A mobile context-aware framework for supporting self-regulated learners

Abstract

We have previously developed a mobile context-aware learning schedule (mCALS) framework, which provides a potential effective learning approach for supporting self-regulated students. This framework uses the learner's learning schedule to retrieve their location and available time contexts in order to suggest appropriate materials to them based on these, at the time of usage. The user's learning styles and knowledge level contexts are also considered. A suggestion mechanism selects appropriate learning objects to students from a learning object repository. Our interview study has been conducted and the purpose of this paper is to present the data analysis relating to participants' learner characteristics and their usage of learning schedules for supporting time management of studies as well as their views regarding m-learning. Results showed that 1) participants who closely followed their learning schedules were learners with self-regulated learning characteristics, 2) the act of planning study-related events had helped self-regulated participants to motivate their studies, and 3) a strong significant positive correlation was obtained between participants who were more enthusiastic to m-learning and those who enjoyed studies more. The results corroborate that the learning schedule within our mCALS framework can be used successfully as a motivating learning approach for supporting self-regulated learners.