Merging strategies for authoring QoE-based adaptive hypermedia

Personalization is desirable, but writing the adaptation behaviour description to go with it is taxing. Even more challenging is the application of multiple adaptation strategies over the same static content. This paper focuses on recent work on strategy modularisation and merger development in the authoring process ofadaptive hypermedia. The reason for the modularisation of strategies is to break a complex adaptation decision into a number of simpler ones, which may be reused more easily and applied in different orders. The rationale for strategy merger is to be able to apply multiple adaptation strategies over the same content - a challenge which is not yet fully addressed in current adaptive hypermedia systems. To demonstrate the proposed method we present an example case study and sample strategies written in the LAG adaptation language. The case study is based on a recently proposed model for Quality of Experience in e-learning. This model exposes the complex interaction between a number of factors affecting QoE and hence presents a good candidate for the application of a strategy merger, as well as modularisation. We have then evaluated this approach via structured questionnaires used with a number of design experts of hypermedia content creation, especially in the domain of education. This allows us to draw generic conclusions for both our own further research, as well as for the community at large, interested in the area of reuse and modularisation of adaptation