Learning Analytics to Support Dissimilar Learners in Mathematics: A Scientific and Exploratory Research Mapping

The present study focuses on exploring how Learning Analytics (LA) and Dispositional Learning Analytics (DLA) can be used to support dissimilar learners’ needs in mathematics. For this purpose, a scientific mapping methodology is used via bibliometric and content analytic methods. The results from this analytics and evaluative scientific mapping showed that Learning and Dispositional Learning Analytics provide teachers and educational stakeholders a valuable insight into students learning. DLA along with trace data can be used to determine dissimilar/struggling learners and their needs in mathematics and in general. The implications of the results are further discussed from the perspective of dissimilar learners in mathematics and their environment and how they can be further supported by the outcomes of learning analytics and dispositional learning analytics based on high esteemed research publications.