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The Sentiments and the Impact of ChatGPT on Computer Programming Learning: Data Mining From Comments on YouTube Videos

IF 4.6 2区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH Journal of Computer Assisted Learning Pub Date : 2025-02-22 DOI:10.1111/jcal.70013

Meina Zhu

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Abstract

Background

Computer programming learning and education play a critical role in preparing a workforce equipped with the necessary skills for diverse fields. ChatGPT and YouTube are technologies that support self-directed programming learning.

Objectives

This study aims to examine the sentiments and primary topics discussed in YouTube comments about ChatGPT's impact on learning and writing computer programming.

Methods

The data were collected from 30 November 2022 to 11 January 2024, by extracting 30,773 comments from 57 YouTube videos. Sentiment analysis, topic modelling and thematic analysis were used for data analysis.

Results and Conclusions

Through sentiment analysis and thematic analysis, a positive attitude among YouTube self-directed learners towards employing ChatGPT for learning and writing computer programming was identified. The results of topic modelling and thematic analysis revealed that these learners recognise both the perceived advantages and limitations of using ChatGPT for learning and writing computer programming. The advantages include creating learning plans, generating code, self-correction, explaining code and saving programming time, while the limitations are incorrect information, challenges in debugging programmes, perceived inefficiency and ineffectiveness and the absence of intelligence. Diverse perspectives regarding the impact of ChatGPT on programming professions and education were discussed. Some ethical concerns regarding data privacy, code copyright and equity issues were raised and needed further exploration. The findings imply the importance of computer programming education and integrating ChatGPT into programming education. Guidelines and instructions regarding using ChatGPT for programming learning are needed.

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ChatGPT对计算机编程学习的情感和影响：来自YouTube视频评论的数据挖掘

计算机编程学习和教育在培养具备不同领域所需技能的劳动力方面起着至关重要的作用。ChatGPT和YouTube是支持自主编程学习的技术。本研究旨在研究YouTube评论中讨论的关于ChatGPT对学习和编写计算机编程的影响的情绪和主要主题。方法收集2022年11月30日至2024年1月11日，从57个YouTube视频中提取30,773条评论。数据分析采用情感分析、话题建模和主题分析。结果与结论通过情感分析和主题分析，发现YouTube自主学习者对使用ChatGPT学习和编写计算机程序持积极态度。主题建模和主题分析的结果显示，这些学习者认识到使用ChatGPT学习和编写计算机编程的优势和局限性。优点包括创建学习计划，生成代码，自我纠正，解释代码和节省编程时间，而缺点是不正确的信息，调试程序的挑战，感知效率低下和无效以及缺乏智能。讨论了关于ChatGPT对编程专业和教育的影响的不同观点。提出了一些关于数据隐私、代码版权和公平问题的伦理问题，需要进一步探讨。这一发现暗示了计算机编程教育以及将ChatGPT整合到编程教育中的重要性。需要关于使用ChatGPT进行编程学习的指南和说明。

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

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

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