Causal competencies and learning styles: A framework for adaptive instruction
Vive Kumar, Sabine Graf, Kinshuk -, School of Computing and Information Systems, Athabasca University, Canada
Journal of e-Learning and Knowledge Society Volume 7, Number 3, ISSN 1826-6223 e-ISSN 1826-6223 Publisher: Italian e-Learning Association
Learning in online environments has the potential to better classroom instruction in many avenues. In this context, this article presents two novel technologies, first, a method to causally model learner competencies, both conceptual and metacognitive, and second, a method to identify learning styles of individual learners. We contend that in both cases it would be extremely difficult for human instructors to thoroughly understand the competencies and competency developments of individual leaners as well as the individual learning styles and changes to learning styles. We further contend that these two technologies, as part of a singular framework, will assist classroom instructors to complement their understanding of competencies and learning styles of their classes, respectively, and facilitate instructions to be adapted at various levels of granularity.
Kumar, V., Graf, S. & -, K. (2011). Causal competencies and learning styles: A framework for adaptive instruction. Journal of e-Learning and Knowledge Society, 7(3), 13-32. Italian e-Learning Association.
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J. Michael Spector, Univ. of North Texas, United States
Society for Information Technology & Teacher Education International Conference 2016 (Mar 21, 2016) pp. 2728–2737
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