Balanced student partitioning to promote effective learning: Applications in an international school

Wenbin Zhu, Hu Qin, Andrew Lim, Zhou Xu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

In this paper, we describe a system that our team developed to solve the problem of heterogeneously partitioning students into classes for the Singapore International School based in Hong Kong. This problem has multiple objectives such as to achieve similar class sizes, similar gender ratios among all classes, each student having at least one old classmate of the same gender, conflict avoidance among students, and similarity of score distribution curves. We proved that this problem is extremely hard and provided an example to show that the number of feasible solutions is astronomical for only medium size cases. We devised and implemented a simulated annealing (SA) algorithm to solve this problem. Our experimental results based on real application data indicate that our SA algorithm is able to improve the quality of the school's partitioning solutions and clearly meets all objectives set out by the client.
Original languageEnglish
Title of host publicationKnowledge Management and Acquisition for Smart Systems and Services - 11th International Workshop, PKAW 2010, Proceedings
Pages38-48
Number of pages11
DOIs
Publication statusPublished - 3 Nov 2010
Event11th International Workshop on Knowledge Management and Acquisition for Smart Systems and Services, PKAW 2010 - Daegu, Korea, Republic of
Duration: 20 Aug 20103 Sep 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6232 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th International Workshop on Knowledge Management and Acquisition for Smart Systems and Services, PKAW 2010
Country/TerritoryKorea, Republic of
CityDaegu
Period20/08/103/09/10

Keywords

  • multiple objective
  • simulated annealing
  • student partitioning

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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