The week's pick
Random Articles
Reseach Article
Analyzing Educational Data through EDM Process: A Survey
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 136 - Number 5 |
| Year of Publication: 2016 |
| Authors: Tripti Dwivedi, Diwakar Singh |
10.5120/ijca2016908392
|
Tripti Dwivedi, Diwakar Singh . Analyzing Educational Data through EDM Process: A Survey. International Journal of Computer Applications. 136, 5 ( February 2016), 13-15. DOI=10.5120/ijca2016908392
Abstract
This paper presents the survey of student background history which helps academic planners in institute to give right direction to student. If the class of student is predicted in midsession of institute in final year then it will be easy for the academic planner to plan some important workshop for the enhancement of performance of student which helps it in placement at the end of academic session. In educational institute data mining techniques plays an important role in each activities of institute whether it is academic, cultural, examination and training and placement etc. in which Educational Data Mining which is a field of data mining helps a lot to find the actual filtered data in various field of department in institute. Hidden knowledge through data mining techniques is extracted from large database which helps to predict the pattern in such activities. It plays a great role in predictions of student data for placement and performance.
References
- Dutta, r. j. (june 2013). "A survey on educational data mining and research trends department". International Journal of Dtabase Management system .
- K.Yacef, R. a. (2009). "The State of Educational Data Mining". Journal of Educational Dta Mining .
- Kamber, J. a. (2000). "Data Mining: Concepts and techniques
- Kumar, J. (2015). "A Comprehensive Study of educational Data mining". IJEECSE .
- Mohod, S. R. (April 2014). "Quality Improvisation of Student Performance using Data Mining Techniques". International Journal of Scientific and Research Publication Vol 4 .
- Naqvi, S. a. (2006). "Factor affecting student's performance:ACase of Private College". Bangladesh e-Journal of Sociology,vol 3,no1 .
- Pal, B. K. (2011). "Mining Educational Data to Analyze Students Performance". IJACSA .
- Pratiwi, O. N. (2013). "Predicting student Placement Class using Data mining". 2013 IEEE International Conference on Teaching ,assesment and learning for Engineering(TALE), (p. 618). Bali Dynasty Bali Resort,Kutta Indonesia.
- Q.A.Al-Radaideh, E. a.-N. (2006). "Mining student data using decision trees". International Arab Conference on Information Technlogy(ACIT 2006). Yarmouk University Jordan.
- Rakesh Kumar Arora and Dr, D. B. (jul 2014). "Placement Prediction Through Data Mining". IJARCSSE
- S.Niramathi, U. a. (August 2013). "A Study on Student Data Analysis Using Data Mining Techniques". IJAECSSE
- S.Pal, U. a. (2011). "Data Mining :Aprediction of performer or underperformer using classification"(IJCSIT). IJCSIT .
- Vikas Chirumamilla, B. S. (2014). "A Novel approach to predict student placement Chance with Decision Tree induction". IJST .
- www.educationaldatamining.org. (n.d.).
- Chori, I. A. (2014). "An application of Educational Data Mining Techniquesfor scholorship Prediction". IJSEIA , 31-42.
- C.M.Vera, C. a. (feb 2013). "Predicting School Failure and drop out by using Data Mining Techniques". IEEE Journal of Latin America Learnin g Technology .
- http://en.wikipedia.org/wiki/Educational_data _mining.
- el-Halees, A. (2009). "Mining student's data to analyze e learning behaviour:A case Study".
- Jay Ruby, K. (2014). "Predicting the performance of students in higher education using Data Mining Classification:A Case Study. IJRASET .
- Ajay Shiv Sharma, S. P. (2014). "Placement preidction system using Logistic Regression". IEEE .
Index Terms
Keywords