Augmented Transfer of Knowledge in eLearning Materials based on Associative Relevance
Author(s) -
Gufran Ahmad
Publication year - 2015
Publication title -
international journal of emerging technologies in learning (ijet)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.454
H-Index - 24
eISSN - 1868-8799
pISSN - 1863-0383
DOI - 10.3991/ijet.v10i6.4871
Subject(s) - relevance (law) , computer science , knowledge transfer , associative property , process (computing) , transfer of learning , associative learning , field (mathematics) , frontier , knowledge management , artificial intelligence , psychology , cognitive psychology , mathematics , history , archaeology , law , pure mathematics , operating system , political science
Studies for enhancement of learning approaches in the field of eLearning have been molded beyond frontier. An improved transfer of knowledge can cultivate considerably outstanding knowledge-sharers and better learners as well. In this study, we conducted experiments to assemble samples as data from participants who joined in this research. We investigated the assembled data to confirm our hypothesis that the eLearning materials based on associative relevance had substantially boosted transfer of learning process. The analyzed data and produced ingenious specifics evidenced that there were improved transfer of knowledge in eLearning based on associative relevance.
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