Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

Social Organisation and Cooperative Learning: Identification and Categorisation of Groups and Sub-Groups in Non-Cooperative Games

  • Conference paper
  • First Online:
Immersive Learning Research Network (iLRN 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1044))

Included in the following conference series:

Abstract

This paper outlines the results of a Modified SYMLOG (Mod-SYMLOG) analysis for group formation, structure and interactions. While collaborative working has been an established working methodology for Education and Computer Science researchers alike, there has been a lack of focus in the latter as to what a group actually is within psychologically complex human communities. Here we discuss why groups can be beneficial to student learning in education, but also how misusing groups has negative effects. This paper presents the results of two board game based experiments. The first experiment used the classic SYMLOG model to show validity of the scenario in data collection and the second testing our Mod-SYMLOG. Results showed that Mod-SYMLOG was effective in capturing group dynamics, with indications of group structure.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Bales, R.F.: Interaction Process Analysis; A Method for the Study of Small Groups. Addison-Wesley, Oxford (1950)

    Google Scholar 

  2. Bartlett, R.L.: A flip of the coin-a roll of the die: an answer to the free-rider problem in economic instruction. J. Econ. Educ. 26(2), 131–139 (1995)

    Google Scholar 

  3. Berdun, F., Armentano, M., Berdun, L., Cincunegui, M.: Building symlog profiles with an online collaborative game. Int. J. Hum. Comput. Stud. (2018). https://doi.org/10.1016/j.ijhcs.2018.07.002

    Article  Google Scholar 

  4. Blumenfeld, P.C., Marx, R.W., Soloway, E., Krajcik, J.: Learning with peers: from small group cooperation to collaborative communities. Educ. Researcher 25(8), 37–39 (1996)

    Article  Google Scholar 

  5. Calhamer, A.B.: The Rules of Diplomacy (2000). https://www.wizards.com/avalonhill/rules/diplomacy.pdf

  6. Cohen, E.G.: Restructuring the classroom: conditions for productive small groups. Rev. Educ. Res. 64(1), 1–35 (1994)

    Article  MathSciNet  Google Scholar 

  7. Dooley, J., Callaghan, V., Hagras, H., Gardner, M., Ghanbaria, M., AlGhazzawi, D.: The intelligent classroom: beyond four walls. In: Proceedings of the Intelligent Campus Workshop (IC 2011) held at the 7th IEEE Intelligent Environments Conference (IE 2011), Nottingham (2011)

    Google Scholar 

  8. Engel, D., Woolley, A.W., Jing, L.X., Chabris, C.F., Malone, T.W.: Reading the mind in the eyes or reading between the lines? Theory of mind predicts collective intelligence equally well online and face-to-face. PLoS ONE 9(12), e115212 (2014)

    Article  Google Scholar 

  9. Felemban, S., Gardner, M., Callaghan, V.: Towards recognising learning evidence in collaborative virtual environments: a mixed agents approach. Computers 6(3), 22 (2017)

    Article  Google Scholar 

  10. Forsyth, D.R.: Group Dynamics 15, (2014)

    Google Scholar 

  11. Gardner, M.R., Elliott, J.B.: The immersive education laboratory: understanding affordances, structuring experiences, and creating constructivist, collaborative processes, in mixed-reality smart environments. EAI Endorsed Trans. Future Intell. Educ. Environ. 1(1), e6 (2014)

    Google Scholar 

  12. Goodman, B., Linton, F., Gaimari, R.: Encouraging student reflection and articulation using a learning companion: a commentary. Int. J. Artif. Intell. Educ. 26(1), 474–488 (2016)

    Article  Google Scholar 

  13. Gunderson, D.E., Moore, J.D.: Group learning pedagogy and group selection. Int. J. Constr. Educ. Res. 4(1), 34–45 (2008)

    Article  Google Scholar 

  14. Jambi, E., Gardner, M., Callaghan, V.: Supporting mixed-mode role-play activities in a virtual environment. In: 2017 9th Computer Science and Electronic Engineering Conference, CEEC 2017 - Proceedings, pp. 49–54. IEEE, September 2017

