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Reseach Article

A New Approach to Collaborative Group Formation

by Anurag Sarkar, Dibyabiva Seth, Kaustav Basu, Anal Acharya
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 128 - Number 3
Year of Publication: 2015
Authors: Anurag Sarkar, Dibyabiva Seth, Kaustav Basu, Anal Acharya
10.5120/ijca2015906462

Anurag Sarkar, Dibyabiva Seth, Kaustav Basu, Anal Acharya . A New Approach to Collaborative Group Formation. International Journal of Computer Applications. 128, 3 ( October 2015), 7-14. DOI=10.5120/ijca2015906462

@article{ 10.5120/ijca2015906462,
author = { Anurag Sarkar, Dibyabiva Seth, Kaustav Basu, Anal Acharya },
title = { A New Approach to Collaborative Group Formation },
journal = { International Journal of Computer Applications },
issue_date = { October 2015 },
volume = { 128 },
number = { 3 },
month = { October },
year = { 2015 },
issn = { 0975-8887 },
pages = { 7-14 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume128/number3/22851-2015906462/ },
doi = { 10.5120/ijca2015906462 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:20:16.374919+05:30
%A Anurag Sarkar
%A Dibyabiva Seth
%A Kaustav Basu
%A Anal Acharya
%T A New Approach to Collaborative Group Formation
%J International Journal of Computer Applications
%@ 0975-8887
%V 128
%N 3
%P 7-14
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper implements a tool, referred to as the Automated Group Decomposition Program (AGDP), which divides a class of students into groups, using the k-means algorithm, for the purpose of collaborative learning, and then heterogenizes the groups based on a factor called the degree of heterogeneity (DOH). The tool takes as input two sets of scores and the students’ roll numbers and outputs the required groups. The first score set scored students on communication skills, fluency in using computers and group work attitude. This score set was used to generate the homogeneous groups. The second score set scored students on their knowledge of the subject and was used to generate the heterogeneous groups. The tool can be used to generate homogeneous clusters, heterogeneous clusters and a mixture of both. This tool can not only be used by teachers but also by instructors with minimal computer experience wishing to form groups to maximize learning.

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Index Terms

Computer Science
Information Sciences

Keywords

collaborative learning k-means constraint satisfaction degree of homogeneity group learning homogeneous groups heterogeneous groups.