A Relative Analysis of Data Mining Approaches for Student’s Academics Performance Prediction

Data is exploding as a result of technological innovation. Consequently, there has been a perceived need for enhanced analytical tools that can aid in the extraction of pertinent data, patterns, and correlations for decision-making. The educational sector shares the same reality. Approaches of Learning data and educational data mining have been applied to the analysis of educational data. Predicting student performance to influence educational outcomes is one of the most important goals of educational research. The goal of this field’s research is to discover the approaches and procedures that can enhance prediction as well as the qualities that may be utilised to evaluate performance or create predictions. In order to establish the present state of new art and identify approaches, traits, and metrics utilised in forecasting student achievement using educational data mining and learning data, this paper will undertake a systematic literature analysis.