Forming heterogeneous groups for intelligent collaborative learning systems with ant colony optimization

Sabine Graf, Rahel Bekele

Research output: Chapter in Book/Report/Conference proceedingPublished Conference contributionpeer-review

123 Citations (Scopus)

Abstract

Heterogeneity in learning groups is said to improve academic performance. But only few collaborative online systems consider the formation of heterogeneous groups. In this paper we propose a mathematical approach to form heterogeneous groups based on personality traits and the performance of students. We also present a tool that implements this mathematical approach, using an Ant Colony Optimization algorithm in order to maximize the heterogeneity of formed groups. Experiments show that the algorithm delivers stable solutions which are close to the optimum for different datasets of 100 students. An experiment with 512 students was also performed demonstrating the scalability of the algorithm.

Original languageEnglish
Title of host publicationIntelligent Tutoring Systems - 8th International Conference, ITS 2006, Proceedings
Pages217-226
Number of pages10
DOIs
Publication statusPublished - 2006
Event8th International Conference on Intelligent Tutoring Systems, ITS 2006 - Jhongli, Taiwan, Province of China
Duration: 26 Jun. 200630 Jun. 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4053 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Conference on Intelligent Tutoring Systems, ITS 2006
Country/TerritoryTaiwan, Province of China
CityJhongli
Period26/06/0630/06/06

Fingerprint

Dive into the research topics of 'Forming heterogeneous groups for intelligent collaborative learning systems with ant colony optimization'. Together they form a unique fingerprint.

Cite this