    Google Scholar 

  15. Keyton, J., Wall, V.D.J.: Research instrument SYMLOG theory and method for measuring group and organizational communication. Manage. Commun. Q. 2(4), 544 (1989)

    Article  Google Scholar 

  16. List, C.: Group knowledge and group rationality: a judgment aggregation perspective. Episteme 2(01), 25–38 (2005)

    Article  Google Scholar 

  17. Longford, E., Gardner, M.R., Callaghan, V.: Group immersion in classrooms: a framework for an intelligent group-based tutoring system of multiple learners. In: Beck, D., et al. (eds.) Workshop, Long and Short Paper, and Poster Proceedings from the Fourth Immersive Learning Research Network Conference (iLRN 2018 Montana), pp. 133–135 (2018). https://doi.org/10.3217/978-3-85125-609-3-20

  18. Lonnqvist, J.E., Paunonen, S., Verkasalo, M., Leikas, S., Tuulio-Henriksson, A., Lonnqvist, J.: Personality characteristics of research volunteers. Eur. J. Pers. 21(8), 1017–1030 (2007)

    Article  Google Scholar 

  19. Olsen, Jennifer K., Belenky, Daniel M., Aleven, Vincent, Rummel, Nikol: Using an intelligent tutoring system to support collaborative as well as individual learning. In: Trausan-Matu, Stefan, Boyer, Kristy Elizabeth, Crosby, Martha, Panourgia, Kitty (eds.) ITS 2014. LNCS, vol. 8474, pp. 134–143. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-07221-0_16

    Chapter  Google Scholar 

  20. Palmgren-Neuvonen, L., Korkeamäki, R.L.: Group interaction of primary-aged students in the context of a learner-generated digital video production. Learn. Cult. Soc. Inter. 3(1), 1–14 (2014)

    Article  Google Scholar 

  21. Rrafzadeh, A., Alexander, S., Dadgostar, F., Fan, C., Bigdeli, A.: How do you know that I don’t understand? A look at the future of intelligent tutoring systems. Comput. Hum. Behav. 24(4), 1342–1363 (2008)

    Article  Google Scholar 

  22. Salkind, N.: Encyclopedia of Research Design (2010)

    Google Scholar 

  23. Springer, L., Stanne, M.E., Donovan, S.S.: Effects of small-group learning on undergraduates in science, mathematics, engineering, and technology: a meta-analysis. Rev. Educ. Res. 69(1), 21–51 (1999)

    Article  Google Scholar 

  24. Stahl, G.: The group as paradigmatic unit of analysis: the contested relationship of CSCL to the learning sciences. Learn. Sci. Mapp. Terrain (2015)

    Google Scholar 

  25. Suebnukarn, S.: Intelligent tutoring system for medical problem-based learning. Prog. Educ. 18(18), 233–302 (2010)

    Google Scholar 

  26. Walker, E., Rummel, N., Koedinger, K.R.: Designing automated adaptive support to improve student helping behaviors in a peer tutoring activity. Int. J. Comput. Support. Collaborative Learn. 6(2), 279–306 (2011)

    Article  Google Scholar 

  27. Wallin, P.: Volunteer subjects as a source of sampling bias. Am. J. Sociol. 54(6), 539–544 (1949)

    Article  Google Scholar 

  28. Woolley, A.W.: Evidence for a collective intelligence factor in the performance of human groups. Science 330(6004), 683–686 (2010)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Edward Longford .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Longford, E., Gardner, M., Callaghan, V. (2019). Social Organisation and Cooperative Learning: Identification and Categorisation of Groups and Sub-Groups in Non-Cooperative Games. In: Beck, D., et al. Immersive Learning Research Network. iLRN 2019. Communications in Computer and Information Science, vol 1044. Springer, Cham. https://doi.org/10.1007/978-3-030-23089-0_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-23089-0_10

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-23088-3

  • Online ISBN: 978-3-030-23089-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics