The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Student Perceptions of Using Generative AI Chatbot in Learning Programming
Open accessAbstract
Interest in Generative Al (GenAl) chatbots has exploded across the education industry, subsequently expanding in sophistication and usage. However, students' perceptions on utilizing this technology ultimately determines how well these chatbots promote learning. Hence, this study examines the factors influencing how Singapore secondary school-aged computing students perceive using MyBotBuddy (MBB), a GenAl chatbot, to assist them with programming tasks. A thematic analysis determined that students' perceptions were influenced by reliability, utility, cognitive effort needed, satisfaction, and enjoyment. The study contributes to the literature on GenAl chatbots supporting secondary school programming students and may guide the development of such tools in secondary school classrooms more effectively.
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“A second major objective is to situate the development of computational thinking and programming competence within authentic practices. Here, the target is to support students in refining their algorithmic reasoning, problem decomposition, and coding practices. The integration of AI-powered programming environments and intelligent feedback mechanisms serves to meet these goals, particularly by low”
From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [98]
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“Some studies document confusion, frustration, and other negative emotions driven by mistrust, technical limits, or unmet expectations [78,87,93,98], and even declines in self-efficacy [140].”
From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [98]
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Citations
Cites
Perceived usefulness, perceived ease of use, and user acceptance of information technology
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Technology Acceptance Model 3 and a Research Agenda on Interventions
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Bahroun, Z., Anane, C., Ahmed, V., & Zacca, A. (2023) · Sustainability · doi:10.3390/su151712983 · Cited by 784
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Computer Programming Education in the Age of Generative AI: Insights from Empirical ResearchPreprint
Deriba, F. G., Sanusi, I. T., Campbell, O. O., & Oyelere, S. S. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4891302 · Cited by 23
Research works printed but not linked: 3
- Khor, E. T., Koh, E., & Seow, P. (2024, June). Leveraging generative artificial Intelligence to support students in learning programming: A chatbot pilot study. In Proceedings of the 18th International Conference on Learning Sciences. International Society of the Learning Sciences. United States: Buffalo.
- Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257-285. https://doi.org/10.1207/s15516709cog1202_4 · DOI · Paper page
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Cited by
Sorted by citations
Lin, X., & Tan, H. (2025) · Systems · doi:10.3390/systems13100840 · Cited by 22
Metadata
- Authors
- KHOR, E. T., CHAN, L., KOH, E., & SEOW, P.
- Affiliations
- Nanyang Technological University (SG)
- Venue
- International Conference on Computers in Education
- Published
- 2024-11-25
- ISSN
- 3078-4360 (ISSN-L)
- OpenAlex
- W4406621555
- Cited by
- 2
- References
- 6
- Citations by year
- 2025: 2
- FWCI
- 0.88
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- International Conference on Computers in Education (publishedVersion)
- NIE Digital Repository (National Institute of Education, Nanyang Technological University) (publishedVersion)
- International Conference on Computers in Education (acceptedVersion)
- Funders
- Ministry of Education, India
- 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
- generative AI chatbots, student perceptions, programming education, high school students, chatbot reliability, perceived usefulness, cognitive effort, student satisfaction, student enjoyment, AI-assisted learning
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- KHOR, E. T., CHAN, L., KOH, E., & SEOW, P. (2024). Student Perceptions of Using Generative AI Chatbot in Learning Programming. International Conference on Computers in Education. https://doi.org/10.58459/icce.2024.4822
