TY - JOUR
T1 - Framing AI in Higher Education: A Critical Discourse Analysis of Inclusivity and Power in University AI Guidance Documents
AU - Simpson, Nicholas
PY - 2025/2/24
Y1 - 2025/2/24
N2 - The language of artificial intelligence (AI) guidance documents in higher education (HE) institutions reflects broader societal dynamics and raises important questions about inclusivity and accessibility. This study investigates how selective (Russell Group) and less selective UK universities craft their student-facing AI guidance documentation, focusing on the language and discourses embedded within these documents. Using critical discourse analysis (CDA), documents from six UK universities (three less selective institutions from the top of the intergenerational mobility rankings and three highly selective universities from the bottom) are analysed to explore differences in language, style, content, and framing of agency and responsibility. Findings reveal that selective universities often adopt hierarchical, authoritarian language that emphasises individual student accountability for the proper use of AI tools. Such an approach reflects selective universities’ institutional approaches to power and hierarchy and aligns with broader societal worries about the influence of AI. In contrast, less selective institutions adopt a relatively more inclusive and explanatory rhetoric more consistent with the expectations and needs of students from diverse socioeconomic backgrounds.
AB - The language of artificial intelligence (AI) guidance documents in higher education (HE) institutions reflects broader societal dynamics and raises important questions about inclusivity and accessibility. This study investigates how selective (Russell Group) and less selective UK universities craft their student-facing AI guidance documentation, focusing on the language and discourses embedded within these documents. Using critical discourse analysis (CDA), documents from six UK universities (three less selective institutions from the top of the intergenerational mobility rankings and three highly selective universities from the bottom) are analysed to explore differences in language, style, content, and framing of agency and responsibility. Findings reveal that selective universities often adopt hierarchical, authoritarian language that emphasises individual student accountability for the proper use of AI tools. Such an approach reflects selective universities’ institutional approaches to power and hierarchy and aligns with broader societal worries about the influence of AI. In contrast, less selective institutions adopt a relatively more inclusive and explanatory rhetoric more consistent with the expectations and needs of students from diverse socioeconomic backgrounds.
M3 - Article
SN - 2748-9329
JO - Educational Linguistics
JF - Educational Linguistics
ER -