Virtual co Learner: An approach against learner’s isolation (original) (raw)

Abstract

Adaptation and personalization of the information and instruction offered to the users in on-line e-learning environments are considered to be the turning point of recent research efforts. Collaborative learning may contribute to adaptive and personalized asynchronous e-learning. In this chapter authors intend to introduce the Virtual co Learner (VcL) that is a system designed on a basis of distributed architecture able to imitate the behavior of a learning companion who has suitable to the user’s cognitive and learning style and behavior. Matching human and simulated learners who have cognitive characteristics of the same type, one can find that learning procedure becomes more efficient and productive. Aiming to establish such VcL, one faces a number of questions. An important question is related to the user’s cognitive or learning characteristics diagnosis. Authors of this chapter have published work concerning learning style diagnosis based on Bayesian networks, and Fuzzy Cognitive Maps. Both are based on David Kolb’s learning cycles. Other questions concern the VcLs’ responses and reactions to learner, the evaluation of VcL’s influence to the learning procedure, and the optimization of VcL’s actions. Adaptive Educational Hypermedia Systems (AEHSs) in World Wide Web became a very active research field and the need of standardization of user assessment, instruction material and e-learning environments arose, as the continually augmenting research efforts lacked the interoperability dimension. VcL design takes under consideration such issues aiming to contribute to AEHS efficiency

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