• Prasanna M. Kothawale

Abstract: All the researches referred in the present review have revealed some significant areas in the field of education where prediction with data mining has provided systematic valuable information on various aspects of students and education related issues including management and policy designing. It is found that there are specific issues of concern; sometimes they are institution specific that needs to be addressed for better results. Attributes like emotional intelligence, self-management, work experiences and life experiences are also important attributes in gauging and lifting student’s performance in the academics. One author has recommended open source Waikato Environment for Knowledge Analysis (WEKA) software for convenient data preprocessing, cleaning and handling missing values, and this is very common application software that can be used in each school / college for initial collection of data.

Data Mining, EDM, (WEKA) software

" Literature Survey on Educational Data Mining ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 2, page no.622-626, February-2019, Available :http://www.jetir.org/papers/JETIR1902195.pdf

" Literature Survey on Educational Data Mining ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 2, page no. pp622-626, February-2019, Available at : http://www.jetir.org/papers/JETIR1902195.pdf