Revisiting The Usability of Personalised E-Learning Framework with Social Collaboration Support Using PCA

Abstract

Personalised e-learning aims at providing a personalisation effect based on the learner’s characteristics such as knowledge level, preferences, and learning style. The support derived from using social collaboration tools like social media reflects the discovery of these characteristics from content generated during collaboration. The collaboration process is guided using different annotations equipped with the collaboration tool. This type of system needs to be evaluated in terms of usability factors including usefulness, ease of use, and System Usability Scale (SUS). These evaluation factors reflect the objectives of the system based on the different functionalities provided. Thus, the correlation between these factors and how they are related to the system objectives is needed to be validated. This validation is performed using Principal Component Analysis (PCA) utilising PerLCol framework as discussed in this paper. PerLCol is a framework that aims at providing personalisation effects by utilising the generated information during social collaboration and interaction. The result reveals the strength items as indicated by the selected components (PC1, PC2, and PC3). These components are related to three evaluated factors which are personalisation, social collaboration, and seamless design which ultimately reflect the objectives of the framework.