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Héctor J. Pijeira-Díaz; Sophia Braumann; Janneke van de Pol; Tamara van Gog; Anique B. H. Bruin – British Journal of Educational Technology, 2024
Advances in computational language models increasingly enable adaptive support for self-regulated learning (SRL) in digital learning environments (DLEs; eg, via automated feedback). However, the accuracy of those models is a common concern for educational stakeholders (eg, policymakers, researchers, teachers and learners themselves). We compared…
Descriptors: Computational Linguistics, Independent Study, Secondary School Students, Causal Models
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Kitto, Kirsty; Hicks, Ben; Shum, Simon Buckingham – British Journal of Educational Technology, 2023
An extraordinary amount of data is becoming available in educational settings, collected from a wide range of Educational Technology tools and services. This creates opportunities for using methods from Artificial Intelligence and Learning Analytics (LA) to improve learning and the environments in which it occurs. And yet, analytics results…
Descriptors: Causal Models, Learning Analytics, Educational Theories, Artificial Intelligence
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Gibson, David; Kovanovic, Vitomir; Ifenthaler, Dirk; Dexter, Sara; Feng, Shihui – British Journal of Educational Technology, 2023
This paper discusses a three-level model that synthesizes and unifies existing learning theories to model the roles of artificial intelligence (AI) in promoting learning processes. The model, drawn from developmental psychology, computational biology, instructional design, cognitive science, complexity and sociocultural theory, includes a causal…
Descriptors: Learning Theories, Artificial Intelligence, Learning Processes, Evaluation Criteria