UGC Approved Journal no 63975

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 6 Issue 2
February-2019
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIRAE06102


Registration ID:
198757

Page Number

439-441

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Title

Tracking and Predicting Student Performance Using Machine Learning

Abstract

Educational Data Mining (EDM) and Learning Analytics (LA) research have emerged as interesting areas of research, which are unfolding useful knowledge from educational databases for many purposes such as predicting student’s success. The ability to predict a student’s performance can be beneficial for actions in modern educational systems. Existing methods have used features which are mostly related to academic performance, family income assets, while features belonging to family expenditures and students personal information are usually ignored. In this paper, an effort is made to investigate aforementioned feature sets by collecting the scholarship holding students data from different universities. Learning analytics, discriminative and generative classification models are applied to predict whether a student will be able to complete his degree or not. Experimental results show that proposed method significantly outperforms existing methods due to exploitation of family expenditures and students personal information feature sets.

Key Words

Data Mining, Machine Learning, Tracking Students Performance, Course Prediction, and Recommendation System

Cite This Article

"Tracking and Predicting Student Performance Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 2, page no.439-441, February-2019, Available :http://www.jetir.org/papers/JETIRAE06102.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Tracking and Predicting Student Performance Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 2, page no. pp439-441, February-2019, Available at : http://www.jetir.org/papers/JETIRAE06102.pdf

Publication Details

Published Paper ID: JETIRAE06102
Registration ID: 198757
Published In: Volume 6 | Issue 2 | Year February-2019
DOI (Digital Object Identifier):
Page No: 439-441
Country: -, -, - .
Area: Engineering
ISSN Number: 2349-5162


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