On Suitability Index to Create Optimal Personalised Learning Packages

Abstract

The paper aims to present a novel probabilistic method to creating personalised learning packages. The method is based on learning components’ suitability to students needs according to their learning styles. In the paper, the authors use Felder-Silverman Learning Styles Model and an example of Inquiry Based Learning (IBL) method. Expert evaluation method based on trapezoidal fuzzy numbers is applied in the research to obtain numerical values of suitability of learning styles and learning activities. Personalised learning packages should consist of learning components (learning objects, learning activities and learning environments) that are optimal (i.e. the most suitable) to particular students according to their learning styles. “Optimal” means “having the highest suitability index”. Original probabilistic method is applied to establish not only students’ learning styles but also probabilistic suitability of learning activities to students’ learning styles. An example of personalised learning package using IBL activities is presented in more detail.