A Neuro-Fuzzy Model for E-Learning Activities - Isiaka, Rafiu Mope
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Existing Learning Management Systems (LMS) miss-out the important roles of Instructional design (ID) models for qualitative lessons that could guarantee learning.This is because contemporary LMS provide a mere plane and passive platform for content authoring, thus becomes vulnerable for poor instructional design. This work demonstrates an effort to ameliorate this limitation by extending the IEEE Learning Technology System Architecture (LTSA) with ID design processes. A neuro-fuzzy model of learners' traces on the platform is used to evaluate the extended architecture.

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Produktbeschreibung
Existing Learning Management Systems (LMS) miss-out the important roles of Instructional design (ID) models for qualitative lessons that could guarantee learning.This is because contemporary LMS provide a mere plane and passive platform for content authoring, thus becomes vulnerable for poor instructional design. This work demonstrates an effort to ameliorate this limitation by extending the IEEE Learning Technology System Architecture (LTSA) with ID design processes. A neuro-fuzzy model of learners' traces on the platform is used to evaluate the extended architecture.
Autorenporträt
Isiaka, Rafiu Mope Ph.D. is a lecturer at the Department of Computer Science, Kwara State University, Malete, Nigeria. He had his Ph.D in 2015 at the Ladoke Akintola University of Technology, Ogbomoso, Nigeria in the Department of Computer Science and Engineering. His research interest include soft computing, data mining and information security.