Whose Judgement Counts? An Appraisal-Informed Critical Discourse Analysis of Educational AI Communications

Public guidance on generative AI asks students to exercise judgement while institutions and platforms define the conditions of use. This study examines how these texts distribute authority over writing, evidence and assessment. The purposively selected corpus comprises eight official webpages from three UK universities and Google and captions from three educational videos, retrieved in October 2026. Appraisal-informed critical discourse analysis examines 30 decision-focused units: passages addressing a particular choice or responsibility. Analysis also considers modality and legitimation, meaning the reasons offered to justify a practice. The main finding is boundary maintenance: texts distinguish what fluent writing, technical capability or disclosure can establish about learning, reliability and permission. University guidance and Gemini promotion both value learner participation, although they serve different purposes. Staff guidance also encourages discussion of assessment criteria. These findings suggest that teachers should explain acceptable assistance, student responsibilities and opportunities to question criteria. The small documentary corpus supports interpretation of published communications, not conclusions about classroom practice or AI effectiveness.

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Publication Details

Journal
International Journal of Language and Literary Studies
Published
2026-11-02
DOI
https://doi.org/10.36892/ijlls.v8i6.2845
Primary Topic
Discourse Analysis in Language Studies
Type
article
Field-Weighted Citation Impact
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article

Whose Judgement Counts? An Appraisal-Informed Critical Discourse Analysis of Educational AI Communications

Thamer Marzouq
4 links
International Journal of Language and Literary Studies
Discourse Analysis in Language Studies
article

Whose Judgement Counts? An Appraisal-Informed Critical Discourse Analysis of Educational AI Communications

Thamer Marzouq
article en

Abstract

Public guidance on generative AI asks students to exercise judgement while institutions and platforms define the conditions of use. This study examines how these texts distribute authority over writing, evidence and assessment. The purposively selected corpus comprises eight official webpages from three UK universities and Google and captions from three educational videos, retrieved in October 2026. Appraisal-informed critical discourse analysis examines 30 decision-focused units: passages addressing a particular choice or responsibility. Analysis also considers modality and legitimation, meaning the reasons offered to justify a practice. The main finding is boundary maintenance: texts distinguish what fluent writing, technical capability or disclosure can establish about learning, reliability and permission. University guidance and Gemini promotion both value learner participation, although they serve different purposes. Staff guidance also encourages discussion of assessment criteria. These findings suggest that teachers should explain acceptable assistance, student responsibilities and opportunities to question criteria. The small documentary corpus supports interpretation of published communications, not conclusions about classroom practice or AI effectiveness.

International Journal of Language and Literary StudiesVol. 8(6)
Taif University (SA)
Quality education
Openalex Percentile: Top 3%
Discourse Analysis in Language Studies
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Whose Judgement Counts? An Appraisal-Informed Critical Discourse Analysis of Educational AI Communications — Thamer Marzouq · International Journal of Language and Literary Studies (2026) | TGRS Research Map | TGRS