What factors will affect the effectiveness of using ChatGPT to solve programming problems? A quasi-experimental study

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Pubblicato in:Humanities & Social Sciences Communications vol. 11, no. 1 (Dec 2024), p. 319
Autore principale: Jing, Yuhui
Altri autori: Wang, Haoming, Chen, Xiaojiao, Wang, Chengliang
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Springer Nature B.V.
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024 7 |a 10.1057/s41599-024-02751-w  |2 doi 
035 |a 2931867553 
045 2 |b d20241201  |b d20241231 
100 1 |a Jing, Yuhui  |u Zhejiang University of Technology, College of Educational Science and Technology, Zhejiang, China (GRID:grid.469325.f) (ISNI:0000 0004 1761 325X) 
245 1 |a What factors will affect the effectiveness of using ChatGPT to solve programming problems? A quasi-experimental study 
260 |b Springer Nature B.V.  |c Dec 2024 
513 |a Journal Article 
520 3 |a The emergence of ChatGPT has sparked new expectations for AI-empowered educational transformation. However, it remains unknown which factors affect its effectiveness in empowering learners to solve programming problems. Therefore, this study employed a quasi-experimental research design and used Python graphing in programming education as an example to investigate the factors influencing the effectiveness of learners in applying ChatGPT to problem-solving. Findings: AI literacy significantly influences learners’ effectiveness in using ChatGPT to solve problems, with AI awareness and AI usage being key factors. The knowledge base of programming language significantly affects learners’ effectiveness in applying ChatGPT to solve programming problems. Learners’ cognitive level of ChatGPT significantly influences their effectiveness in applying ChatGPT to problem-solving, while usage intention does not have a significant impact. However, learners’ intention to use ChatGPT significantly improves after application. Based on these findings, this study proposes that in the process of empowering education with Artificial Intelligence Generated Content (AIGC) products, the focus on learners should shift from cultivating their AI usage to AI literacy, laying the foundation for empowering learning with AIGC products. It is suggested to shift from mastering specific knowledge to graph-based rules as a method for empowering learning with AIGC products. Additionally, the focus should shift from enhancing learners’ intention to use the technology to strengthen their technological awareness, thereby creating practical pathways for empowering learning with AIGC products. 
653 |a Problem solving 
653 |a Teaching 
653 |a Research methodology 
653 |a Human-computer interaction 
653 |a Literacy 
653 |a Artificial intelligence 
653 |a Language usage 
653 |a Knowledge 
653 |a Language instruction 
653 |a Research design 
653 |a Empowerment 
653 |a Questionnaires 
653 |a Systems development 
653 |a Programming languages 
653 |a Education 
653 |a Learning 
653 |a Chatbots 
653 |a Digital literacy 
653 |a Knowledge base 
653 |a Effectiveness 
653 |a Quasi-experimental methods 
653 |a Transformation 
653 |a Educational programs 
653 |a Artificial intelligence literacy 
700 1 |a Wang, Haoming  |u East China Normal University, Department of Education Information Technology, Faculty of Education, Shanghai, China (GRID:grid.22069.3f) (ISNI:0000 0004 0369 6365) 
700 1 |a Chen, Xiaojiao  |u Zhejiang University of Technology, College of Educational Science and Technology, Zhejiang, China (GRID:grid.469325.f) (ISNI:0000 0004 1761 325X) 
700 1 |a Wang, Chengliang  |u East China Normal University, Department of Education Information Technology, Faculty of Education, Shanghai, China (GRID:grid.22069.3f) (ISNI:0000 0004 0369 6365) 
773 0 |t Humanities & Social Sciences Communications  |g vol. 11, no. 1 (Dec 2024), p. 319 
786 0 |d ProQuest  |t Social Science Database 
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