Abstract
Successful prediction of student performance has significant impact to many stakeholders, including students, teachers and educational institutes. In this domain, it is equally important to have accurate and explainable predictions, where accuracy refers to the correctness of the predicted value, and explainability refers to the understandability of the prediction made. In this systematic review, we investigate explainable models of student performance prediction from 2015 to 2020. We analyze and synthesize primary studies, and group them based on nine dimensions. Our analysis revealed the need for more studies on explainable student performance prediction models, where both accuracy and explainability are properly quantified and evaluated.