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A computer program to aid assignment of student project groups

Published: 01 February 2001 Publication History

Abstract

Group projects are a valuable part of the computer science curriculum. Group work can be enhanced if formation of groups is not via self-selection by the students themselves. Students who are assigned to groups are more likely to be exposed to other students with different backgrounds and abilities from which they can learn new things. However in a university with students having a wide mix of schedules, a crucial aspect of successful group formation is compatible time-schedules within a group. This paper describes a computer program designed to aid assignment to groups while helping to ensure that groups have suitable outside-of-class meeting times.

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Cited By

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  • (2021)How Do Students Collaborate? Analyzing Group Choice in a Collaborative Learning EnvironmentProceedings of the 52nd ACM Technical Symposium on Computer Science Education10.1145/3408877.3432389(212-218)Online publication date: 3-Mar-2021
  • (2020)Genetic Algorithm Optimization of Teams for Heterogeneity2020 IEEE Frontiers in Education Conference (FIE)10.1109/FIE44824.2020.9274243(1-5)Online publication date: 21-Oct-2020
  • (2020)AssessmentGuide to Teaching Computer Science10.1007/978-3-030-39360-1_13(279-303)Online publication date: 6-Aug-2020
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cover image ACM Conferences
SIGCSE '01: Proceedings of the thirty-second SIGCSE technical symposium on Computer Science Education
February 2001
456 pages
ISBN:1581133294
DOI:10.1145/364447
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 01 February 2001

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SIGCSE '01 Paper Acceptance Rate 78 of 225 submissions, 35%;
Overall Acceptance Rate 1,787 of 5,146 submissions, 35%

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Cited By

View all
  • (2021)How Do Students Collaborate? Analyzing Group Choice in a Collaborative Learning EnvironmentProceedings of the 52nd ACM Technical Symposium on Computer Science Education10.1145/3408877.3432389(212-218)Online publication date: 3-Mar-2021
  • (2020)Genetic Algorithm Optimization of Teams for Heterogeneity2020 IEEE Frontiers in Education Conference (FIE)10.1109/FIE44824.2020.9274243(1-5)Online publication date: 21-Oct-2020
  • (2020)AssessmentGuide to Teaching Computer Science10.1007/978-3-030-39360-1_13(279-303)Online publication date: 6-Aug-2020
  • (2018)A “Mixed” Strategy for Collaborative Group Formation and Its Learning OutcomesJournal of Educational Technology Systems10.1177/004723951774924646:4(440-462)Online publication date: 5-Jan-2018
  • (2018)Towards Team Formation Using Belbin Role Types and a Social Networks Analysis Approach2018 IEEE Technology and Engineering Management Conference (TEMSCON)10.1109/TEMSCON.2018.8488386(1-6)Online publication date: Jun-2018
  • (2018)Group Formation Using Multi Objectives Ant Colony System for Collaborative Learning2018 5th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)10.1109/EECSI.2018.8752690(696-702)Online publication date: Oct-2018
  • (2017)Homogeneous group formation in collaborative learning using fuzzy C-means2017 IEEE 6th International Conference on Teaching, Assessment, and Learning for Engineering (TALE)10.1109/TALE.2017.8252307(74-79)Online publication date: Dec-2017
  • (2017)Group Matching for Peer Mentorship in Small GroupsCollaboration and Technology10.1007/978-3-319-63874-4_6(65-80)Online publication date: 9-Jul-2017
  • (2015)A hybrid genetic algorithm for group formation at workplace2015 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC.2015.7257301(3287-3295)Online publication date: May-2015
  • (2015)AssessmentGuide to Teaching Computer Science10.1007/978-1-4471-6630-6_10(187-205)Online publication date: 8-Jan-2015
  • Show More Cited By

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