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In an educational system, a large amount of data is kept. This data may be students’ data, alumni data, teachers’ data, non-teaching staff data, resource data, and so on. Educational data mining is used in discovering the patterns in these data for decision-making(Edin Osmanbegovic, 2012).
Educational data mining can answer a lot of questions from the patterns obtained from student data, questions such as:
1. Who are the students at risk of failing in the future?
2. What is the quality of student participation?
3. Who are the students likely to drop a course?
4. What are the chances of student gaining promotion to the next class
5. Which courses should a department offer to attract more students?
6. How many students should be accepted into the department every session.
The results of educational data mining can be used by different members of the educational system such as the examiners, teachers, security officers and the students. Students can use them to identify the activities, resources and learning tasks needed to improve their learning. Teachers can use them to get more objective feedback, to differentiate the stronger students from the weaker students and to guide the weaker students (also considered as students at risk) and help them to succeed. The security officers can use the result of educational data mining to identify and locate students in the case of an emergency. The result of educational data mining can also be used by the institution to identify the most commonly made mistakes and to organize the contents of the institution’s website in an efficient way.
There are two types of educational systems:
A. Traditional education system: The traditional education system involves direct contact between the students and the teacher. Students’ record which include information such as attendance, and grades may be kept manually or digitally. The performance of students is a measure of this information.
B. Web based learning system: The web based learning system is also known as e-learning. It is becoming the more expedient approach towards education and it has become more popular as the students can learn from any place without any time constraint. In the web based education system, various data about the students are automatically collected through logs.
This project work describes a model that predicts the academic performance of students in a traditional education system. The following development will help us to understand the relevance of this model because reducing the number of students who fail is the main aim of this project work. Since inferior students are also enrolled into the institutions, the results of the institutions are depreciating when it comes to good grades therefore if we know in advance which students are likely to fail, the institutions or the teachers can take the necessary steps towards improving the results. This will help in improving the quality of graduates that are produced yearly from these institutions ( R.R. Kabra and R.S Bichkar, 2011).
1.1.Background of the Study
Since one of the goals of tertiary institutions is to contribute to the improvement of the quality and standard of higher education, the success in the creation of human capital has been a subject of continuous analysis. Hence the prediction of students’ success is very important to these higher education institutions, because the purpose of any teaching process is to meet students’ educational needs and enhance overall student’s academic success. In this regard, important data and information are gathered on a regular basis after which they are used in the prediction of students’ academic performance (EdinOsmanbegovic, 2012).
Measuring and predicting the academic performance of students has been a challenging task since students’ academic performance depends on diverse factors such as personal, socioeconomic, psychological and other environmental variables. But the prediction of student’s performance is a very important endeavor as it helps the student and teachers to minimize poor academic performances and produce better educated and enlightened students in order to make the society a better place. With the help of performance prediction, a failing student can be identified and helped by putting all the factors affecting the student into consideration and providing solutions to counter this factors so as to facilitate better performance (Brijesh Kumar Bhardwaj and Saurabh Pal, 2011).
1.2. Statement of the Problem
Without adequate measures to curb the existing problem of persistent students’ failure, it will continue to remain a major problem for higher institutions. But with the analysis of the factors which are socioeconomic, psychological and environmental, a headway can be made towards curbing the problem of student failure.
1.3. Aim and Objectives of the Study
The aim of this project is to predict a student’s performance using the decision tree method.
The specific objectives are:
1. To identify various factors that affect the performance of students in their academic endeavors.
2. To use the identified factors as well as the student’s past performance to predict the future performance of the student.
3. To develop a model which can predict student’s academic performance using decision tree method.
1.4. Scope and limitation of the Study
This project work titled STUDENTS ACADEMIC PERFORMANCE PREDICTION USING DECISION TREE attempts to analyze those factors that affect the students academically. Furthermore, this work predicts the future academic performance of students but does not automatically address these problems as the tutors and teachers and even the students themselves still need to take steps towards curbing the performance problem by eliminating this factors themselves.
1.5. Significance of the Study
1. To help teachers and tutors identify weak and strong students so teachers can lay more emphasis on instructions and procedures when dealing with the weak students
2. To help the students identify and eliminate those factors either found in the student himself or the school or the society.
3. To help the tutors and teachers find solutions to the problems affecting the weaker students so as to enhance overall academic performance.
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