Empowering learners with AI-generated content for programming learning and computational thinking: The lens of extended effective use theory

IF 5.1 2区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Journal of Computer Assisted Learning Pub Date : 2024-05-08 DOI:10.1111/jcal.12996

Shang Shanshan, Geng Sen

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引用次数: 0

Abstract

Background

Artificial intelligence–generated content (AIGC) has stepped into the spotlight with the emergence of ChatGPT, making effective use of AIGC for education a hot topic.

Objectives

This study seeks to explore the effectiveness of integrating AIGC into programming learning through debugging. First, the study presents three levels of AIGC integration based on varying levels of abstraction. Then, drawing on extended effective use theory, the study proposes the underlying mechanism of how AIGC integration impacts programming learning performance and computational thinking.

Methods

Three debugging interfaces integrated with AIGC by ChatGPT were developed for this study according to three levels of AIGC integration design. The study conducts a between-subject experiment with one control group and three experimental groups. Analysis of covariance and a structural equation model are employed to examine the effects.

Results and Conclusions

The results show that the second and third levels of abstraction in AIGC integration yield better learning performance and computational thinking, but the first level shows no difference compared to traditional debugging. The underlying mechanism suggests that the second and third levels of abstraction promote transparent interaction, which enhances representational fidelity and consequently impacts learning performance and computational thinking, as evidenced in test of the mechanism. Moreover, the study finds that learning fidelity weakens the effect of transparent interaction on representational fidelity. Our research offers valuable theoretical and practical insights.

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利用人工智能生成的内容增强学习者的编程学习和计算思维能力：扩展有效使用理论的视角

随着 ChatGPT 的出现，人工智能生成的内容（AIGC）成为人们关注的焦点，有效利用 AIGC 进行教育也成为热门话题。本研究旨在探索通过调试将 AIGC 融入编程学习的有效性。首先，本研究根据不同的抽象程度提出了三个层次的 AIGC 集成。根据 AIGC 集成设计的三个层次，本研究开发了三种通过 ChatGPT 与 AIGC 集成的调试界面。研究采用了一个对照组和三个实验组的主体间实验。结果表明，AIGC 整合中的第二和第三抽象层次能产生更好的学习成绩和计算思维，但第一层次与传统调试相比没有差异。其基本机制表明，第二和第三层抽象促进了透明交互，从而提高了表征保真度，进而影响了学习成绩和计算思维，这在机制测试中得到了证明。此外，研究还发现，学习保真度会削弱透明互动对表征保真度的影响。我们的研究提供了宝贵的理论和实践启示。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Computer Assisted Learning EDUCATION & EDUCATIONAL RESEARCH-

CiteScore

9.70

自引率

6.00%

发文量

116

期刊介绍： The Journal of Computer Assisted Learning is an international peer-reviewed journal which covers the whole range of uses of information and communication technology to support learning and knowledge exchange. It aims to provide a medium for communication among researchers as well as a channel linking researchers, practitioners, and policy makers. JCAL is also a rich source of material for master and PhD students in areas such as educational psychology, the learning sciences, instructional technology, instructional design, collaborative learning, intelligent learning systems, learning analytics, open, distance and networked learning, and educational evaluation and assessment. This is the case for formal (e.g., schools), non-formal (e.g., workplace learning) and informal learning (e.g., museums and libraries) situations and environments. Volumes often include one Special Issue which these provides readers with a broad and in-depth perspective on a specific topic. First published in 1985, JCAL continues to have the aim of making the outcomes of contemporary research and experience accessible. During this period there have been major technological advances offering new opportunities and approaches in the use of a wide range of technologies to support learning and knowledge transfer more generally. There is currently much emphasis on the use of network functionality and the challenges its appropriate uses pose to teachers/tutors working with students locally and at a distance. JCAL welcomes: -Empirical reports, single studies or programmatic series of studies on the use of computers and information technologies in learning and assessment -Critical and original meta-reviews of literature on the use of computers for learning -Empirical studies on the design and development of innovative technology-based systems for learning -Conceptual articles on issues relating to the Aims and Scope