Skip to main content
SpringerLink
Log in
Book cover

The Psychology of Digital Learning pp 105–122Cite as

A Conceptual Framework of Knowledge Exchange

  • Chapter
  • First Online:

Abstract

Knowledge exchange, defined as interpersonal interactions that change knowledge in the heads and/or knowledge in the world, is a topic of interest in many research fields. This chapter outlines a conceptual framework which captures many variables that play a role in knowledge exchange. The conceptual framework draws a distinction between input variables, process variables, and output variables. Moreover, the framework stresses the importance of taking both individual-level variables and group-level variables into account in order to describe and explain knowledge exchange. These variables can be used to describe and categorize a broad range of empirical studies from various scholarly fields. Patterns of covariation that are discovered in the network of variables have the potential to transform the conceptual framework of knowledge exchange into a theoretical framework.

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

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   119.99
Price excludes VAT (USA)
  • Durable hardcover 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

Learn about institutional subscriptions

References

  • Baddeley, A. D., & Hitch, G. (1974). Working memory. In G. H. Bower (Ed.), The psychology of learning and motivation: Advances in research and theory (pp. 47–89). New York: Academic Press.

    Google Scholar 

  • Baker, M. J., Andriessen, J., Lund, K., van Amelsvoort, M., & Quignard, M. (2007). Rainbow: a framework for analysing computer-mediated pedagogical debates. International Journal of Computer-Supported Collaborative Learning, 2, 315–357.

    Article  Google Scholar 

  • Buder, J. (2011). Group awareness tools for learning: Current and future directions. Computers in Human Behavior, 27, 1114–1117.

    Article  Google Scholar 

  • Buder, J., & Bodemer, D. (2008). Supporting controversial CSCL discussions with augmented group awareness tools. International Journal of Computer-Supported Collaborative Learning, 3, 123–139.

    Article  Google Scholar 

  • Buder, J., Schwind, C., Rudat, A., & Bodemer, D. (2015). Selective reading of large online forum discussions: The impact of rating visualizations on navigation and learning. Computers in Human Behavior, 44, 191–201.

    Article  Google Scholar 

  • Clark, H., & Brennan, S. (1991). Grounding in communication. In L. B. Resnick, J. M. Levine, & S. D. Teasley (Eds.), Perspectives on socially shared cognition (pp. 127–149). Washington, DC: American Psychological Association.

    Chapter  Google Scholar 

  • Cress, U., & Kimmerle, J. (2017). The interrelations of individual learning and collective knowledge construction: A cognitive-systemic framework. In S. Schwan & U. Cress (Eds.), The psychology of digital learning: Constructing, exchanging, and acquiring knowledge with digital media. New York: Springer.

    Google Scholar 

  • De Jong, T., & van Joolingen, W. (1998). Scientific discovery learning with computer simulations of conceptual domains. Review of Educational Research, 68, 179–201.

    Article  Google Scholar 

  • Dehler, J., Bodemer, D., Buder, J., & Hesse, F. W. (2011). Guiding knowledge communication in CSCL via group knowledge awareness. Computers in Human Behavior, 27, 1068–1078.

    Article  Google Scholar 

  • Dehler-Zufferey, J., Bodemer, D., Buder, J., & Hesse, F. W. (2011). Partner knowledge awareness in knowledge communication: Learning by adapting to the partner. The Journal of Experimental Education, 79, 102–125.

    Article  Google Scholar 

  • Diehl, M., & Stroebe, W. (1987). Productivity loss in brainstorming groups: Toward the solution of a riddle. Journal of Personality and Social Psychology, 53, 497–509.

    Article  Google Scholar 

  • Doise, W., & Mugny, G. (1984). The social development of the intellect. Oxford: Pergamon.

    Google Scholar 

  • Efklides, A. (2008). Metacognition: Defining its facets and levels of functioning in relation to self-regulation and co-regulation. European Psychologist, 13, 277–287.

