Learning Analytics in Mathematics: A Systematic Review

Abstract

Learning analytics (LA) is a useful approach in helping teachers to interpret the data obtained from students. Applying LA in Mathematics is also an effective approach for teachers to understand their students in depth. The objective of this systematic review is to look at LA applications and their benefits in teaching and learning Mathematics. Systematic review allows researcher to perform a clear examination of LA and Mathematics using systematic and explicit methods. The PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) approaches that cover resources from Scopus and Web of Science are applied in implementing a systematic review process, selection criteria and exceptions. As a result, 30 studies which related to LA and Mathematics have been reviewed. Review findings show that the LA approach in Mathematics is frequently applied in improving the quality of the teaching and learning process. In this context, the improvement of the quality of teaching is seen through the improvement of the quality of learning materials, the ability to see the development of learning, and the improvement of student attitudes and behaviors towards Mathematics. LA’s benefits in Mathematics education allow teachers to predict student achievement and the risk of dropout of students in learning. Proposed future studies should highlight qualitative studies or mixed methods in support of LA application in Mathematics. Applying a game-based approach (GBL) that has the potential to make the learning process more positive and effective by applying technology is an approach that can be explored in leveraging LA in Mathematics.