INSPECTION OF DATA MINING TECHNIQUES IN HIGHER EDUCATION SYSTEM

Sunil Kumar Tiwari, Archi Dubey

Abstract


Higher education is essential for the growth and development of a country. Higher education has been under incomparable pressure to provide better access to our institutions. One of the key points of the higher education is the increase in education data explosion. This information is fast growing without the management and organization facilities. We believe that managing this huge amount of information is a daunting task. However, with new strategies and tools of data mining, we can easily process large quantities of information generated in business processes and find useful knowledge and information. Data Mining is a technique for extracting prediction information hidden from large databases. It is a powerful technology with significant potential that helps universities or higher education institutions to focus on key information in their data warehouses. In this paper we focus on the various data mining techniques that are useful for solving various problems happening in higher education of India.


Keywords


Higher Education, Data mining, Clustering, Decision Tree, prediction

Full Text:

PDF

References


Sunil Kumar Tiwari, Archi Dubey, Concise Discussion on Growth of Higher Education in India: PARIPEX, Volume-8 | Issue-5 | May-2019 | PRINT ISSN No. 2250 - 1991

T.Thilagaraj, Dr.N Sengottaiyan, A Review of Educational Data Mining in Higher Education System : Proceedings of the Second International Conference on Research in Intelligent and Computing in Engineering pp. 349–358 DOI: 10.15439/2017R87 ACSIS, Vol. 10 ISSN 2300-5963

K. R. Kavyashree, LakshmiDurga – “A Review on Mining Students Data for Performance Prediction” - International Journal of Advanced Research in Computer and Communication Engineering Vol. 5,Issue 4, April 2016.

G. Gray, C.McGuinness, P.Owende – “An Application of Classification models to predict learner progression in tertiary education” - Advance Computing Conference (IACC), 2014 IEEE International, IEEE, 2014, pp. 549–554.

Amirah Mohamed Shahiria, WahidahHusaina and Nuraini Abdul Rashida – “A Review on Predicting Students performance using Data Mining Techniques” - The Third Information Systems International Conference, Procedia Computer Science 72( 2015 ) 414 – 422.

Khushbu N.Shah, Misika R. Patel, Neha V. Trivedi, Priyanka N. Gadariya, Richa H. Shah, Ms. Nehal Adhvaryu, Study of Data Mining in Higher Education-A Review, International Journal of Computer Science and information Technologies, Vol. 6 (1) , 2015, 455-458.

Ajinkya Kunjir, Poonam Pardeshi, Shrinik Doshi, Karan Naik, Recommendation of Data Mining Technique in Higher Education, IJCER, ISSN (e): 2250 – 3005 Volume, 05 Issue, 03 March – 2015 .

TriptiDwivedi, Diwakar Singh – “Analyzing Educational Data through EDM Process: A Survey” - International Journal of Computer Applications (0975 – 8887) Volume 136 – No.5, February 2016.

Abdulmohsen Algarni - “Data Mining in Education” - (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 7, No. 6, 2016

Heba Mohammed Nagy, Walid Mohamed Aly, Osama FathyHegazy – “An Educational Data Mining System for Advising Higher Education Students” - International journal of Computer, Electrical, Automation, Control and Information Engineering Vol:7, No:10, 2013.

Monika Goyal and Rajan Vohra - “Applications of Data Mining in Higher Education” - IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 2, No 1, March 2012.

U. K. Pandey and S. Pal - “A Data mining view on class room teaching language” International Journal of Computer Science Issue, Vol. 8, Issue 2, pp. 277-282, ISSN:1694- 0814,2011.

Dr. MohdMaqsood Ali - “Role of data mining in education sector” - International Journal of Computer Science and Mobile Computing Vol. 2, Issue. 4, April 2013.

Morgan Kaufmann Publishers An Imprint of Elsevier Science “Data Mining Concepts and Techniques” ISBN 81-7867-023-2 ,Chapter 7,p.279 Date:11/12/2014


Refbacks

  • There are currently no refbacks.