J. Today’s Ideas - Tomorrow’s Technol.

A Review on Prediction of Academic Performance of Students at-Risk Using Data Mining Techniques

Preet Kamal, Sachin Ahuja

KEYWORDS

Data Mining (DM), Educational data mining (EDM), Education System

PUBLISHED DATE June 2017
PUBLISHER The Author(s) 2017. This article is published with open access at www.chitkara.edu.in/publications
ABSTRACT

Educational data mining is the procedure of converting raw data collected from educational databases into some useful information. It can be helpful in designing and answering research questions like performance prediction of students in academics, factors that affect the students’ performance, help the teachers in understanding the problems faced by the students to understand the course content and complexity of the subject taken so that the teachers can take timely action to control the dropout rate. This also includes improving the teaching learning process so that the interventions can be taken at the right time to improve the performance of the student. This paper is the review of the research work done in the field of educational data mining for the prediction of students’ performance. The factors that influence the performance of the students i.e. the type of classrooms they attend such as traditional or on-line, socio-economic, educational background of the family, attitude toward studies and challenges faced by the students during course progress. These factors leads to the categorization of the students into three groups “Low-Risk”: who have High probability of succeeding, “Medium-Risk”: who may succeed in their examination, “High-Risk”: who have High probability of failing or drop-out. It elaborates the different ways to improve the teaching learning process by providing the students personal assistance, notes, class-assignments and special class tests. The most efficient techniques that are used in educational data mining are also reviewed such as; classification, regression, clustering and and prediction.

INTRODUCTION

Educational Data Mining (EDM) is the application of Data Mining (DM) and its objective is to analyze the different types of data in order to resolve educational research issues [16]. Data Mining is the process of extracting useful and important information from data sets. It is being used by organizations, scientists and governments from last so many years to collect data like airline passenger records and record of census data [2]. The volume of educational data has increased with advancement of technologies. It can be handled using Data Mining techniques. The educational institutes are also getting automated with the help of advanced technologies.

The educational research in Data Mining also contributes a lot to the predictive technologies. Data Mining is set up on the theory that the historic data retains the hidden and unknown information observed as a challenging task in data prediction. Data analysis is one way of forecasting the growth or decline in academic performance. The use of internet and e-learning in the field of education has facilitated the students. On the other hand offline education- is the medium to exchange knowledge and develop skills by faceto-face interaction. The tutor can easily understand the behavior of the student towards his studies. The data mining techniques can be applied to such data like students’ behavior towards his studies, performance in their academics, family background and the data collected form students in classroom interactions. Such data help to create student models. E-learning and Learning Management System (LMS) is the combination of online instruction and communication that collaborates administration and reporting tools. Intelligent Tutoring (ITS) and Adaptive Educational Hypermedia System (AEHS) acquire background knowledge about teaching strategy and student behavior are few examples of student models. [17].

Page(s) 30–39
URL http://dspace.chitkara.edu.in/jspui/bitstream/123456789/5/1/jotitt.2017.51002.pdf
ISSN Print : 2321-3906, Online : 2321-7146
DOI 10.15415/jotitt.2017.51002
CONCLUSION

The experiments have been carried out in open universities in countries other than India. The research work done in this field is especially related to subjects like psychology, mathematics, history and home science. Very few focused on the technical courses like : computers. Majority of the studies conducted are predicting the performance of the students based on the demographic, academic and social factors alien to the Indian environment. Since Indian culture and living style is different, it demands a different study to exactly relate to its educational system. There is a need to further explore the Indian education system so that the factors that affect the students performance can be studied according to the Indian scenario.

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