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2 references
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- Vol 4 RE: Chapters 5, 14, 19, App B, App C
human agencyintentionalityforethoughtself-regulationself-reflectioncollective agencysocial cognitive theoryJournal article Evidence summaryAt a glance
Bandura presents an agentic account in which people help shape their circumstances rather than merely react to environmental forces.
Key ideas
Human agency rests on intentionality, forethought, self-reactiveness, and self-reflectiveness: people form plans, anticipate consequences, regulate action, and examine their own functioning. Agency can be exercised personally, by proxy through others, or collectively through coordinated effort. Social cognitive theory avoids treating agency and social structure as opposites; people create social systems that subsequently enable and constrain action. The article also places agency within biological, cultural, and technological coevolution.
Why it matters
For educators, the account supports learning environments in which students set meaningful goals, select and monitor strategies, reflect on consequences, and experience collective efficacy, while recognising that agency always operates through opportunities and constraints in the surrounding system.
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- Vol 7 RE: Chapters 11, 14
hybrid intelligencelearning analyticseducational artificial intelligencecognitive augmentationhuman agencyai literacyhuman–ai collaborationJournal article Evidence summaryAt a glance
Cukurova challenges the narrow view of educational AI as a collection of tools, especially generative systems that externalize human cognitive work. He reconnects artificial intelligence, learning analytics, and learning science through a human-centred framework with three possibilities: AI can externalize cognition by performing tasks, shape cognition as people internalize its models and outputs, or extend cognition through tightly coupled human–AI systems.
Key ideas
The last possibility supports hybrid intelligence, in which complementary human and machine capabilities produce outcomes neither could achieve alone. AI and analytics can also make learning processes visible and provide material for scientific inquiry, feedback, awareness, and regulation. Yet prediction alone does not explain learning, and indiscriminate delegation may weaken important human competencies. The article therefore asks researchers and educators to examine which cognitive work should remain human, how agency and meaning-making are preserved, and how systems affect competence over time.
Why it matters
It calls for broader AI literacy, educational-system innovation, and research that evaluates augmentation, ethics, and human development rather than merely tool performance.
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Edition abbreviations
- TE
- Teacher Edition
- PE
- Practice Edition
- RE
- Research Edition
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