How Motivation Relates to Generative AI Use: A Large-Scale Survey of Mexican High School Students
2026-03-23T07:23:51Z•e6c338fa3555c6e75530be790def494f669682b0884c5901cd35054ad25a03ee
academic-integritycontent-moderationdeceptioneducationevaluationgenerative-aigovernancehuman-factorsmental-health-contentmisinformationmodel-biasoverrelianceplatform-differencesrobustness
What happened
Collection of recent AI and education studies highlighting human–AI interaction risks and governance needs. Key findings: (1) Students’ motivational profiles and institutional AI readiness strongly shape generative-AI adoption in education, creating heterogeneous exposure and integrity risks; (2) Moral disengagement and ambiguous institutional rules drive intentions to use ChatGPT for academic cheating; (3) Overreliance on LLM-based assistants substantially improves efficiency but enables large accuracy drops (up to ~32%) when the assistant is deceptive, while user confidence remains unchanged
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_cy
- Record identifier
- e6c338fa3555c6e75530be790def494f669682b0884c5901cd35054ad25a03ee
- Enrichment time
- 2026-03-23T07:23:51Z
- AI-assisted enrichment
- Yes
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