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ML (Mobile Learning) has extended e-learning to a new paradigm of "Anywhere, anytime learning". The potential of ML in individualization of learning process for the diverse learners should be optimized as learners learn in different ways and usually have their own styles and preferences for learning environment. Research in ML should include of adaptive features to enable more personalized and successful learning outcomes for students. Matching the main m-learning environment constructs with the learners' preferred learning styles offers an advanced form of learning environment that attempts to meet the needs of different students.
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