Towards a Personalized Task Selection Model with Shared Instructional Control
ISAIJLS Volume 34, Number 5, ISSN 0020-4277
Modern education emphasizes the need to flexibly personalize learning tasks to individual learners. This article discusses a personalized task-selection model with shared instructional control based on two current tendencies for the dynamic sequencing of learning tasks: (1) personalization by an instructional agent which makes sequencing decisions on the basis of learner's expertise, and (2) personalization by the learner who is given control over-final-task selection. The model combines both trends in a model with shared instructional control. From all available learning tasks, an instructional agent selects a subset of tasks based on the learner's performance scores and invested mental effort (i.e., system-control). Subsequently, this subset is presented to the learner who makes the final decision (i.e., learner control). A computer-assisted instructional program has been developed to put the model into practice and preliminary results are discussed. The model can be used to increase the efficiency and effectiveness of instruction and to make it more appealing by providing the learner an optimal level of control over task selection.
Corbalan, G., Kester, L. & Van Merrienboer, J.J.G. (2006). Towards a Personalized Task Selection Model with Shared Instructional Control. Instructional Science: An International Journal of the Learning Sciences, 34(5), 399-422.
Cited ByView References & Citations Map
Slava Kalyuga, University of New South Wales, Australia
EdMedia + Innovate Learning 2008 (Jun 30, 2008) pp. 4167–4174
Amy Grincewicz, Janet Mannheimer Zydney, Lori Diehl & Paul Jones, University of Cincinnati, United States
EdMedia + Innovate Learning 2009 (Jun 22, 2009) pp. 1294–1302
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