STUDENTS AND STAFFS PERFORMANCE PREDICTION USING MACHINE LEARNING
Author(s):
Abishake J, Roshan Kumar J, Abishek Js
Keywords:
Student Performance, Algorithm, Machine Learning, Education, Prediction, Data Mining
Abstract
In recent years, educational data mining (EDM) has become a new research field due to the development of various statistical methods to study data in the educational context. One such application is the early prediction of student performance. Weak disciples" in order to arrange some form of correction for them. . Since the number of attributes is large enough, a feature selection algorithm is applied to the data set to reduce the number of features. Then five types of machine learning algorithms (MLA) were applied to the data set, and it was found that the decision tree algorithm class gave the best results. Students and staffs performance prediction is very important to know a student progress rate. during this Research, we are attempting to seek out out student' current status, previous status and predict his/her future results. once the outcome, lecturers can provide him/her correct recommendation to avoid the poor result and can also groom the student. a lecturer can't monitor each and every single student at once. If a system can facilitate a lecturer regarding the scholars like that student needs which sort of help. The aim helps the student to avoid his/her predicted poor result and to improve their extra info activities based on the student’s performance level using Artificial Intelligence. This research would be useful for the students and staffs.
Article Details
Unique Paper ID: 151846

Publication Volume & Issue: Volume 8, Issue 1

Page(s): 976 - 981
Article Preview & Download


Share This Article

Conference Alert

NCSST-2021

AICTE Sponsored National Conference on Smart Systems and Technologies

Last Date: 25th November 2021

SWEC- Management

LATEST INNOVATION’S AND FUTURE TRENDS IN MANAGEMENT

Last Date: 7th November 2021

Latest Publication

Go To Issue



Call For Paper

Volume 9 Issue 10

Last Date for paper submitting for March Issue is 25 March 2023

About Us

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org

Social Media

Google Verified Reviews

Contact Details

Telephone:6351679790
Email: editor@ijirt.org
Website: ijirt.org

Policies

Important Links

Browse Rsearch papers