Date
Publisher
arXiv
Generative artificial intelligence (GenAI) has already had a big impact on
computing education with prior research identifying many benefits. However,
recent studies have also identified potential risks and harms. To continue
maximizing AI benefits while addressing the harms and unintended consequences,
we conducted a systematic literature review of research focusing on the risks,
harms, and unintended consequences of GenAI in computing education. Our search
of ACM DL, IEEE Xplore, and Scopus (2022-2025) resulted in 1,677 papers, which
were then filtered to 224 based on our inclusion and exclusion criteria. Guided
by best practices for systematic reviews, four reviewers independently
extracted publication year, learner population, research method, contribution
type, GenAI technology, and educational task information from each paper. We
then coded each paper for concrete harm categories such as academic integrity,
cognitive effects, and trust issues. Our analysis shows patterns in how and
where harms appear, highlights methodological gaps and opportunities for more
rigorous evidence, and identifies under-explored harms and student populations.
By synthesizing these insights, we intend to equip educators, computing
students, researchers, and developers with a clear picture of the harms
associated with GenAI in computing education.
Study at a glance
- Question: What harms of generative AI in computing education have been reported, and what empirical evidence supports them?
- Setting and data: Higher education computing education, 2022 to 2025, 224 peer-reviewed academic papers identified across ACM Digital Library, IEEE Xplore, and Scopus.
- Method: Systematic literature review following PRISMA guidelines with deductive and inductive content coding.
Why it matters
Generative AI offers educational benefits, but concerns about negative impacts and unintended consequences are not yet well-understood. Examining these harms is necessary to maximize AI benefits while addressing risks in computing education.
Key findings
- Cognitive harms were the most prevalent category across the reviewed papers (32.4%) and had the highest proportion supported by empirical evidence (28.2%).
- Many reported harms remain insufficiently supported by empirical evidence, with cheating and plagiarism concerns supported by measured evidence in only 8.4% of relevant papers.
- Reported harms heavily concentrated on introductory undergraduate students (69.6% of instances), while social harms and peer collaboration impacts were examined in only 8.5% of papers.
Summary drafted with AI from the full paper and may contain errors. See the full paper for details.
Who age?
Study design
