AMASE: A framework for composing adaptive and personalised learning activities on the web

Abstract

Personalised Web information systems have in recent years been evolving to provide richer and more tailored experiences for users than ever before. In order to provide even more interactive experiences as well as to address new opportunities, the next generation of Personalised Web information systems needs to be capable of dynamically personalising not just web media but web services as well. In particular, eLearning provides an example of an application domain where learning activities and personalisation are of significant importance for engaging and enhancing the learning experience of a learner. This paper presents a novel approach and technical framework called AMASE to support the dynamic generation and enactment of Personalised Learning Activities, which uniquely entails the personalisation of media content and the personalisation of services in a unified manner. In doing so, AMASE combines state of the art techniques from both adaptive web and adaptive workflow systems. © 2012 Springer-Verlag.