Claims

User engagement with GAI tools is filtered through imagined affordances rather than direct encounter with software functionalities

Claim · All claims
Evidence · 1 study · associational r1 · q1
Currency · newest study 2026 · not yet checked against its sources · 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.

q1 i? If a user does not imagine the software can be used for a purpose, they will not use the technology that way, so perceptions are integral to technology use. → Kahn P 2026

Evidence

Kahn P 2026

Kahn P, Carrigan M, Wyman I, Liu R, Smith P, Andonegui AR, Murtagh L and Song F (2026) Still emerging: understanding Generative AI use in Higher Education. Front. Educ. 11:1885253. https://doi.org/10.3389/feduc.2026.1885253

q1 · i? · associational · r1

Theoretical argument in the literature review, drawing on Nagy and Neff (2015) and Archer (2000): affordances manifest through interaction rather than inhering in software. The article offers this as a conceptual argument, not a tested result, and states the study takes perceptions as indicators of how affordances are imagined.

"user engagement is always filtered through imagined affordances rather than being an immediate encounter with functionalities and constraints that are objectively part of the software. Indeed, the relational character of affordances complicates objectivity"

Discussion

Page metadata
Field Value
type claim
id imagined-affordances-filter-gai-engagement
title User engagement with GAI tools is filtered through imagined affordances rather than direct encounter with software functionalities
description User engagement with GAI tools is filtered through imagined affordances rather than direct encounter with software functionalities
status review
evidence_strength weak
newest_evidence 2026
generated by process:wiki-ingest on 2026-10-11
trust unverified — no one has confirmed this page's content
sources 1 — kahn-p-2026

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