比较教师手动反馈与 ChatGPT 智能反馈对中国高校协作编程的影响

IF 2.9 3区教育学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

IEEE Transactions on Learning Technologies Pub Date : 2024-10-25 DOI:10.1109/TLT.2024.3486749

Fan Ouyang;Mingyue Guo;Ning Zhang;Xianping Bai;Pengcheng Jiao

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引用次数: 0

摘要

随着大型语言模型领域的快速发展，人工通用智能（AGI）越来越受到全球的关注。由于具有类似人类的认知能力，AGI 系统在帮助教师在整个教学过程中为学生提供详细、全面和个性化的反馈方面具有巨大潜力。ChatGPT 作为 AGI 系统的初级版本，具有改善编程教育的潜力。在编程过程中，学生往往在编写代码和调试错误时遇到困难，而 ChatGPT 可以提供智能反馈，支持学生的编程学习过程。本研究利用 ChatGPT 生成的智能反馈来促进学生小组之间的协作编程，并进一步比较了 ChatGPT 与教师手动反馈对编程的影响。本研究采用了多种学习分析方法来分析学生的计算机编程表现、认知和调节话语以及编程行为。结果表明，在教师手动反馈和 ChatGPT 智能反馈的情况下，学生在编程知识掌握和小组编程产品质量方面没有发现实质性差异。ChatGPT 智能反馈促进了学生以规则为导向的协作编程，而教师手动反馈则促进了编程过程中以认知为导向的协作讨论。与教师手动反馈相比，学生认为 ChatGPT 智能反馈有更明显的优点和缺点。根据研究结果，本研究为加强 ChatGPT 与高等教育编程教育的整合提供了教学和分析见解。这项研究还为促进学生、教师和 AGI 系统之间的协作学习体验提供了新的视角。

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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Comparing the Effects of Instructor Manual Feedback and ChatGPT Intelligent Feedback on Collaborative Programming in China's Higher Education

Artificial general intelligence (AGI) has gained increasing global attention as the field of large language models undergoes rapid development. Due to its human-like cognitive abilities, the AGI system has great potential to help instructors provide detailed, comprehensive, and individualized feedback to students throughout the educational process. ChatGPT, as a preliminary version of the AGI system, has the potential to improve programming education. In programming, students often have difficulties in writing codes and debugging errors, whereas ChatGPT can provide intelligent feedback to support students’ programming learning process. This research implemented intelligent feedback generated by ChatGPT to facilitate collaborative programming among student groups and further compared the effects of ChatGPT with instructors’ manual feedback on programming. This research employed a variety of learning analytics methods to analyze students’ computer programming performances, cognitive and regulation discourses, and programming behaviors. Results indicated that no substantial differences were identified in students’ programming knowledge acquisition and group-level programming product quality when both instructor manual feedback and ChatGPT intelligent feedback were provided. ChatGPT intelligent feedback facilitated students’ regulation-oriented collaborative programming, while instructor manual feedback facilitated cognition-oriented collaborative discussions during programming. Compared to the instructor manual feedback, ChatGPT intelligent feedback was perceived by students as having more obvious strengths as well as weaknesses. Drawing from the results, this research offered pedagogical and analytical insights to enhance the integration of ChatGPT into programming education at the higher education context. This research also provided a new perspective on facilitating collaborative learning experiences among students, instructors, and the AGI system.

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来源期刊

IEEE Transactions on Learning Technologies COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-

CiteScore

7.50

自引率

5.40%

发文量

审稿时长

>12 weeks

期刊介绍： The IEEE Transactions on Learning Technologies covers all advances in learning technologies and their applications, including but not limited to the following topics: innovative online learning systems; intelligent tutors; educational games; simulation systems for education and training; collaborative learning tools; learning with mobile devices; wearable devices and interfaces for learning; personalized and adaptive learning systems; tools for formative and summative assessment; tools for learning analytics and educational data mining; ontologies for learning systems; standards and web services that support learning; authoring tools for learning materials; computer support for peer tutoring; learning via computer-mediated inquiry, field, and lab work; social learning techniques; social networks and infrastructures for learning and knowledge sharing; and creation and management of learning objects.