A Review on Random Forest Measurements To Assess And Predict Student Learning of Software Engineering Teamwork

Karthik Suresh , Jibin Biju , Karthika Santhosh

Index Terms: software engineering teamwork, prediction, machine learning, education .

Abstract: The overall thing of our Software Engineering Teamwork Assessment and Prediction (SETAP) design is to develop effective machine- literacy- grounded styles for assessment and early prediction of pupil learning effectiveness in software engineering teamwork. Through this paper we briefly present a review on SETAP using Random Forest algorithm done at San Francisco State University (SFSU), Fulda University, Florida Atlantic University (FAU). These data are grouped into 11 time intervals, each measuring important phase of design development during the class. Results show that they're suitable to descry pupil teams who are bound to fail or need attention in early class time with good delicacy also the variable significance analysis shows that the features with high prophetic power. These measures can be used to guide preceptors and software engineering directors to insure early intervention for teams bound to fail.

Published Paper   E-Certificate

"A Review on Random Forest Measurements To Assess And Predict Student Learning of Software Engineering Teamwork", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.8, Issue 3, page no.1488 - 1494, March-2023, Available :https://ijsdr.org/papers/IJSDR2303261.pdf

Volume 8 Issue 3, March-2023

Pages : 1488 - 1494

Paper Reg. ID: IJSDR_204989

Published Paper Id: IJSDR2303261

Downloads: 000347540

Research Area: Engineering

Country: -, -, -

Published Paper PDF: https://ijsdr.org/papers/IJSDR2303261

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR2303261

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition