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The Psychometric Properties of a Preliminary Social Presence Measure Using Rasch Analysis

  • Karel KreijnsEmail author
  • Joshua Weidlich
  • Kamakshi Rajagopal
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11082)

Abstract

Social presence is an important construct in computer mediated communication, such as found in online collaborative learning (OCL) settings. It is hypothesized that social presence influences the degree of perceived learning and learning outcomes of OCL group members. However, the construct social presence is contested as many incompatible definitions exist in the research community and so do the many measures of social presence. Also, none of the existing social presence measures has undergone a rigid construct validation process such as proposed by Rasch Measurement theory. As a result, hypothesis testing using these measures produced unreliable findings. To address this undesirable situation, we returned to the original definition of Short et al. [29] and redefined it as the degree to which the other person is perceived as physical ‘real’ in the communication. We present a social presence measure that assesses this perception of realness. Rasch analysis was used to validate the raw social presence measure. Our findings revealed that measuring the degree of realness was excellent for those who have high perceptions of realness of the other (i.e., they could be well differentiated), whereas this was moderate for those who have low perceptions (i.e., they could be less well differentiated). Our conclusion is that the social presence measure is already an improvement when compared to existing social presence measures that emphasize realness but it surely needs further improvement: those who have low perceptions of realness should equally well be differentiated as those with high perceptions of it.

Keywords

Online collaborative learning Rash measurement model Social presence theory Social presence measure 

