Improving Method of Evaluating Semantic Filtering for Human Computer Interaction in an Adaptive Collaborative Learning Environment
A. A. Adigun *
Department of Information and Communication Technology, Osun State University, Osogbo, Nigeria.
A. O. Osofisan
Department Computer Science, University of Ibadan, Ibadan, Nigeria.
O. Longe
Department of Computer Science, University of Ibadan, Ibadan, Nigeria.
M. O. Kolawole
Department of Electrical and Electronics Engineering, Federal University of Technology, Akure, Nigeria.
*Author to whom correspondence should be addressed.
Abstract
Human Computer Interaction Semantic filtering techniques are used in learning environment to track problems in collaborative systems. However, as noted in Adigun et al. [1], when sharing and dynamism are promoted, a problem of redundancy and integrity appeared not to have been well addressed. An improved ASF-based method of evaluating semantic filtering for social network systems in collaborative learning environment is developed, which assisted participants to achieve greater levels of performance with information sharing from other collaborators, as well as in reusing ideas across the period of collaboration.
Keywords: HCI, semantic filtering, adaptive collaborative system, participant, information sharing and reuse.