Higher Education AI Policies—A Document Analysis of University Guidelines

ABSTRACT Artificial Intelligence (AI) has been highlighted as a potentially disruptive force across several industries and in higher education. Research has suggested that education and upskilling of citizens should adopt a broad approach, not only focusing on experts, for better nationwide AI readi...

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Vydané v:European journal of education Ročník 60; číslo 3
Hlavný autor: Humble, Niklas
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Paris Blackwell Publishing Ltd 01.09.2025
Predmet:
AI Policy
Artificial intelligence
Computer Science with specialization in Computer Science Education Research
Datavetenskap med inriktning mot datavetenskapens didaktik
Document analysis
Education policy
Ethics
Generative AI
Higher Education
Official documents
School Policy
Skill development
Technological change
University Guidelines
ISSN:0141-8211, 1465-3435, 1465-3435
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Popis
Shrnutí:ABSTRACT Artificial Intelligence (AI) has been highlighted as a potentially disruptive force across several industries and in higher education. Research has suggested that education and upskilling of citizens should adopt a broad approach, not only focusing on experts, for better nationwide AI readiness. This study investigates the content of AI policies in higher education by analysing official documents from Swedish universities. It identifies key themes and patterns, comparing them with related research and international guidelines. Expanding on the results of the study, it develops a dynamic alignment model for higher education AI policy (DAMHEAP) which, grounded in institutional theory, highlights strategic, pedagogical, ethical and legal, operational and adaptive alignments. This model, together with 10 practical recommendations, provides a roadmap for higher education institutions to develop and maintain AI policies that are pedagogically relevant, ethically responsible and adaptive to technological change.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0141-8211
1465-3435
1465-3435
DOI:10.1111/ejed.70214