Skip to main content
Log in

An examination of CSCL methodological practices and the influence of theoretical frameworks 2005–2009

  • Published:
International Journal of Computer-Supported Collaborative Learning Aims and scope Submit manuscript

Abstract

The goal of this research is to provide an overview of CSCL methodological practices. CSCL is a vibrant interdisciplinary research field where several different theoretical and methodological traditions converge. Given the diversity of theoretical and methodological traditions that co-exist in CSCL, it is important to document the kinds and range of methodological practices and examine how they are related to the diverse theoretical perspectives in the field. In the current study, we examined CSCL research methodology in terms of (1) research designs, (2) research settings, (3) data sources, and (4) analysis methods. We then examined how these dimensions are related to the theoretical frameworks of the research. A content analysis was carried out based on empirical CSCL studies published in seven leading journals of the field during 2005–2009. The analysis identified the dominant CSCL research practices. We found that the modal CSCL study used descriptive designs that were carried out in classroom settings, typically collected questionnaires and/or analyzed the data quantitatively. CSCL research methods, however, were also quite diverse and eclectic, as researchers used range of data collection and analysis practices. Methodological practices were influenced by the theoretical framework of the research. A cluster analysis examined how these practices co-varied and revealed four distinctive method-theory clusters. Remaining methodological challenges of the field are discussed along with suggestions to move the field toward meaningful synthesis.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Notes

  1. Studies that used more than one design (N = 1) or research settings (N = 8) were excluded from the analysis.

References

  • Alpers, G. W., Winzelberg, A. J., Classen, C., Roberts, H., Dev, P., Koopman, C., et al. (2005). Evaluation of computerized text analysis in an Internet breast cancer support group. Computers in Human Behavior, 21, 361–376.

    Google Scholar 

  • Anderson, T., & Shattuck, J. (2012). Design-based research: A decade of progress in education research? Educational Researcher, 41(1), 16–25.

    Google Scholar 

  • Ares, N. (2008). Cultural practices in networked classroom learning environments. International Journal of Computer-Supported Collaborative Learning, 3, 301–326.

    Google Scholar 

  • Arnseth, H. C., & Ludvigsen, S. (2006). Approaching institutional contexts: Systemic versus dialogic research in CSCL. International Journal of Computer-Supported Collaborative Learning, 1, 167–185.

    Google Scholar 

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

    Google Scholar 

  • Barab, S. A., & Kirshner, D. (2001). Methodologies for capturing learner practices occurring as part of dynamic learning environments. Journal of the Learning Sciences, 10, 5–6.

    Google Scholar 

  • Barab, S. A., & Squire, K. D. (2004). Design-based research: Putting a stake in the ground. Journal of the Learning Sciences, 13(1), 1–14.

    Google Scholar 

  • Barron, B. (2006). Interest and self-sustained learning as catalysts of development: A learning ecology perspective. Human Development, 49(4), 193.

    Google Scholar 

  • Beers, P., Boshuizen, H. P. A., Kirschner, P., & Gijselaers, W. H. (2007). The analysis of negotiation of common ground in CSCL. Learning and Instruction, 17, 427–435.

    Google Scholar 

  • Berge, O., & Fjuk, A. (2006). Understanding the roles of online meetings in a net-based course. Journal of Computer Assisted Learning, 22, 13–23.

    Google Scholar 

  • Blin, F., & Munro, M. (2008). Why hasn’t technology disrupted academics’ teaching practices? Understanding resistance to change through the lens of activity theory. Computers and Education, 50, 475–490.

    Google Scholar 

  • Borrego, M. (2007). Conceptual difficulties experienced by engineering faculty becoming engineering education researchers. Journal of Engineering Education, 96(2), 91–102.

    Google Scholar 

  • Brown, A. L. (1992). Design experiments: Theoretical and methodological challenges in creating complex interventions in classroom settings. Journal of the Learning Sciences, 2(2), 141–178.

    Google Scholar 

  • Bryman, A. (1984). The debate about quantitative and qualitative research: A question of method or epistemology. The British Journal of Sociology, 35(1), 75–92.

    Google Scholar 

  • Calinski, T., & Harabasz, J. (1974). A dendrite method for cluster analysis. Communications in Statistics-Theory and Methods, 3(1), 1–27.

