Supporting the non-expert in the authoring of personalized learning using IMS LD

Abstract

This paper presents an alternate classification of the approaches employed in today’s IMS LD authoring tools to support the engagement of non-experts in the design of instruction for today’s e-learning. The classification is based on how the authors can approach the design task and the support that is afforded to them by the authoring tool. The paper presents the case for an approach based on educational scenario-based modelling, as best suitable to actualize a higher level of involvement on the part of the non-expert authors in the creation of personalized learning based on portfolios, and learner information. Additionally, based on the classifications, the paper proposes a set of features based on which today’s crop of IMS LD tools can be classified, and a new generation of tools to support the non-expert authors can be modelled.