References

  1. 1.
    Abdullah, M.H.: Social presence in online conferences: What makes people ‘real’? Malays. J. Dist. Educ. 6(2), 1–22 (2004)MathSciNetGoogle Scholar
  2. 2.
    Argyle, M., Dean, J.: Eye contact, distance and affiliation. Sociometry 28, 289–304 (1965)CrossRefGoogle Scholar
  3. 3.
    Baghaei, P.: The Rasch model as a construct validation tool. Rasch Measur. Trans. 22(1), 1145–1146 (2008)Google Scholar
  4. 4.
    Biocca, F., Harms, C., Burgoon, J.K.: Toward a more robust theory and measure of social presence: review and suggested criteria. Presence: Teleoperators Virtual Environ. 12(5), 456–480 (2003)CrossRefGoogle Scholar
  5. 5.
    Bond, T., Fox, C.M.: Applying the Rasch Model: Fundamental Measurement in the Human Sciences, 3rd edn. Routledge, New York, London (2015)CrossRefGoogle Scholar
  6. 6.
    Boone, W.J., Staver, J.S., Yale, M.S.: Rasch Analysis in the Human Sciences. Springer, Dordrecht, The Netherlands (2014)CrossRefGoogle Scholar
  7. 7.
    Boone, W.J.: Rasch analysis for instrument development: Why, when, and how? CBE-Life Sci. Educ. 15(4), rm4 (2016)CrossRefGoogle Scholar
  8. 8.
    Engelhard Jr., G.: Invariant Measurement: Using Rasch Models in the Social, Behavioral, and Health Sciences. Routledge, New York, London (2013)CrossRefGoogle Scholar
  9. 9.
    Garrison, D.R.: Communities of inquiry in online learning. In: Rogers, P.L. (ed.) Encyclopedia of distance learning, 2nd edn, pp. 352–355. IGI Global, Hershey, PA (2009)CrossRefGoogle Scholar
  10. 10.
    Gunawardena, C.N.: Social presence theory and implications for interaction and collaborative learning in computer conferences. Int. J. Educ. Telecommun. 1(2&3), 147–166 (1995)Google Scholar
  11. 11.
    Gunawardena, C.N., Zittle, F.: Social presence as a predictor of satisfaction within a computer mediated conferencing environment. Am. J. Dist. Educ. 11(3), 8–25 (1997)CrossRefGoogle Scholar
  12. 12.
    Hollis, H.: The impact of social media on social presence and student satisfaction in nursing education. Unpublished dissertation. University of Alabama, Tuscaloosa, AL (2014)Google Scholar
  13. 13.
    Kaplan, A.M., Haenlein, M.: Users of the world, unite! the challenges and opportunities of social media. Bus. Horiz. 54, 59–68 (2010)CrossRefGoogle Scholar
  14. 14.
    Kim, J.I., Ha, T., Woo, W., Shi, C.-K.: Enhancing Social Presence in Augmented Reality-Based Telecommunication System. In: Shumaker, R. (ed.) VAMR 2013, Part I. LNCS, vol. 8021, pp. 359–367. Springer, Heidelberg (2013).  https://doi.org/10.1007/978-3-642-39405-8_40CrossRefGoogle Scholar
  15. 15.
    Kreijns, K., Kirschner, P.A., Jochems, W., Van Buuren, H.: Measuring perceived social presence in distributed learning groups. Educ. Inf. Technol. 16(4), 365–381 (2011)CrossRefGoogle Scholar
  16. 16.
    Kreijns, K., Van Acker, F., Vermeulen, M., van Buuren, H.: Community of inquiry: Social presence revisited [Special Issue: Inquiry into “Communities of Inquiry:” Knowledge, Communication, Presence, Community]. E-Learn. Digit. Media 11(1), 5–18 (2014)CrossRefGoogle Scholar
  17. 17.
    Linacre, J.M.: KR-20/Cronbach alpha or Rasch person reliability: which tells the “truth”? Rasch Measur. Trans. 11(3), 580–581 (1997)Google Scholar
  18. 18.
    Linacre, J.M.: Computer adaptive testing: a methodology whose time has come. In: Chae, S., Kang, U., Jeon, E., Linacre, J.M. (eds.) Development of Computerized Middle School Achievement Test. Komesa Press, Seoul, South Korea (2000)Google Scholar
  19. 19.
    Linacre, J.M.: Winsteps® Rasch measurement computer program user’s guide. Winsteps.com, Beaverton, OR (2016)Google Scholar
  20. 20.
    Liu, S.Y., Gomez, J., Yen, C.-J.: Community college online course retention and final grade: predictability of social presence. J. Interact. Online Learn. 8(2), 165–182 (2009)Google Scholar
  21. 21.
    Lombart, M., Ditton, T.: At the heart of it all: The concept of presence. J. Comput. Med. Commun. 3(2), (1997). https://academic.oup.com/jcmc/article/3/2/JCMC321/4080403. Accessed 16 June 2018
  22. 22.
    Lowenthal, P.R.: The evolution and influence of social presence theory on online learning. In: Kidd, T.T. (ed.) Online Education and Adult Learning: New Frontiers for Teaching Practices, pp. 124–134. IGI Global, Hershey, PA (2010)CrossRefGoogle Scholar
  23. 23.
    Lowenthal, P.R., Snelson, C.: In search of a better understanding of social presence: an investigation into how researchers define social presence. Dist. Educ. 38(2), 1–19 (2017)Google Scholar
  24. 24.
    Messick, S.: Validity and washback in language testing. Lang. Test. 13(3), 241–256 (1996)CrossRefGoogle Scholar
  25. 25.
    Rasch, G.: Probabilistic Models for Some Intelligence and Attainment Tests. Paedagogiske Institut, Kopenhagen (1960)Google Scholar
  26. 26.
    Rosakranse, C., Nass, C., Oh, S.: Social presence in CMC and VR. In: Burgoon, J., Magnenat-Thalmann, N., Pantic, M., Vinciarelli, A. (eds.) Social Signal Processing, pp. 110–120. Cambridge University Press, Cambridge (2017)CrossRefGoogle Scholar
  27. 27.
    Richardson, J.C., Maeda, Y., Lv, J., Caskurlu, S.: Social presence in relation to students’ satisfaction and learning in the online environment: a meta-analysis. Comput. Hum. Behav. 71, 402–417 (2017)CrossRefGoogle Scholar
  28. 28.
    Rourke, L., Anderson, T.: Exploring social interaction in computer conferencing. J. Interact. Learn. Res. 13(3), 257–273 (2002)Google Scholar
  29. 29.
    Short, J., Williams, E., Christie, B.: The Social Psychology of Telecommunications. Wiley, London (1976)Google Scholar
  30. 30.
    Sick, J.: Rasch measurement and factor analysis. SHIKEN: JALT Test. Eval. SIG Newslett. 15(1), 15–17 (2011)Google Scholar
  31. 31.
    Swan, K., Matthews, D., Bogle, D., Boles, E., Day, S.: Linking online course design and implementation to learning outcomes: a design experiment. Internet High. Educ. 15(2), 81–88 (2012)CrossRefGoogle Scholar
  32. 32.
    Tennant, A., Conaghan, P.G.: The Rasch measurement model in rheumatology: What is it and why use it? When should it be applied and what should one look for in a Rasch paper? Arthritis Rheum. 57(8), 1358–1362 (2007)CrossRefGoogle Scholar
  33. 33.
    Tu, C.H.: The measurement of social presence in an online learning environment. Int. J. Educ. Telecommun. 1(2), 34–45 (2002)MathSciNetGoogle Scholar
  34. 34.
    Tu, C.H.: The relationship between social presence and online privacy. Internet High. Educ. 5(2002), 293–318 (2002)CrossRefGoogle Scholar
  35. 35.
    Wei, C.-W., Chen, N.-S., Kinshuk, : A model for social presence in online classrooms. Educ. Technol. Res. Develop. 60(3), 529–545 (2012)CrossRefGoogle Scholar
  36. 36.
    Weidlich, J., Bastiaens, T.: Explaining social presence and the quality of online learning with the SIPS model. Comput. Hum. Behav. 72, 479–487 (2017)CrossRefGoogle Scholar
  37. 37.
    Wiener, M., Mehrabian, A.: Language Within Language: Immediacy, A Channel in Verbal Communication. Apple-Century-Crofts, New York (1968)Google Scholar
  38. 38.
    Wright, B.D.: Comparing Rasch measurement and factor analysis. Struct. Eqn. Model. 3(1), 3–24 (1996)CrossRefGoogle Scholar
  39. 39.
    Wright, B.D., Linacre, J.M.: Reasonable mean-square fit values. Rasch Measur. Trans. 8, 370–371 (1994)Google Scholar
  40. 40.
    Wright, B.D., Masters, G.N.: Rating Scale Analysis. MESA Press, Chicago, IL (1982)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Karel Kreijns
    • 1
    Email author
  • Joshua Weidlich
    • 2
  • Kamakshi Rajagopal
    • 1
  1. 1.Open Universiteit NederlandHeerlenThe Netherlands
  2. 2.FernUniversität HagenHagenGermany

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