    Google Scholar 

  • Chen, W., & Hirschheim, R. (2004). A paradigmatic and methodological examination of information systems research from 1991 to 2001. Information Systems Journal, 14, 197–235.

    Google Scholar 

  • Chi, M. T. H. (1997). Quantifying qualitative analyses of verbal data: A practical guide. Journal of the Learning Sciences, 6(3), 271–315.

    Google Scholar 

  • Chi, M. T. H. (2009). Active-constructive-interactive: A conceptual framework for differentiating learning activities. Topics in Cognitive Science, 1, 73–105.

    Google Scholar 

  • Chi, M. T. H., Siler, S. A., Jeong, H., Yamauchi, T., & Hausmann, R. G. (2001). Learning from human tutoring. Cognitive Science, 25, 471–533.

    Google Scholar 

  • Cho, K., & Schunn, C. (2007). Scaffolded writing and rewriting in the discipline: A web-based reciprocal peer review system. Computers and Education, 48, 409–426.

    Google Scholar 

  • Cobb, P., & Jackson, K. (2008). The consequences of experimentalism in formulating recommendations for policy and practice in mathmatics education. Educational Researcher, 37(9), 573–581.

    Google Scholar 

  • Cooper, H., Hedges, L. V., & Valentine, J. C. (Eds.). (2009). Handbook of research synthesis and meta-analysis (2nd ed.). New York: Russell Sage.

    Google Scholar 

  • Council, N. R. (2002). Scientific culture and educational research. Washington: National Academies of Press.

    Google Scholar 

  • Cress, U. (2008). The need for considering multilevel analysis in CSCL research—an appeal for the use of more advanced statistical methods. International Journal of Computer-Supported Collaborative Learning, 3, 69–84.

    Google Scholar 

  • Cress, U., Barquero, B., Schwain, S., & Hesse, F. W. (2007). Improving quality and quantity of contributions: Two models for promoting knowledge exchange with shared database. Computers and Education, 49, 423–440.

  • Davies, A., Fidler, D., & Gorbis, M. (2011). Future work skills 2020. Palo Alto: Institue for the future.

    Google Scholar 

  • De Laat, M., Lally, V., Lipponen, L., & Simons, R.-J. (2007). Online teaching in networked learning communities: A multi-method approach to studying the role of the teacher. Instructional Science, 35, 257–286.

    Google Scholar 

  • De Lisi, R., & Golbeck, S. L. (1999). Implications of Piagetian theory for peer learning. In A. M. O’Donnell & A. King (Eds.), Cognitive perspectives on peer learning. Mahwah: Erlbaum.

    Google Scholar 

  • De Wever, B., Schellens, T., Valcke, M., & van Keer, H. (2006). Content analysis schemes to analyze transcripts of online asynchronous discussion groups: a review. Computers and Education, 46, 6–28.

    Google Scholar 

  • De Wever, B., van Keer, H., Schellens, T., & Valcke, M. (2007). Applying multi-level modelling to content analysis data: Methodological issues in the study of role assignment in asynchronous discussion groups. Learning and Instruction, 17, 436–447.

    Google Scholar 

  • Dillenbourg, P., Jarvela, S., & Fischer, F. (2009). The evolution of research on computer-supported collaborative learning. In N. Balacheff (Ed.), Technology-enhance learning. New York: Springer.

    Google Scholar 

  • Doise, W., Mugny, G., & Perret-Clermont, A. (1975). Social interaction and the development of cognitive operations. European Journal of Social Psychology, 5(3), 367–383.

    Google Scholar 

  • Dori, Y. J., & Belcher, J. (2005). How does technology-enabled active learning affect undergraduate students’ understanding of electromagnetism concepts? Journal of the Learning Sciences, 14(2), 243–279.

    Google Scholar 

  • Dringus, L. P., & Ellis, T. (2005). Using data mining as a strategy for assessing asynchronous discussion forum. Computers and Education, 45, 141–160.

    Google Scholar 

  • Dyke, G., Lund, K., & Girardot, J.-J. (2009). Tatiana: An environment to support the CSCL analysis process. In Proceedings of the 8th International Conference of the Learning Sciences, International Society of the Learning Sciences.

  • Ellis, R. A., Goodyear, P., Prosser, M., & O’Hara, A. O. (2006). How and what university students learn through online and face-to-face discussion: conceptions, intentions and approaches. Journal of Computer Assisted Learning, 22(4), 244–256.

