Analysis of students performance using learning analytics—a case study

Abstract

Utilization of digital tools has been increased enormously in our daily learning activity by generating data on a huge scale. This huge amount of data generation provides exciting challenges to the researchers. Learning analytics effectively facilitates the evolution of pedagogies and instructional designs to improve and monitor the students’ learning and predict students’ performance, detects unusual learning behaviors, emotional states, identification of students who are at risk, and also provides guidance to the students. Data mining is considered a powerful tool in the education sector to enhance the understanding of the learning process. This study uses predictive analytics, which help teachers to identify student’s at risk and monitor students progress over time, thereby providing the necessary support and intervention to students those are in need.