Data analytics as a tool for smart learning

Abstract

Modern learning environments are characterized by the pervasive use of technology. Data from electronic submissions, student achievement and attendance records, student library/lab interactions, financial profiles, social media style interactions between students and teachers and content processing/delivery tools like TurnItIn, Moodle, and the likes is huge and growing fast. This big data can be exploited to profile learners so that content delivery is tailored for the particular needs and abilities of the individual learner. Educators always sought information about the learner to personalize the learning experience and make content delivery more effective and focused[2]. Learning analytics is concerned with using the multisource data on the learner and the surrounding environment/context for an optimized learning experience that is effective, personalized and less stressful and conducive to improved achievement. Learning analytics is based on applying data mining tools to student data footprint to ascertain user characteristics relevant to the educational process and adjust the teacher-student interaction accordingly[3]. The potential of data analytics is well recognized and is being increasingly exploited in diverse fields like finance, health, commerce, politics and much more. Education is no exception. We are already witnessing the expanded use of data analytics in the learning process for school, higher and continuing education and training. As elsewhere, one can foresee an array of issues that need to be tackled, including privacy, ethical and language considerations to steer the data analytics augmented learning process in the right direction[1]. With the growing emphasis on elearning and digitizing education in Palestine, one can see the potential of learning analytics in the local setting and the need to begin addressing this paradigm by teams of experts versed in both education and data analytics for the best results in the Palestinian context.