Learning Object metadata Application Profile for personalisation

Abstract

Currently, many Learning Objects (LOs) are designed especially for learners having different learning styles e.g. according to Honey-Mumford learning styles model (activists, reflectors, pragmatists, and theorists). The paper aims to analyse creation and application of Learning Object metadata (LOM) Application Profile (AP) suitable to personalise learning objects according to students’ individual differences, e.g. learning styles. During the last years, semantic search methods and technologies are used more widely but keywords-based search techniques (e.g. LOM) are still popular and widely used. The concept of Learning Objects (LOs) has gained wide spread acceptance in the world of e-learning. The main purpose of LOs is to provide a modularised model, based on the standards that enhance flexibility, platform independence, and reuse of the learning content, as well as providing a higher degree of control for teachers and learners. During the past few years, a number of international efforts have been initiated for defining specifications and standards which can facilitate reusability in learning technologies. These efforts have already resulted in a number of specifications for e-Learning applications and services. However, the current versions of these specifications do not support personalised learning. In the paper, first of all, related research review is provided. Second, proposals how to create LOM AP suitable to personalise learning are presented. Third, some practical examples of applying Honey- Mumford learning styles model to personalise LOM AP are presented.