A Large-Scale Category-Based Evaluation of A Visual Language for Adaptive Hypermedia

Abstract

Adaptive Hypermedia (AH) provides a personalised and customised approach, enhancing the usability of hypermedia, by building a model of various qualities of a user and applying this information to adapt the content and the navigation to their requirements. However, authoring adaptive materials is not a simple task, as an author may be pressed for time, or simply lack the skills needed to create new adaptive materials from scratch. The most challenging part is the authoring of the adaptation specification (adaptive behaviour rules). This paper tackles this challenge by proposing and evaluating (on a large scale) a visual language for authoring of adaptive hypermedia.