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

IF 5.1 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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引用次数: 0

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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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