Adaptive versus Learner Control in a Multiple Intelligence Learning Environment
Declan Kelly, National College of Ireland, Ireland
Journal of Educational Multimedia and Hypermedia Volume 17, Number 3, ISSN 1055-8896 Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC USA
Abstract: Within the field of technology enhanced learning, adaptive educational systems offer an advanced form of learning environment that attempts to meet the needs of different students. Such systems capture and represent, for each student, various characteristics such as knowledge and traits in an individual learner model. Subsequently, using the resulting model it dynamically adapts the learning environment for each student in a manner that attempts to best support learning. However, there are some unresolved issues in building adaptive educational systems that adapt to individual traits. For example in what way should the learning environment support users with different learning characteristic and what advantage does adaptive control have over learner control. This paper describes an experiment using the Multiple Intelligence based adaptive intelligent educational system, EDUCE, that explores how the learning environment should change for users with different trait characteristics. In particular it explores the effect of using different adaptive presentation strategies in contrast to giving the learner complete control over the learning environment. Results suggest that students who do not explore alternative resources beyond the first presented resource have most to benefit from adaptive presentation strategies and that surprisingly learning gain increases when they are provided with resources not normally preferred.
Kelly, D. (2008). Adaptive versus Learner Control in a Multiple Intelligence Learning Environment. Journal of Educational Multimedia and Hypermedia, 17(3), 307-336. Waynesville, NC USA: Association for the Advancement of Computing in Education (AACE).
© 2008 Association for the Advancement of Computing in Education (AACE)
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Lisa Brown, Claremont Lincoln University, United States
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Ching-Huei Chen, National Changhua University of Education
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