Enticing Correlation between Motivation and Self-Regulation: A Novel Approach for Academic Excellence

• Published in: International journal for research in applied science and engineering technology 2022-11, Vol.10 (11), p.949-954
• Main Authors: Kharb, Latika, Chahal, Deepak
• Format: Article
• Language: English
• ISSN: 2321-9653; 2321-9653
• DOI: 10.22214/ijraset.2022.47485

Today, we can easily say that there is no limit to the size of the data that exists in the real world-it can be in tens, hundreds, thousands, billions or even trillions of dimensions. However, not all dimensions are vital or relevant for a more detailed analysis. The key objective of educational data mining is to analyze educational data to solve educational and research problems. Our research in this paper focuses primarily on identifying relevant characteristics that can help determine the academic performance of students. The selection of features carried out as data preprocessing techniques keeping in mind the key idea to eliminate irrelevant and redundant features and thus selecting the optimal characteristics that can improve the overall accuracy of the model. The characteristics selected through the selection of functions can help to predict the academic performance of the student in several colleges and universities, which is one of the most imperative contemplations by interested parties to build and maintain a quality system. Although there are several studies that determine the factors that affect the academic performance of students, there is still a gap in existing research that focuses on the psychological factors of a student. The document is structured as follows. Section two contains a brief explanation about the related work in this field. In section three, we have discussed the adopted methodology that presents the data set, the feature selection algorithms, and the characteristic evaluation approach. Section four presents the configuration and experimental results and section five focuses on the conclusion and future scope.