Title: Using learning styles as a basis for creating adaptive open learning environments: an evaluation

Authors: Heba Fasihuddin; Geoff Skinner; Rukshan Athauda

Addresses: School of Design, Communication, and IT, Faculty of Science and IT, The University of Newcastle, Callaghan, NSW 2308, Australia ' School of Design, Communication, and IT, Faculty of Science and IT, The University of Newcastle, Callaghan, NSW 2308, Australia ' School of Design, Communication, and IT, Faculty of Science and IT, The University of Newcastle, Callaghan, NSW 2308, Australia

Abstract: This paper presents an adaptive framework to personalise open learning environments. The design of the framework is grounded in cognitive science and learning principles. Theories of learning styles, specifically the model of Felder and Silverman (1988), have been considered and applied, with the technology of adaptive navigation support integrated into the design of an open learning environment, testing the use of sorting and hiding techniques. This adaptive framework adapts to learners' learning styles by sorting content based on learners' preferences and hiding the least preferred content. Detailed descriptions of the framework's functionalities and different components are presented in this paper. A prototype of this framework was developed and piloted on 88 undergraduate students. Subjective and objective data were collected and statistically analysed in order to evaluate the proposed framework and learners' satisfaction with the adaptive design of the open learning environment. The results and evaluations of this pilot study are reported in this paper, and these show that adapting to learning styles appears to be both helpful for learning and appreciated by learners.

Keywords: adaptive learning systems; learning styles; massive open online courses; MOOCs; open learning environments; personalisation; cognitive science; adaptive navigation support; learner preferences; higher education; undergraduate students; e-learning; electronic learning; online learning.

DOI: 10.1504/IJLT.2016.079034

International Journal of Learning Technology, 2016 Vol.11 No.3, pp.198 - 217

Published online: 09 Sep 2016 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article