Learning Analytics Lens: Improving Quality of Higher Education

With digital revolution expansion and a rapid change in the technologies, educational data is increasing at a swift pace. Learning analytics (LA) turns out to be a powerful tool for improving learning and teaching practices. Learning analytics uncover hidden patterns, correlation, and other insights about learners and educators in educational big data that leads them to stay agile, better outcomes, and employability. This literature review aims to categorize such measures of data-driven improvement. A comprehensive review of Learning Analytics (LA) and Educational Data Mining (EDM) and significant techniques in higher education was conducted. Analysis of the research questions, methodology, techniques, learning environment, associated projects, and findings of various published papers is done and is accordingly categorized. Analysis of various reviews on the development and growth of LA in higher education in various countries is also done. The results provide a comprehensive background for understanding current knowledge on LA and EDM and its impact on both learner and instructor in the various learning environment. The results showed that in HEIs, where LA has been implemented aimed at better assessing and predicting learner's performance. It has also helped in monitoring and motivating them, discovering undesirable learning behaviors and their emotional states, help educators and administrators to unlock big data potentials, and making quicker datadriven decisions.