Data Analysis of Student Academic Performance Using Social and Academic Indicators

Abstract

Data analysis has become one of the most important emerging fields. This is due to the wide usefulness of this discipline in improving and enhancing many other arenas. Whether in industry, commerce, economy, psychology, or education, data analysis has proven its efficiency in providing users with valuable results to increase their level of achievement. The ability to effectively manage information and extract knowledge is now seen as a key competitive advantage for organizations. [1] Valuable knowledge could easily be extracted with the use of data analysis to develop every sector of every world economy [2]. In this paper, we have combined a set of data in the educational field with some computational, statistical, or analytical techniques to draw interesting conclusions. Based on data from Al Akhawayn University in Ifrane AUI, this paper analyzes and predicts the distribution of students by schools and majors, the variance in their GPAs based on different criteria, and predicts the GPAs (Grade Point Average) of next years’ students. In this regard, the hypotheses that the study tackles as a basis for the analysis are as follows:•Students are more interested in engineering majors than social Sciences•Female students are more academically achieving compared to their male peers•Female students have better academic conduct•Next years’ students are more likely to have better average GPAs