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Creating effective student groups: an introduction to groupformation.org

Published:06 March 2013Publication History

ABSTRACT

Success in the computing industry often depends on an individual's ability to be a productive member of an effective study group or project team. In order to prepare students for successful careers, computer science curriculum often includes group projects. This paper discusses the challenges of forming effective student groups, discusses existing software for forming groups, and introduces groupformation.org, a new free and open source group formation service.

References

  1. Agustín-Blas, L. E. , Salcedo-Sanz , S., Ortiz-García , E. G., Portilla-Figueras , A., Pérez-Bellido , Á. M., Jiménez-Fernández, S. 2011. Team formation based on group technology: A hybrid grouping genetic algorithm approach, Computers and Operations Research, v.38 n.2, p.484--495. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Agustín-Blas, L. E. , Salcedo-Sanz , S., Ortiz-García , E. G., Portilla-Figueras , A. 2008. Assignment of Students to Preferred Laboratory Groups Using a Hybrid Grouping Genetic Algorithm. In Proceedings of the 8th IEEE International Conference on Hybrid Intelligent Systems (HIS '08). DOI=10.1109/HIS.2008.37 Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Ani, Z., Yasin, A. Husin, M., Hamid, Z., 2010. A Method for Group Formation Using Genetic Algorithm, (IJCSE) International Journal on Computer Science and Engineering Vol. 02, No. 09, 3060--3064Google ScholarGoogle Scholar
  4. Baykasoglu, A., Dereli, T., Das, S. 2007. Project Team Selection Using Fuzzy Optimization Approach. Cybern. Syst. 38, 2 (February 2007), 155--185. DOI=10.1080/01969720601139041 Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Beheshtian-Adekani, M., and Mahmood, M. 1986. Development and validation of a tool for assigning students to groups for class projects. Decision Sciences. v17. 92--113.Google ScholarGoogle Scholar
  6. Carpenter, S., Fortune, J., Delugach, H., Etzkorn, L., Utley, D., Farrington, P., and Virani, S. 2008. Studying team shared mental models. In Proceedings of the 3rd International Conference on the Pragmatic Web: Innovating the Interactive Society (ICPW '08), ACM, New York, NY, USA, 41--48. DOI=10.1145/1479190.1479197 Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Cavanaugh, R., Ellis, M., Layton, R., and Ardis, M. 2004. Automating the process of assigning students to cooperative-learning teams. In Proceedings of the 2004 ASEE Annual Conference. American Society for Engineering Education.Google ScholarGoogle Scholar
  8. Chan, T., Chen, C., Wu, Y., Jong, B., Hsia, Y., and Lin, T. 2010. Applying the genetic encoded conceptual graph to grouping learning. Expert Syst. Appl. 37, 6 (June 2010), 4103--4118. DOI=10.1016/j.eswa.2009.11.014 Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Christodoulopoulos, C.E., Papanikolaou, K. 2007. Investigation of group formation using low complexity algorithms. In: Proc. of PING Workshop, pp. 57--60.Google ScholarGoogle Scholar
  10. Craig , M., Horton, D., Pitt, F. 2010. Forming reasonably optimal groups: (FROG), Proceedings of the 16th ACM international conference on Supporting group work, November 07--10, 2010, Sanibel Island, Florida, USA. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Cutshall, R., Gavirneni, S., and Schultz, K. 2007. Indiana University's Kelley School of Business Uses Integer Programming to Form Equitable, Cohesive Student Teams. Interfaces 37, 3, 265--276. DOI=10.1287/inte.1060.0248 Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Doyle, K., Kroha, S., Palchowdhury, A., and Xu, W. 2002. Project Group Assignment System, Proceedings of MASPLAS'02 The Mid-Atlantic Student Workshop on Programming Languages and Systems, Pace University.Google ScholarGoogle Scholar
  13. Feng, B., Jiang, Z., Fan, Z., Fu, N. 2010. A method for member selection of cross-functional teams using the individual and collaborative performances, European Journal of Operational Research, Volume 203, Issue 3, 16, ISSN 0377--2217, DOI: 10.1016/j.ejor.2009.08.017.Google ScholarGoogle ScholarCross RefCross Ref
  14. Gaston, M. E., des Jardins, M. 2005. Agent-organized networks for dynamic team formation. In Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems (AAMAS '05), 230--237. DOI=10.1145/1082473.1082508 Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Henry, T.R. 2013. http://groupformation.orgGoogle ScholarGoogle Scholar