    Article  Google Scholar 

  • Engelmann, T., & Hesse, F. W. (2010). How digital concept maps about the collaborators’ knowledge and information influence computer-supported collaborative problem solving. International Journal of Computer-Supported Collaborative Learning, 5, 299–320.

    Article  Google Scholar 

  • Engelmann, T., & Hesse, F. W. (2011). Fostering sharing of unshared knowledge by having access to the collaborators’ meta-knowledge structures. Computers in Human Behavior, 27, 2078–2087.

    Article  Google Scholar 

  • Engelmann, T., Kolodziej, R., & Hesse, F. W.Preventing undesirable effects of mutual trust and the development of skepticism in virtual groups by applying the knowledge and information awareness approach. International Journal of Computer-Supported Collaborative Learning, 9, 211–235.

    Google Scholar 

  • Engelmann, T., Kozlov, M. D., Kolodziej, R., & Clariana, R. B. (2014). Fostering group norm development and orientation while creating awareness contents for improving net-based collaborative problem solving. Computers in Human Behavior, 37, 298–306.

    Article  Google Scholar 

  • Engelmann, T., Dehler, J., Bodemer, D., & Buder, J. (2009). Knowledge awareness in CSCL: a psychological perspective. Computers in Human Behavior, 25, 949–960.

    Article  Google Scholar 

  • Festinger, L. (1954). A theory of social comparison processes. Human Relations, 7, 117–140.

    Article  Google Scholar 

  • Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive-developmental inquiry. American Psychologist, 34, 906–911.

    Article  Google Scholar 

  • Fodor, J. (1975). The language of thought. Cambridge: Harvard University Press.

    Google Scholar 

  • Hart, J. T. (1965). Memory and the feeling-of-knowing experience. Journal of Educational Psychology, 56, 208–216.

    Article  Google Scholar 

  • Hart, W., Albarracin, D., Eagly, A. H., Brechan, I., Lindberg, M. J., & Merrill, L. (2009). Feeling validated versus being correct: A meta-analysis of selective exposure to information. Psychological Bulletin, 135, 555–588.

    Article  Google Scholar 

  • Hutchins, E. (1995). Cognition in the wild. Cambridge, MA: MIT Press.

    Google Scholar 

  • Jehn, K. (1995). A multimethod examination of the benefits and detriments of intragroup conflict. Administrative Science Quarterly, 40, 256–282.

    Article  Google Scholar 

  • Johnson, D. W., & Johnson, R. T. (1979). Conflict in the classroom: Controversy and learning. Review of Educational Research, 49, 51–69.

    Article  Google Scholar 

  • Kiesler, S., Siegel, J., & McGuire, T. W. (1984). Social psychological aspects of computer-mediated communication. American Psychologist, 39, 1123–1134.

    Article  Google Scholar 

  • Kolodziej, R., Hesse, F. W., & Engelmann, T. (2016). Improving negotiations with bar charts: The advantages of priority awareness. Computers in Human Behavior, 60, 351–360.

    Article  Google Scholar 

  • Kozlov, M. D., Engelmann, T., Buder, J., & Hesse, F. W. (2015). Is knowledge best shared or given to individuals? Expanding the content-based knowledge awareness paradigm. Computers in Human Behavior, 37, 298–306.

    Google Scholar 

  • Kruger, J., Epley, N., Parker, J., & Ng, Z. W. (2005). Egocentrism over e-mail: Can we communicate as well as we think? Journal of Personality and Social Psychology, 89, 925–936.

    Article  Google Scholar 

  • Lea, M., & Spears, R. (1991). Computer-mediated communication, de-individuation and group decision-making. International Journal of Man-Machine Studies, 34, 283–301.

    Article  Google Scholar 

  • Mayer, R. E. (2001). Multimedia learning. New York: Cambridge University Press.

