Predicting Student Academic Performance in KSA using Data Mining Techniques

Abstract

The main objective of higher education institutions is to provide quality education to its students. One way to achieve highest level of quality is to identify factors affecting academic performance and then trying to resolve weakness of these factors. The specific objective of the proposed research work is to find out if there are any patterns in the available data (student and courses records) that could be useful for predicting students' performance. The study involved a sample of 150 students collected from Najran University students in Saudi Arabia. The data was captured and arranged with the use of statistical package for social sciences (SPSS) and data mining tool (clementine). Developing an accurate student's performance prediction model is challenging task. Data mining based model were used to identify which of the known factors can give an early indicator of expected performance. This paper employs both feature reduction and classification technique to reduce error rate. The experimental results reveal significant relationships between including both practical work and assignments in course and its success rate. But, on the other hand the number of given assignment has a negative impact on course academic performance. In context of factors affect student academic performance, the most affecting factor is student attendance in class in addition to final exam and mid exam grades.

A Comparative Study of Engineering Students Pedagogical Progress

“…Further five courses were evaluated to predict the performance of graduation that did not lead to a better accuracy. Nawal Ali Yassein et al [5] have proposed patterns in the available student and courses records to predict students" performance. Statistical package for social sciences (SPSS) and data mining tool (clementine) were used for experimentation purpose.…”

“…Data mining is a computational study of data processing which has been successfully functional in many areas that intend to extract useful knowledge from that data [5]. There are various techniques of data mining that are operate-able on large volumes of data to find out hidden patterns and their relationships helping in decision making for different applications such as Artificial Intelligence, Business Management, Decision Support, Machine Learning, Market Analysis, and Statistical and Database Systems [6], [9].…”

“…Among others, classification is a data mining technique, particularly, which plots data into predefined classes or groups [5], [9]. Classification is specifically used for predicting the unknown class label of data objects [16].…”

“…Predicting and enhancing students learning has become more challenging in order to improve student"s grades and thus benefit educational institutes in adaptation of different learning strategies [5].…”

“…There have been already many data mining methods applied in the field of education at multiple levels. So many parameters to analyze and track student pedagogical progress have been undertaken using data mining techniques at various levels: at a training system level to predict whether selected or specific knowledge/skills are mastered, at a course level or degree level to predict whether a student will be capable to pass a course or a degree, or to predict their marks [5]. The present study aims to initially identify and investigate the students score based upon pre-final or prelim marks throughout the academic session and finding ways to improve student performance.…”