A Novel Metaheuristic Approach for Collaborative Learning Group Formation

Bibliographic Details
Title: A Novel Metaheuristic Approach for Collaborative Learning Group Formation
Language: English
Authors: Lambic, Dragan (ORCID 0000-0001-8611-353X), Lazovic, Bojana, Djenic, Aleksandar, Maric, Miroslav
Source: Journal of Computer Assisted Learning. Dec 2018 34(6):907-916.
Availability: Wiley-Blackwell. 350 Main Street, Malden, MA 02148. Tel: 800-835-6770; Tel: 781-388-8598; Fax: 781-388-8232; e-mail: cs-journals@wiley.com; Web site: http://www.wiley.com/WileyCDA
Peer Reviewed: Y
Page Count: 10
Publication Date: 2018
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Heuristics, Cooperative Learning, Group Dynamics, Interpersonal Relationship, Prosocial Behavior, College Freshmen, Foreign Countries, Business Schools, Business Administration Education, Experimental Groups, Control Groups, Academic Ability, Computer Uses in Education, Nongraded Instructional Grouping, Monte Carlo Methods
Geographic Terms: Serbia
DOI: 10.1111/jcal.12299
ISSN: 0266-4909
Abstract: In this paper, a new approach for the formation of four-member collaborative learning groups is presented. Group formation is presented by the mathematical optimization problem. Based on the proposed approach and the variable neighbourhood search (VNS) algorithm, the application that solves the presented problem and provides the appropriate division into groups is created. The proposed approach considers the scores of a pretest, interpersonal relationships, and prosocial behaviour/openness skill of students. In order to validate our approach, an experiment was designed with 108 first-year university students of Belgrade Business School--Higher Educational Institution for Applied Studies. Experimental and control groups were divided into four-member groups. The experimental group was divided by using the proposed method and the control group by student selection and random selection. Multilevel analysis is used to determine whether there is a significant difference in learning outcomes between the two groups. The experimental results showed that students from the experimental group achieved significantly higher success than the students from the control group. In addition, computational results obtained with the proposed VNS algorithms are compared and verified with the results obtained by random (Monte Carlo) method.
Abstractor: As Provided
Entry Date: 2018
Accession Number: EJ1196152
Database: ERIC
More Details
ISSN:0266-4909
DOI:10.1111/jcal.12299
Published in:Journal of Computer Assisted Learning
Language:English