    Book  Google Scholar 

  • McGrath, J. E., & Hollingshead, A. B. (1994). Groups interacting with technology. Newbury Park: Sage.

    Google Scholar 

  • Medina, R., & Suthers, D. D. (2013). Inscriptions becoming representations in representational practices. Journal of the Learning Sciences, 22, 33–69.

    Article  Google Scholar 

  • van Mierlo, T. (2014). The 1 % rule in four digital health social networks: An observational study. Journal of Medical Internet Research, 16, e33.

    Article  Google Scholar 

  • Mohammed, S., & Dumville, B. C. (2001). Team mental models in a team knowledge framework: Expanding theory and measurement across disciplinary boundaries. Journal of Organizational Behavior, 22, 89–106.

    Article  Google Scholar 

  • Monge, P. R., & Kirste, K. K. (1980). Measuring proximity in human organization. Social Psychology Quarterly, 43, 110–115.

    Article  Google Scholar 

  • Nelson, T. O. (1996). Consciousness and metacognition. American Psychologist, 51, 102–116.

    Article  Google Scholar 

  • Nelson, T. O., & Narens, L. (1994). Why investigate metacognition? In J. Metcalfe & A. Shimamura (Eds.), Metacognition: Knowing about knowing (pp. 1–25). Cambridge, MA: MIT.

    Google Scholar 

  • Nickerson, R. S. (1998). Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology, 2, 175–220.

    Article  Google Scholar 

  • Piaget, J., & Inhelder, B. (1969). The psychology of the child. New York: Basic Books.

    Google Scholar 

  • Ray, D., Neugebauer, J., Sassenberg, K., Buder, J., & Hesse, F. W. (2013). Motivated shortcomings in explanation: The role of comparative self-evaluation and awareness of explanation recipient knowledge. Journal of Experimental Psychology: General, 142, 445–457.

    Article  Google Scholar 

  • Reimann, P., Yacef, K., & Kay, J. (2011). Analyzing collaborative interactions with data mining methods for the benefit of learning. In S. Puntambekar, G. Erkens, & C. Hmelo-Silver (Eds.), Analyzing Interactions in CSCL (pp. 161–185). Berlin: Springer.

    Chapter  Google Scholar 

  • Roschelle, J. (1992). Learning by collaborating: Convergent conceptual change. The Journal of the Learning Sciences, 2, 235–276.

    Article  Google Scholar 

  • Rudat, A., & Buder, J. (2015). Making retweeting social: The influence of content and context information on sharing news in Twitter. Computers in Human Behavior, 46, 75–84.

    Article  Google Scholar 

  • Rudat, A., Buder, J., & Hesse, F. W. (2014). Audience design in Twitter: Retweeting behavior between informational value and followers' interests. Computers in Human Behavior, 35, 132–139.

    Article  Google Scholar 

  • Scholl, A., Landkammer, F., & Sassenberg, K. (2017). Knowledge exchange as a motivated social process. In S. Schwan & U. Cress (Eds.), The psychology of digital learning: Constructing, exchanging, and acquiring knowledge with digital media. New York: Springer.

    Google Scholar 

  • Schreiber, M., & Engelmann, T. (2010). Knowledge and information awareness for initiating transactive memory system processes of computer-supported collaborating ad hoc groups. Computers in Human Behavior, 26, 1701–1709.

    Article  Google Scholar 

  • Schubert, M., Buder, J., & Hesse, F. W. (2014). What should I say now? A metacognitive model on the regulation of information exchange in group learning. Meeting of the EARLI SIG 16 Metacognition. Istanbul, Turkey.

    Google Scholar 

  • Schwind, C., & Buder, J. (2012). Reducing confirmation bias and evaluation bias: When are preference-inconsistent recommendations effective—and when not? Computers in Human Behavior, 28, 2280–2290.

    Article  Google Scholar 

  • Schwind, C., Buder, J., Cress, U., & Hesse, F. W. (2012). Preference-inconsistent recommendations: An effective approach for reducing confirmation bias and stimulating divergent thinking? Computers & Education, 58, 787–796.

