The article interprets the ethics gap as students viewing ethics through coursework practices and instructors treating it as an integrity question shaped by lack of institutional clarity¶

Claim · All claims
Evidence · 1 study · associational r? · q1
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person · recheck by 2031: baselines and conditions change

Subclaims¶

q1 i? The authors propose that students tend to view ethics through their immediate coursework practices, whereas teachers interpret it through the lack of institutional clarity and treat it as a question of integrity. → Fekete 2026

Evidence¶

Fekete 2026¶

Fekete, I. (2026). Between Promise and Practice: Bridging Ethical Artificial Intelligence Literacy Gaps Across Students, Educators, and Policy. Journal of University Teaching and Learning Practice. https://doi.org/10.53761/9fr5vw20

q1 · i? · associational · r?

This is the authors' own interpretation offered as a possible explanation ("might be because") for the group differences; the article presents it as a hedged explanatory account, not a tested result, and provides no separate evidence for it.

"which might be because students tend to view ethics through their immediate coursework practices, whereas teachers interpret it through the lack of institutional clarity and treat is as a question of integrity"

Discussion¶

Related Claims¶

• Academic integrity, professional development, and equity concerns about AI span all surveyed units, though interpreted differently — related
• Associate deans report that neither their institution nor their units have implemented official AI policies, prompting localized unit-level guidelines — related
• AI integration in academic settings has outpaced regulatory frameworks, leaving ethical practices, assessment, and institutional responses inconsistent — a broader claim this one bears on
• In interviews with 25 engineering students at one Swedish university, students described GenAI as acceptable when it stimulates reflection and directly copying its outputs as cheating, and one used its fallibility as a prompt to double-check — a narrower finding that bears on this claim
• Institutions have expanded student access to generative AI tools faster than they have developed policies, guidance, and shared learning goals for their use — related
• Teachers raise big-picture concerns about GenAI including surveillance, over-reliance, reduced teacher collaboration, job replacement, and training needs — related
• Student perceptions of AI use in academic work are neutral and range from viewing AI as valid learning assistance to viewing it as cheating, depending on task type, transparency, and assessment design — a narrower finding that bears on this claim
• University students' engagement with AI tools tends to cluster at two extremes: avoidance and uncritical use — related
• A gap exists between students' ethical awareness and their GenAI practices, with students who frequently engage in behaviours they view as unethical and rationalisations normalising such use — related
• Undergraduate students hold mixed views on whether using GenAI for coursework constitutes plagiarism, ranging from not misconduct to serious misconduct — related
• Whether student GenAI use constitutes academic misconduct depends fundamentally on the prior question of the university's purpose — related
• University administrations endorse contradictory positions on GenAI, encouraging faculty integration while treating AI-generated work as misconduct — related
• Institutional AI policy formation lags behind practical AI presence in coursework, leaving many faculty in policy vacuums — related