Neuro-fuzzy synergism for planning the content in a web-based course

The vision of a new generation of learning environments, which possess the ability to make intelligent decisions about the interactions that take place during learning, encourages researchers to look at novel forms of co-operation and communication between tutors, learners, developers and computers and to investigate the technical possibilities for their realization. In this paper, neuro-fuzzy synergism is suggested as a means to implement intelligent decision making for planning the content in a web-based course. In this context, the content of the lesson is dynamically adapted to the learner’s knowledge goals and level of expertise on the domain concepts s/he has already studied. Several issues that affect the effectiveness of the lesson adaptation scheme are investigated: the development of the educational material, the structure of the domain knowledge and the assessment of the learner under uncertainty. A connectionist-based structure is adopted for representing the domain knowledge and inferring the planning strategy for generating the lesson presentation from pieces of educational material. The learner’s assessment is based on relating learner’s behavior to appropriate knowledge and cognitive characterizations and on embedding the knowledge of the tutors on the learning and assessment processes into the system by defining appropriate fuzzy sets. The proposed neuro-fuzzy adaptation scheme is applied to a web-based learning environment to evaluate its behavior and reliability.