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Five-sites framework of AI-use expectations in a course

Design · All designs
Evidence · 1 claim (1 for) · 1 study (1 qualitative), q2 · 0 of 1 report an effect size · 1 claim rests on one study

Description

The article proposes that for any given course, concepts of appropriate AI use for academic writing are housed in five distinct sites: faculty intention, formal policy, student interpretation, student self-policy, and student practice. These sites, whether explicit or implicit, formal or informal, often differ from one another, and the divergences create openings for re-interpretation of ethically questionable AI use. The framework explains how instructor expectations are translated, interpreted, personalized, and enacted, with the boundary of acceptable use softening at each site.

Design Implications

Context

Requirements

  • Analysis of a course requires access to both syllabi or formal policy documents and student accounts of their interpretation and practice, as the article obtained through interviews, syllabi, chat logs, and submissions.

Constraints

  • Faculty intention was not measured directly; the article states it was inferred from syllabi and participant interviews because faculty were not interviewed.

Target Learners

  • undergraduate students in higher education

Learning Goals

  • understanding and negotiating course AI policies in academic writing

Claims

Examples

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Key Sources

  • Kim, Jiyoon; Toyama, Kentaro; Kim, Sangmi; Carroll, John. (2026). "It's OK Because...": The Wild West of Student Rationalization of AI Use in Academic Writing. https://arxiv.org/abs/2605.29090. doi:10.48550/arxiv.2605.29090
Page metadata
Field Value
type design
id five-sites-ai-policy-framework
title Five-sites framework of AI-use expectations in a course
description The article proposes that for any given course, concepts of appropriate AI use for academic writing are housed in five distinct sites: faculty intention, formal policy, student interpretation, student self-policy, and...
status review
generated by process:settle-candidates on 2026-10-11
trust unverified — no one has confirmed this page's content
sources 1 — kim-2026

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