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Collaborative Mobile Learning: A Systematic Literature Review
Abstract
Mobile learning (ML) fosters engaging personalized learning where students can optimize their understanding and learning gratification via wireless mobile devices. Although there are studies conducted on the research trends on ML, not much studies were conducted on the cutting-edge researches pertaining to Collaborative ML. Collaborative ML is significant because it promotes active learning and cooperative skills. This paper aims to analyze the state-of-the-art research conducted in the span of five years for identifying the trends and focuses in Collaborative ML. The systematic literature review is conducted based on Knowledge Discovery Database model capitalizing data mining as the main research methodology. Findings were based on top ten Impact Factor Journals on Educational Technology indexed in the ISI Web of Knowledge. The SLR discovered ten main areas that were discussed pertaining to Collaborative ML which are Motivation, Students' Acceptance, Pedagogy, Assessment, Tools, Social Networking, Gaming, Knowledge Sharing, Special Needs and Communications.
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