  16. Henry, T.R. 2013. Algorithmic Issues of Forming Productive Student Groups, TR No. CS-2013-01. http://www.ecst.csuchico.edu/~tyson/tr/TR13-01.pdfGoogle ScholarGoogle Scholar
  17. Hishina, M., Okada, R., Suzuki, K. 2005. Group Formation for Web-Based Collaborative Learning with Personality Information, International Journal on E-Learning, v4 n3.Google ScholarGoogle Scholar
  18. Karn, J., Cowling, T. 2006. A follow up study of the effect of personality on the performance of software engineering teams. In Proceedings of the 2006 ACM/IEEE international symposium on Empirical software engineering (ISESE '06). DOI=10.1145/1159733.1159769 Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Kyprianidou, M., Demetriadis, S., Pombortsis, A., Karatasios, G. 2009. PEGASUS: designing a system for supporting group activity, Multicultural Education & Technology Journal, Vol. 3 Iss: 1, pp.47 -- 60Google ScholarGoogle ScholarCross RefCross Ref
  20. Layton, R. A., Loughry, M. L., Ohland, M. W., G. D. Rico, G. D. 2010. Design and validation of a web-based system for assigning members to teams using instructor-specified criteria. Advances in Engineering Education, Vol. 2, No. 1.Google ScholarGoogle Scholar
  21. Lewis, T. L., Smith, W. J., 2008. Creating high performing software engineering teams: the impact of problem solving style dominance on group conflict and performance. J. Comput. Small Colleges. 24, 2, 121--129. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Lin, Y., Huang, Y., Cheng, S. 2010. An automatic group composition system for composing collaborative learning groups using enhanced particle swarm optimization. Comput. Educ. 55, 4. DOI=10.1016/j.compedu.2010.06.014 Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Mahenthiran, S., and Rouse, P. 2000. The impact of group selection on student performance and satisfaction. The International Journal of Educational Management. v14 i6.Google ScholarGoogle Scholar
  24. Meyer, D. 2009. OptAssign-A web-based tool for assigning students to groups. Computer Education. 53, 4. DOI=10.1016/j.compedu.2009.05.022 Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Nielsen, T., Hvas, A. E., Kjaergaard, A. 2009. Student team formation based on learning styles at university start: does it make a difference to the student? Reflection Education. v5 i2. 85--103.Google ScholarGoogle Scholar
  26. Ohland, M. W. 2012. http://catme.org https://engineering.purdue.edu/CATMEGoogle ScholarGoogle Scholar
  27. Redmond, M. A. 2001. A computer program to aid assignment of student project groups. In Proceedings of the thirty-second SIGCSE technical symposium on Computer Science Education. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Rutherfoord, R. H. 2006. Using personality inventories to form teams for class projects: a case study. In Proceedings of the 7th conference on Information technology education (ACM SIGITE). DOI=10.1145/1168812.1168817 Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. Strnad, D., Guid, N. 2010. A fuzzy-genetic decision support system for project team formation. Appl. Soft Comput.10, 4, 1178--1187. DOI=10.1016/j.asoc.2009.08.032 Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. Tobar, C. M., de Freita, R. L. 2007.A support tool for student group definition. In proceedings of the 37th ASEE/IEEE Frontiers in Education.Google ScholarGoogle ScholarCross RefCross Ref
  31. Wang, D., Lin S. S. J., Sun, C. 2010 DIANA: A computer-supported heterogeneous grouping system for teachers to conduct successful small learning groups, Computers in Human Behavior, v.23 n.4 DOI=10.1016/j.chb.2006.02.008 Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. Yeoh, H. K., Nor, M. I. M. 2009. An Algorithm to Form Balanced and Diverse Groups of Students. Computer Applicatons in Engineering Education, v19, i3. DOI=10.1002/cae.20338Google ScholarGoogle Scholar
  33. Zakarian, A., Kusiak, A. 1999. Forming teams: an analytical approach. IIE Transactions. v31. 85--97.Google ScholarGoogle Scholar

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    • Published in

      cover image ACM Conferences
      SIGCSE '13: Proceeding of the 44th ACM technical symposium on Computer science education
      March 2013
      818 pages
      ISBN:9781450318686
      DOI:10.1145/2445196

      Copyright © 2013 ACM

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      Publication History

      • Published: 6 March 2013

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      SIGCSE '13 Paper Acceptance Rate111of293submissions,38%Overall Acceptance Rate1,595of4,542submissions,35%

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