    Article  Google Scholar 

  • Stahl, G. (2005). Group cognition: Computer support for collaborative knowledge building. Cambridge, MA: MIT Press.

    Book  Google Scholar 

  • Stasser, G., & Titus, W. (2003). Hidden profiles: A brief history. Psychological Inquiry, 14, 304–313.

    Article  Google Scholar 

  • Suthers, D., Girardeau, L., & Hundhausen, C. (2003). Deictic roles of external representations in face-to-face and online collaboration. In B. Wasson, S. Ludvigsen, & U. Hoppe (Eds.), Designing for change (pp. 173–182). Berlin: Springer.

    Google Scholar 

  • Thiemann, D., & Engelmann, T. (2015). Computer-supported preference awareness in negotiation teams for fostering accurate joint priorities. In D. Cosley, A. Forte, C. Luigina, & D. McDonald (Eds.), Proceedings of the 18th ACM Conference Companion on Computer Supported Cooperative Work & Social Computing (CSCW'15 Companion) (pp. 227–230). New York, NY: ACM.

    Google Scholar 

  • Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Cambridge: University Press.

    Google Scholar 

  • Webb, N. M. (1991). Task-related verbal interaction and mathematics learning in small groups. Journal for Research in Mathematics Education, 22, 366–389.

    Article  Google Scholar 

  • Wegner, D. M. (1987). Transactive memory: A contemporary analysis of the group mind. In B. Mullen & G. R. Goethals (Eds.), Theories of group behavior (pp. 185–208). New York: Springer.

    Chapter  Google Scholar 

  • Zahn, C. (2017). Digital design and learning: Cognitive-constructivist perspectives on individual and group knowledge processes in design problem solving. In S. Schwan & U. Cress (Eds.), The psychology of digital learning: Constructing, exchanging, and acquiring knowledge with digital media. New York: Springer.

    Google Scholar 

  • Zigurs, I., & Buckland, B. K. (1998). A theory of task/technology fit and group support systems effectiveness. MIS Quarterly, 1998, 313–334.

    Article  Google Scholar 

Download references

Acknowledgments

This chapter constitutes the summary (output variable) of many discussions (process variable) that were conducted during Lab meetings of the Tübingen IWM Knowledge Exchange Lab between 2012 and 2015. Therefore, the author would like to thank previous and current members of the Lab (in alphabetical order) for their input: Inga Bause, Carmen Biel, Moritz Borchers, Irina Brich, Brett Buttliere, Gabriele Cierniak, Tanja Engelmann, Friedrich W. Hesse, Katrin König, Richard Kolodziej, Michail Kozlov, Karsten Krauskopf, Anja Rudat, Michael Schubert, Julien Schweitzer, Christina Schwind, Irene Skuballa, Daniel Thiemann, and Daniel Wessel.

Author information

Authors and Affiliations

  1. Leibniz-Institut für Wissensmedien, Schleichstrasse 6, 72076, Tübingen, Germany

    Jürgen Buder

Authors
  1. Jürgen Buder
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jürgen Buder .

Editor information

Editors and Affiliations

  1. Realistic Depictions, Leibniz-Institut für Wissensmedien, Tübingen, Germany

    Stephan Schwan

  2. Knowledge Construction, Leibniz-Institut für Wissensmedien, Tübingen, Germany

    Ulrike Cress

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this chapter

Cite this chapter

Buder, J. (2017). A Conceptual Framework of Knowledge Exchange. In: Schwan, S., Cress, U. (eds) The Psychology of Digital Learning. Springer, Cham. https://doi.org/10.1007/978-3-319-49077-9_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-49077-9_6

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49075-5

  • Online ISBN: 978-3-319-49077-9

  • eBook Packages: EducationEducation (R0)

Publish with us

Policies and ethics

Search

Navigation