Computational Intelligence in Adaptive Educational Hypermedia

In this paper neuro-fuzzy synergism is applied to implement content sequencing in adaptive hypermedia systems. The level of understanding of the learner is used to construct lessons adapted to the learner’s knowledge goals and level of expertise on the domain concepts s/he has already studied. The learner’s evaluation is based on defining appropriate fuzzy sets and relate learner’s response with appropriate knowledge and cognitive characterizations. A connectionist-based structure of the domain knowledge is adopted for representing knowledge and inferring the planning strategy for generating the hypermedia page from pieces of educational material. The fuzziness associated with the evaluation of the learner is handled well by the proposed connectionist architecture.