From Assistance to Misconduct: Unpacking the Complex Role of Generative AI in Student Learning
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This research-to-practice full paper discusses students' views on the role of generative artificial intelligence (GenAI) in their learning. The rapid integration of GenAI in educational settings has prompted significant interest in its implications for learning and academic integrity. This study investigates the adoption and impact of GenAI tools among computing students at a university, focusing on how they are utilized for educational purposes and their ethical implications. Semi-structured interviews with nine computing students were used to examine GenAI's specific use and timing. Additionally, it explores students' perceptions of the trustworthiness of GenAI outputs and identifies the students' ethical boundaries concerning its use in academic work. The findings reveal that while GenAI tools might enhance learning efficiency and provide substantial educational support, they raise significant ethical concerns, particularly regarding academic misconduct. The study highlights the need for educational strategies to navigate the challenges posed by GenAI technologies. Finally, three recommendations for computing education are outlined. This research contributes to the ongoing discourse on GenAI in education by describing the student's reflections on GenAI.
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In some contexts, there is a prevailing cultural perception that the use of AI tools constitutes a form of academic dishonesty.
“Moreover, in some contexts, there is a prevailing cultural perception that the use of AI tools constitutes a form of aca -demic dishonesty [ 82, 83].”
From Redefining student assessment in AI-infused learning environments: a systematic review of challenges and strategies for academic integrity (2026) · cites this paper as [83]
The paper’s “Perceptions of Academic Misconduct Involving GenAI” section reports that computing students regard copying AI-generated answers into assignments as cheating. Its “Summary of Results” also says they regard GenAI use for inspiration or understanding as acceptable. The source therefore supports a perception that certain uses are dishonest, but not a prevailing cultural perception that AI-tool use generally is dishonest; page numbers are unavailable in our copy. (LLM, conf=0.83)
Experimental — accuracy not yet measuredRegarding honesty and deception, students may make a conscious decision to commit an academic offense when they are under significant pressure to meet deadline.
“Regarding honesty and deception, students may make a conscious decision to commit an academic offense when they are under significant pressure to meet deadline [25].”
From Navigating the Ethical and Societal Impacts of Generative AI in Higher Computing Education (2025) · cites this paper as [25]
The paper’s “Reduce Excessive Pressure to Prevent Misuse” section says students often turn to GenAI for content creation under deadline pressure. Its “Perceptions of Academic Misconduct Involving GenAI” section says students recognize copying GenAI answers into assignments as cheating. Neither passage establishes that students under deadline pressure consciously decide to commit an academic offense; the paper discusses pressured GenAI use more broadly. (LLM, conf=0.84)
Experimental — accuracy not yet measuredStudents use GenAI for a variety of tasks, including content generation, problem-solving, debugging, conceptual understanding, and exam preparation.
“Students use GenAI for a variety of tasks, including content generation, problem-solving, debugging, conceptual understanding, and exam preparation [25, 308].”
From Navigating the Ethical and Societal Impacts of Generative AI in Higher Computing Education (2025) · cites this paper as [25]
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References 26 · Cited by 5
Research works printed but not linked: 5
- C. Longoni, S. Tully, and A. Shariff, "Plagiarizing AI- generated Content Is Seen As Less Unethical and More Permissible," 2023, Accessed: May 10, 2024. [Online]. Available: https://osf.io/preprints/psyarxiv/na3wb/
- P. Denny, H. Khosravi, A. Hellas, J. Leinonen, and S. Sarsa, "Can We Trust AI-Generated Educational Content? Comparative Analysis of Human and AI-Generated Learning Resources," ArXiv Prepr. ArXiv230610509, 2023, Accessed: May 12, 2024. [Online]. Available: https://hassan- khosravi.net/publications/denny2023a.pdf
- C. K. Y. Chan, "Is AI Changing the Rules of Academic Misconduct? An In-depth Look at Students' Perceptions of 'AI-giarism.'" arXiv, Jun. 09, 2023. doi: 10.48550/arXiv.2306.03358. · DOI · Paper page
- H. Ndebele, "Demystifying student plagiarism in academic writing: Towards an 'educational'solution," Crit. Stud. Teach. Learn., vol. 8, no. 2, 2020, Accessed: May 16, 2024. [Online]. Available: https://www.ajol.info/index.php/cristal/article/view/203972
- M. Daniels, Å. Cajander, T. Clear, and R. McDermott, "Collaborative technologies in global engineering: New competencies and challenges," Int. J. Eng. Educ., vol. 31, no. 1, pp. 267-281, 2015.
- Authors
- Axelsson, A., Wallgren, D. T., Verma, U., Cajander, Å., Daniels, M., Eckerdal, A., & McDermott, R.
- Affiliations
- Uppsala University (SE)
- Robert Gordon University (GB)
- Venue
- 2024 IEEE Frontiers in Education Conference (FIE)
- Publisher
- IEEE
- Published
- 2024-10-13
- Pages
- 1-8
- ISSN
- 0190-5848 (ISSN-L)
- OpenAlex
- W4407951461
- Cited by
- 5
- References
- 26
- Citations by year
- 2026: 4 · 2025: 1
- FWCI
- 1.90
- Type
- conference paper
- Language
- en
- Open access
- Locations
- IEEE Frontiers in Education Conference (FIE) (publishedVersion)
- Open Access Institutional Repository at Robert Gordon University (Robert Gordon University) (submittedVersion, cc-by)
- Funders
- Uppsala Universitet
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Social Sciences › Safety Research › Academic integrity and plagiarism
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- generative AI, student perceptions, academic misconduct, academic integrity, computing students, ethical use of AI, artificial intelligence in education, student learning
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