Towards a Model of Automated Adaptive Content Delivery Training Utilizing Fuzzy Logic

G. Vert, A. Phadnis, R. Yakkali, and X. Yu (USA)


Adaptive Learning, Fuzzy Logic, Fuzzy theory, Presentation Modality


Rapid advances in internet technologies have opened gateways for specialized educational opportunities. These range from online distance learning for individuals as well as for those who want to learn a certain skill set, courses for which may not be offered in traditional educational institutions. Although these web based courses have become major global education contributors in overcoming the basic education challenges of the traditional classroom environment, they do not consider the fact that each individual can learn differently. Some students are auditory learners, and some may be visual learners while others may be kinesthetic learners. Adaptive learning systems address this aspect of different learning styles and the need to customize learning instruction. Such systems provide an innovative method of instruction that adapts to the learner’s unique learning style. A novel approach to adaptive learning is presented that utilizes learning modalities of instruction tailored to individual needs. At the heart of this approach is a fuzzy neural network (FNN) that evaluates comprehension and makes instructional modality selections.

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