Content area
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.
Details
Teaching;
Research methodology;
Human-computer interaction;
Literacy;
Artificial intelligence;
Language usage;
Knowledge;
Language instruction;
Research design;
Empowerment;
Questionnaires;
Systems development;
Programming languages;
Education;
Learning;
Chatbots;
Digital literacy;
Knowledge base;
Effectiveness;
Quasi-experimental methods;
Transformation;
Educational programs;
Artificial intelligence literacy
1 Zhejiang University of Technology, College of Educational Science and Technology, Zhejiang, China (GRID:grid.469325.f) (ISNI:0000 0004 1761 325X)
2 East China Normal University, Department of Education Information Technology, Faculty of Education, Shanghai, China (GRID:grid.22069.3f) (ISNI:0000 0004 0369 6365)