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- Vol 4 RE: Chapters 6, 12, 18, 25, App C
artificial intelligence in educationintelligent tutoring systemslearner modellingadaptive assessmenteducational automationhuman agencyeducational technology governanceJournal article Evidence summaryAt a glance
Holmes and Tuomi review the state of artificial intelligence in education and challenge inflated claims about its transformative power.
Key ideas
They explain that expectations often rest on misunderstandings of current technical capabilities, limited knowledge of existing educational applications, and narrow assumptions about education’s social purposes. The article develops a typology of AI-in-education systems and relates different applications to their underlying ideas about intelligence, learning, teaching, and educational aims. It surveys systems that automate or support tasks such as tutoring, assessment, recommendation, and learner modelling, while examining the pedagogical assumptions embedded in their design. The authors identify roadblocks including technically driven development, weak educational theory, limited evidence, reductionist models of learners, and insufficient attention to human agency and institutional context.
Why it matters
They argue that educators and policymakers should evaluate AI by the educational purposes it serves, not by novelty or automation alone, and retain meaningful human responsibility throughout design and use.
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Edition abbreviations
- TE
- Teacher Edition
- PE
- Practice Edition
- RE
- Research Edition
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