong algorithmic computing power in computational education iterations. We further reflect on ChatGPT’s educational application as a tool rather than the ultimate goal, that is, ChatGPT serves as a technical means to assist writing rather than a responsible subject, as an enhancement and supplement to teaching rather than replacing the role of a teacher, and it is required to cooperate with assisting students in learning and not become overly dependent. Finally, we explore the key challenges that ChatGPT brings to the development of computational education from the perspectives of theoretical construction and decision-making empowerment, namely exploring the basic theoretical construction based on educational computing, promoting the evolution of structural rules in computational education, practicing the environmental construction and application practice of computational education, enhancing teachers’ abilities to achieve educational orientation in educational computing, and preventing privacy and bias risks of intelligent application data.

Key words: computational education, artificial intelligence, ChatGPT, education big data, machine learning, data mining, higher order thinking

Yonghe Zheng, Danhua Zhou, Yonghe Zhang, Xuewei Tian, Jingying Wang, Yi Zheng. ChatGPT from the Perspective of Computational Education: Connotation, Theme, Reflection, and Challenge[J]. Journal of East China Normal University(Educational Sciences), 2023, 41(7): 91-102.

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