Students co-designing a GenAI course policy prioritized training for students and instructors, standardized disclosure procedures, and stronger institutional support¶
Claim · All claims
Evidence · 1 study · qualitativer3·q2
Currency · newest study 2025 · checked against its sources 2026-10-20 (automated, 1 of 1 entry) · not reviewed by a person
Subclaims¶
Reading the evidence codes
q is the design tier, i the impact, n the sample, and the kind with its r
the rigour judged within that kind: what each code means.
This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q2 i? In thematic analysis of student policy artifacts and group discussions, participants prioritized training for students and instructors, standardized procedures for disclosing AI use, and stronger institutional support. → Hingle 2025
Evidence¶
Hingle 2025¶
Hingle, A., & Johri, A. (2025). A Guided Inquiry Approach to Students Co-Designing Generative AI Course Policies. https://www.google.com/search?q=A+Guided+Inquiry+Approach+to+Students+Co-Designing+Generative+AI+Course+Policies doi:10.1108/aiie-05-2025-0123
q2 · i? · qualitative · r3
Hybrid inductive-deductive thematic analysis (Cohen's Kappa .84) of individual policy assignments and group discussions from 55 consenting undergraduates in a technology-ethics course, organized around the ED-AI Lit Framework. The study "showed that participants prioritized training for students and instructors, standardized procedures for disclosing AI use, and stronger institutional support."
"Analysis of student artifacts and group discussions showed that participants prioritized training for students and instructors, standardized procedures for disclosing AI use, and stronger institutional support."
Discussion¶
Related Claims¶
- Students framed an effective GenAI course policy as an interconnected system in which knowledge, evaluation, collaboration, contextualization, autonomy, ethics, and institutional responsibility mutually shape one another — a broader claim this one bears on
- Most participants reported learning something new about GenAI and about two-thirds acknowledged engagement with perspectives beyond their own after the co-design activity — related
- The design-based approach yields a transparent, equitable GenAI policy and deeper instructor thinking about assessment — related
- Stakeholder groups prioritized different design guidelines: instructors most frequently commented on usability (G4), students on educational support (G13), and researchers on instructional best practices and learning engineering — related
- Universities converge on disclosure and attribution expectations as the condition distinguishing legitimate AI assistance from misrepresentation — related
- Among the 50 most innovative U.S. universities, instructor-set syllabus-level governance is the dominant GenAI convergence, with 33 of 50 providing syllabus or course-policy guidance — related
- GenAI-era ICT assessment reform requires a whole-of-institution transformation across seven sequential themes — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
students-prioritize-training-disclosure-institutional-support-genai-policy |
title |
Students co-designing a GenAI course policy prioritized training for students and instructors, standardized disclosure procedures, and stronger institutional support |
description |
Students co-designing a GenAI course policy prioritized training for students and instructors, standardized disclosure procedures, and stronger institutional support |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2025 |
source_checked |
2026-10-20 |
generated |
by process:wiki-ingest on 2026-10-10 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — hingle-2025 |
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