Dynamic Content Selection Based On An Associative Semantic Processing Network

Uniqueness of cognitive human thinking stays a secret of unrevealed natural creation. Technological intelligence has tried to mimic or follow such operation to form an even more brilliant system. This research proposes a method of e-learning or distance learning system with dynamic content nomination for each user that correspond to their learning reaction. Done by the theory of human memory or spreading activation network-SAN, the proposed e-learning system employs this human cognitive mechanism (SAN) with the system processing scheme. The system procedure with in time factors of users including system input, user reaction, service event, and content medium are processed in order to evaluate and provide most suitable advices, learning contents or learning activities for each user individually. While the user goes through the individually designed learning content, the system continues utilizing SAN to analyze in-time learning condition and furnish course agenda toward the learning objectives.