Augmented intelligence in programming learning: Examining student views on the use of ChatGPT for programming learning
Open accessAbstract
With the diversification of generative artificial intelligence (AI) applications, the interest in their use in every segment and field of society in recent years has been increasing rapidly. One of these areas is programming learning and program writing processes. One of the generative AI tools used for this purpose is ChatGPT. The use of ChatGPT in program writing processes has become widespread, and this tool has a certain potential in the programming process. However, when the literature is examined, research results related to using ChatGPT for this purpose have yet to be found. The existing literature has a gap that requires exploration. This study aims to analyze the students' perspectives on using ChatGPT in the field of programming and programming learning. The study encompassed a cohort of 41 undergraduate students enrolled in a public university's Computer Technology and Information Systems department. The research was carried out within the scope of the Object-Oriented Programming II course for eight weeks. Throughout the research process, students were given project assignments related to the course every week, and they were asked to use ChatGPT while solving them. The research data was collected using a form consisting of open-ended questions and analyzed through content analysis. The research findings revealed both the advantages and disadvantages of ChatGPT usage, as perceived by the students. The students stated that the main benefits of using ChatGPT in programming learning are providing fast and mostly correct answers to questions, improving thinking skills, facilitating debugging, and increasing self-confidence. On the other hand, the main limitations of using ChatGPT in programming education were getting students used to laziness, being unable to answer some questions, or giving incomplete/incorrect answers, causing professional anxiety in students. Based on the results of the research, it can be said that it would be useful to integrate generative AI tools into programming courses considering the advantages they provide in programming teaching. However, appropriate measures should be taken regarding the limitations it brings. Based on the research findings, several recommendations were proposed regarding the integration of ChatGPT into lessons.
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Even these studies provide contradictory evidence on whether ChatGPT is helpful or harmful for students.
“Even these studies provide contradictory evidence on whether ChatGPT is helpful or harmful for students.”
From Is it harmful or helpful? Examining the causes and consequences of generative AI usage among university students (2024) · cites this paper as Yilmaz & Yilmaz, 2023a
Students lack confidence in their own academic merit when AI handles high-level cognitive processes.
“Issues related to identity also arise, as reported by Yilmaz and Karaoglan Yilmaz (2023): students lack confidence in their own academic merit when AI handles high-level cognitive processes.”
From Mapping the impact of generative AI in higher education: A scoping review of psychological and equity dimensions. (2026) · cites this paper as Yilmaz and Karaoglan Yilmaz (2023)
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Twitter users perceptions of AI-based e-learning technologies
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Cheaters or AI-Enhanced Learners: Consequences of ChatGPT for Programming Education
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Harnessing Artificial Intelligence in Generative Content for enhancing motivation in learning
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AI-powered education: Driving entrepreneurial spirit among university students
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Literature Review on the Integration of Generative AI in Programming Education
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Impact of generative AI dialogic feedback on different stages of programming problem solving
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Harnessing the benefits of ChatGPT for radiography education: A discussion paper
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ChatGPT Helped Me Build a Chemistry App, and Here’s How You Can Make One Also
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Large Language Models in Computer Science Classrooms: Ethical Challenges and Strategic Solutions
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Exploring Student Interactions with AI in Programming Training
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Overview and confirmatory and exploratory factor analysis of AI literacy scale
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Effects of Block-Based Visual Programming on K-12 Students’ Learning Outcomes
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Leveraging ChatGPT to Support Self-Regulated Learning in Online Courses
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- Authors
- Yilmaz, R., & Karaoglan Yilmaz, F. G.
- ORCID
- Yilmaz, Ramazan
- Venue
- Computers in Human Behavior: Artificial Humans
- Publisher
- Elsevier BV
- Published
- 2023-08
- Volume
- 1
- Issue
- 2
- Pages
- 100005
- ISSN
- 2949-8821 (ISSN-L)
- OpenAlex
- W4384461076
- Cited by
- 344
- References
- 48
- Citations by year
- 2026: 94 · 2025: 130 · 2024: 103 · 2023: 16 · 2019: 1
- FWCI
- 78.18
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Computers in Human Behavior Artificial Humans (publishedVersion, cc-by-nc-nd)
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Information Systems › Software Engineering Research
- Keywords
- ChatGPT, generative AI, programming education, student perceptions, augmented intelligence, object-oriented programming, debugging, professional anxiety, AI-assisted programming, computer science undergraduates
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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