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M-Learning Generations and Interview Study Results of a Mobile Context-Aware Learning Schedule Framework
Abstract
Mobile learning applications can be categorized into four generations – ‘non-adaptive’, ‘learning-preferences’-based adaptive, ‘learning-contexts’-based adaptive and ‘learning-contexts’-aware adaptive. The research on our Mobile Context-aware and Adaptive Learning Schedule framework is motivated by some of the challenges within the context-aware mobile learning field. These include being able to create and enhance students’ learning opportunities in different locations by considering different learning contexts and using these as the basis for selecting appropriate learning materials for students. The authors have adopted a pedagogical approach for evaluating this framework – an exploratory interview study with potential users consisting of 37 university students. The authors targeted primarily undergraduate computing students, as well as students within other departments and postgraduate students, so that a deep analysis of a wider variety of users’ thoughts regarding the framework can be gained. The observed interview feedback gives us insights into the use of a pedagogical m-learning suggestion framework deploying a learning schedule subject to the five proposed learning contexts. Their data analysis is described and interpreted leading to a personalized suggestion mechanism for each learner and each scenario, and a proposed model for describing mobile learning preferences dimensions.
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