Abstract
Currently there is an increasing interest in data mining and educational systems, making educational data mining as a new growing research community. Higher education, throughout the world is delivered through universities, colleges affiliated to various universities and some other recognized academic institutes. The main objective of higher education institutes is to provide quality education to its students. Indian education sector has a lot of data that can produce valuable information which can be used to increase the quality of education. Good prediction of student’s success in higher learning institution is one way to reach the higher level of quality in higher education system. In this paper we analyzed the potential use of data mining in education section and survey the most relevant work in this area. Data Mining can be used for dropout students, student’s academic performance, teacher’s performance and student’s complaints. As we know large amount of data is stored in educational database, so in order to get required data and to find the hidden relationship, different data mining techniques are developed & used. Various algorithms and data mining techniques like Classification, Clustering, Regression, Artificial Intelligence, Neural Networks, Association Rules, Decision Trees (CART and CHIAD), Genetic algorithms, Nearest Neighbor method etc. are used for knowledge discovery from databases and helps in prediction of students academic performance. In future work we can apply different data mining techniques on an expanded data set with more distinct attributes to get more accurate results.
Highlights
Every year, educational institutes admit students under various courses from different locations, educational background and with varying merit scores in entrance examinations
Applying data mining (DM) in education is an emerging interdisciplinary research field known as educational data mining (EDM)
Educational Data Mining (EDM) can be defined as the application of data mining (DM) techniques to this specific type of dataset that come from educational environments to address important educational questions
Summary
Educational institutes admit students under various courses from different locations, educational background and with varying merit scores in entrance examinations. Analyzing the past performance of admitted students would provide a better perspective of the probable academic performance of students in the future. This can very well be achieved using the concepts of data mining. Educational data mining is concerned with developing new methods to discover knowledge from educational database. We can use the data mining in educational system as: predicting drop-out student, relationship between the student university entrance examination results and their success, predicting student's academic performance, discovery of strongly related subjects in the undergraduate syllabi, knowledge discovery on academic achievement, classification of student’s performance in computer programming course according to learning style, investing the similarity & difference between schools.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
