Predictive Learning Analytics (PLA) for Higher Level: A Systematic Literature Review

Abstract

The purpose of this study is to present a systematic analysis of the research work on predictive learning analytics (PLA). This study collects information on the predictive learning analytic benefits and its challenges in higher education level. Empirical research and literature review on learning analytics and predictive modelling were collected. The results show the benefits of predictive learning analytics (PLA) which helps higher level education utilize data effectively especially in decision making process. It also helps in facilitate evaluation of students in learning, predict student’s performance, identify student’s emotional, pattern, leaning characteristic as well as student’s engagement. Despite of rapid embrace of PLA, few challenges has been identified related to data tracking, collection, evaluation, analysis; lack of connection to learning sciences; optimizing learning environments, and ethical and privacy issues. The findings of this study enable educator and education institutional to improve teaching and learning in higher education.