• Md Anoosh
• Abin
• Naweed

In recent years the amount of data stored in an educational database is growing rapidly. The stored database contains hidden information which if used aids improvement of student’s performance and behavior. In this paper predictive modeling approach is used for extracting this hidden information. Data is collected, a predictive model is formulated, predictions are made, and the model is validated as additional data becomes available. The predictive models will help the instructor to understand how well or how poorly the students in his/her class will perform, and hence the instructor can choose proper pedagogical and instructional interventions to enhance student learning outcomes. The implementation is done in Hadoop framework with Map Reduce and Revolutionary R Enterprise RRE.

Data collection, prediction, Hadoop, Map Reduce.

"A BIG DATA APPROACH FOR CLASSIFICATION AND PREDICTION OF STUDENT RESULT USING MAPREDUCE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.79-82, May-2019, Available :http://www.jetir.org/papers/JETIRCI06015.pdf

"A BIG DATA APPROACH FOR CLASSIFICATION AND PREDICTION OF STUDENT RESULT USING MAPREDUCE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp79-82, May-2019, Available at : http://www.jetir.org/papers/JETIRCI06015.pdf