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Cited by 108Teaching and Learning ProgrammingArtificial Intelligence in EducationIntelligent Tutoring Systems and Adaptive Learning

The DOI matches its Crossref record; 103 of the 104 references it cites were found in a registry or an index.

The effectiveness of ChatGPT in assisting high school students in programming learning: evidence from a quasi-experimental research

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Yang, Tzu-Chi, Hsu, Yi-Chuan, Wu, Jiun-Yu·2025·Interactive Learning Environments
DOI 10.1080/10494820.2025.2450659
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Abstract

Programming education gains importance in high schools as the digital age progresses. However, the openness and adaptability of programming languages present unique challenges for instructional practices compared to other subjects. While traditional instructional tools offer limited support, ChatGPT, a groundbreaking Generative Artificial Intelligence, has shown impressive capabilities in natural language processing and knowledge generation. This study explored whether ChatGPT can transcend existing limitations and improve programming education through a quasi-experimental approach with post-hoc interviews in high school classrooms. A total of 153 students participated, and the results from MANCOVA and ANCOVA analyses revealed that students using ChatGPT reported lower levels of flow experience, self-efficacy, and learning achievement compared to those utilizing conventional methods. Post-hoc interviews further revealed that students felt ChatGPT's effectiveness in facilitating their programming learning fell short of their initial expectations. These findings highlight the need to carefully consider the complexity of programming learning tasks and students' cognitive, affective, and interactive dimensions when integrating AI technologies into education. We discuss the implications and provide thorough pedagogical strategies, specifically the guidance–practice–transformation (G–P–T) mode, to maximize the potential of AI tools and support high school programming education, emphasizing the balance of technological innovation with learning best practices.

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Crossref · 10.1080/10494820.2025.2450659

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Research works printed but not linked: 2

  1. 10.1016/S0747-5632(04)00036-6 · DOI
  2. Yang, T. C., Hwang, G. J., Yang, S. J., & Hwang, G. H. (2015). A two-tier test-based approach to improving students’ computer-programming skills in a web-based learning environment. Journal of Educational Technology & Society, 18(1), 198–210.

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Metadata

Authors
Yang, T.-C., Hsu, Y.-C., & Wu, J.-Y.
Affiliations
  • National Yang Ming Chiao Tung University (TW)
  • Tainan First Senior High School (TW)
  • Southern Methodist University (US)
Corresponding author
Yang, Tzu-Chi
ORCID
Venue
Interactive Learning Environments
Publisher
Informa UK Limited
Published
2025-01-16
Volume
33
Issue
6
Pages
3726-3743
ISSN
  • 1049-4820 (ISSN-L)
  • 1744-5191
DOI
10.1080/10494820.2025.2450659
OpenAlex
W4406474705
Cited by
80
References
104
Citations by year
2026: 63 · 2025: 17
FWCI
71.05
Type
journal article
Language
en
Open access
Licence
Locations
Interactive Learning Environments (publishedVersion, cc-by)
Funders
National Science and Technology Council (111-2410-H-A49-066-MY3)
Topics
  • Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
  • Social Sciences › Education › Artificial Intelligence in Education
  • Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
Keywords
ChatGPT, generative AI, programming education, high school students, flow experience, self-efficacy, academic performance, artificial intelligence in education, student perceptions of AI tools

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