Using Learning Analytics and Learning using Learning Styles to Personalise Content in Adaptive Educational Systems
AbstractThe efforts towards providing personalised e-learning is an increasing trend due to the fact that content provision is usually a one size fits all approach. Students have different learning styles, skills and needs which dictate the way in which they learn. This paper presents an adaptive educational system called iPal (Integrated Personalised Assessment in Learning). iPal is designed to be a more effective learning environment to satisfy the online delivery of practical Science, Technology, Engineering and Maths (STEM) subjects, as a supplementary course tool in higher education. The practical approach of iPal specifically addresses the lack of game based learning in adaptive educational systems. The focus of this paper is based on a two tiered approach using the implicit approach of learning analytics and the explicit approach of learning styles to personalise content in iPal. This paper discusses how these approaches are effective enablers in the delivery of personalised content. A case study demonstrating the practical application of the iPal system is presented comprising of over 100 undergraduate Computing students. The key significance of this research is that it provides clear evidence for the successful use of iPal as a supplementary course tool in higher education.
McCusker, K, Harkin, J, Wilson, S and Callaghan, MJ (2014) Using Learning Analytics and Learning using Learning Styles to Personalise Content in Adaptive Educational Systems. In: 6th International Conference on Education and New Learning Technologies (EDULEARN). IATED. 10 pp. [Conference contribution]