Mobile Learning Environments for Diverse Learners in Higher Education

ML (mobile learning) has extended e-learning to a new paradigm of "anywhere, anytime learning" [1][2]. The potential of ML in individualization of learning process for the diverse learners [3] should be optimized as learners learn in different ways and usually have their own styles and preferences for learning environment [4]. 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. Such matrices capture and represent, for each student, various characteristics such as knowledge and traits in an individual learner model. Subsequently, when ML is delivered in an interactive environment, with the right tools and support, studies show that students can retain significantly more and achieve a greater level of skill and performance. The secret and the key to realizing these gains is the environment. However, such matching is still in its infancy in Malaysia higher education. The purpose of this study is to identify the main m-learning environment constructs for learners in Malaysia higher education. A survey using questionnaires will be conducted to the IT experts and university students in Malaysia. The development of the survey items relies extensively on literature pertaining to high-quality higher education, expert content validation techniques and learners' learning styles by Myer-Briggs Type Indicator (MBTI). Expected result includes a matrix recommendation matching the m- learning environment constructs with students' MBTI learning styles.