PERSONALISED LEARNING SYSTEM BASED ON STUDENTS’ LEARNING STYLES AND APPLICATION OF INTELLIGENT TECHNOLOGIES
1 Vilnius Gediminas Technical University; Vilnius University Institute of Mathematics and Informatics (LITHUANIA)
2 Vilnius University Institute of Mathematics and Informatics (LITHUANIA)
3 The Netherlands Cancer Institute – Antoni van Leeuwenhoek hospital (NETHERLANDS)
4 Vilnius Gediminas Technical University (LITHUANIA)
About this paper:
Conference name: 9th annual International Conference of Education, Research and Innovation
Dates: 14-16 November, 2016
Location: Seville, Spain
Abstract:The paper aims to present a methodology to personalise learning and a model of personalised intelligent learning system based on students’ learning styles, cognitive traits and another personal characteristics and needs. First of all, the authors performed systematic review on learning personalisation topic. After that, they have analysed students’ preferences to certain learning styles according to Felder and Silverman Learning Styles Model. This analysis is necessary to further creating individual (personalised) learning packages optimised for particular learners in conformity with their learning styles. These learning packages should consist of suitable learning components (learning objects, learning activities, and learning environments) optimal for particular students. Scientific methodology to creating optimised learning packages for particular learners proposed in the paper is based on expert evaluation method and application of intelligent (smart) technologies – ontologies, recommender systems, and intelligent software agents. The results of Lithuanian case study on identifying students’ learning styles are presented in the paper. The model of personalised intelligent learning system based on application of the aforementioned intelligent technologies is presented in more detail. The main success factors of this approach are the application of pedagogically sound vocabularies of the learning components used to create personalised learning packages, and the experts’ collective intelligence.
Keywords: Personalised learning, learning styles, learning packages, intelligent technologies, intelligent learning system.