NDLI: Predictive analytics using data mining technique

Content Provider	IEEE Xplore Digital Library
Author	Gulati, H.
Copyright Year	2015
Description	Author affiliation: Comput. Sci. & Eng., Amity Univ., Noida, India (Gulati, H.)
Abstract	Dropout rates for students in correspondence and open courses are on increase. There is a need of analysis of factors causing increase in dropout rate. The discovery of hidden knowledge from the educational data system by the effective process of data mining technology to analyze factors affecting student drop out can lead to a better academic planning and management to reduce students drop out from the course, as well as can generate valuable information for decision making of stake holder to improve the quality of higher educational system. Data mining technique can be used for analysis and prediction. In this seminar I have used real data from a study center of Indira Gandhi National Open University. I have collected data from various sources like university database, survey form, etc. Various steps of mining is applied to deduce useful result. Various scenarios were compared and there accuracy was calculated. This study presents the work of data mining in predicting the drop out feature of students. This paper presents analysis of data set using data mining algorithms. After analysis the outcome will be the major factors that affect student dropping out of the open courses the most (dropout rate). Before applying classification algorithms some feature selection algorithms are also used so as to get refined prediction results. Such analysis and prediction information will help college management and teachers to make necessary changes for imparting better education. Mining of useful knowledge can be done by using many other mining techniques like association, clustering. Tool used for feature selection and mining is weka.
Starting Page	713
Ending Page	716
File Size	125461
Page Count	4
File Format	PDF
ISBN	9789380544151
e-ISBN	9789380544168
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-03-11
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Bharati Vidyapeeth University, New Delhi
Subject Keyword	Prediction Data Mining Classification algorithms Data mining Weka EDM Accuracy Databases Education Classification Prediction algorithms Decision Trees Decision trees
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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