Adaptation Languages for Learning: The CAM Meta-model

Adaptive Hypermedia (AH) can offer a richer learning experience, tailored to students’ needs. However, authoring of AH is complex. Several models and systems have been developed. However the adaptation that can be defined, is limited in terms of (re)-usability by educational authors. To simplify adaptive behaviour authoring, the solution considered most intuitive [7] is a visual environment. In this paper we specify the design of a visual authoring tool. We describe the implications this visual aspect has for the adaptation languages. This reflects lessons learnt from the experience of authoring project partners of the EU GRAPPLE project, hence is of interest to any designer or developer of reusable, general purpose adaptive elearning system.

• Type: Conference
• Year: 2009
• Where: ICALT
• Authors: Maurice Hendrix, Alexandra I. Cristea, Craig Stewart
• Keywords: Adaptive, ICALT 2009, Machine Learning, Richer Learning Experience, Visual Authoring Tool