    Google Scholar 

  • Engeström, R. (2001). Expansive learning at work: Toward an activity theoretical reconceptualization. Journal of Education and Work, 14(1), 133–156.

    Google Scholar 

  • Erkens, G., & Janssen, J. (2008). Automatic coding of dialogue acts in collaboration protocols. International Journal of Computer-Supported Collaborative Learning, 3, 447–470.

    Google Scholar 

  • Everitt, B. S., Landau, S., Leese, M., & Stahl, D. (2011). Cluster analysis (Wiley series in probability and statistics) (5th ed.). West Sussex: Wiley.

    Google Scholar 

  • Finch, H. (2005). Comparison of distance measures in cluster analysis with dichotomous data. Journal of Data Science, 3(1), 85–100.

    Google Scholar 

  • Fuks, H., Pimentel, M., & de Lucena, C. J. P. (2006). R-U-Typing-2-Me? Evolving a chat tool to increase understanding in learning activities. International Journal of Computer-Supported Collaborative Learning, 1, 117–142.

    Google Scholar 

  • Gee, J. P., & Green, J. L. (1998). Discourse analysis, learning, and school practice: A methodological study. Review of Research in Education, 23, 119–169.

    Google Scholar 

  • Glaser, B. G., & Straus, A. (1967). The discovery of grounded theory: Strategies for qualitative research. New Brunswick: Aldine transaction.

    Google Scholar 

  • Greenhow, C., Robelia, B., & Hughes, J. E. (2009). Learning, teaching, and scholarship in a digital age web 2.0 and classroom research: what path should we take now? Educational Researcher, 38(4), 246–259.

    Google Scholar 

  • Greeno, J. G. (2006). Authorative, accountable positioning and connected, general knowing: progressive themes in understanding transfer. Journal of the Learning Sciences, 15(4), 537–547.

    Google Scholar 

  • Guribye, F., & Wasson, B. (2002). The ethnography of distributed collaborative learning. In Proceedings of the Conference on Computer Support for Collaborative Learning: Foundations for a CSCL Community. International Society of the Learning Sciences.

  • Hew, K. F., Kale, U., & Kim, N. (2007). Past research in instructional technology: Results of a content analysis of empirical studies published in three prominent instructional technology journals from the year 2000 through 2004. Journal of Educational Computing Research, 36(3), 269–300.

    Google Scholar 

  • Hewitt, J., & Brett, C. (2007). The relationship between class size and online activity patterns in asynchronous computer conferencing environments. Computers and Education, 49, 1258–1271.

    Google Scholar 

  • Hmelo-Silver, C. E. (2003). Analyzing collaborative knowledge construction: Multiple methods for integrated understanding. Computers and Education, 41, 397–420.

    Google Scholar 

  • Howley, I., Kumar, R., Mayfield, E., Dyke, G., & Rosé, C. P. (2013). Gaining insights from sociolinguistic style analysis for redesign of conversational agent based support for collaborative learning Productive multivocality in the analysis of group interactions (pp. 477–494): Springer.

  • Hrastinski, S., & Keller, C. (2007). An examination of research approaches that underlie research on educational technology: A review from 2000 to 2004. Journal of Educational Computing Research, 36(2), 175–190.

    Google Scholar 

  • Hummel, H. G. K., Burgos, D., Tattersall, F., Brouns, F., Kurvers, H., & Koper, R. (2005). Encouraging contributions in learning networks using incentive mechanisms. Journal of Computer Assisted Learning, 21, 355–365.

    Google Scholar 

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

    Google Scholar 

  • Jacobs, N., & McFarlane, A. (2005). Conferences as learning communities: Some early lessons in using ‘back-channel’ technologies at an academic conference-distributed intelligence or divided attention? Journal of Computer Assisted Learning, 21, 317–329.

    Google Scholar 

  • Jeong, H. (2013). Verbal data analysis for understanding interactions. In C. Hmelo-Silver, A. M. O’Donnell, C. Chan, & C. Chinn (Eds.), The international handbook of collaborative learning (pp. 168–183). London: Routledge.

    Google Scholar 

  • Jeong, H., & Hmelo-Silver, C. E. (2010a). Technology use in CSCL: A content meta-analysis. In Proceedings of the 43rd Hawaiian International Conference on System Science. IEEE.

  • Jeong, H., & Hmelo-Silver, C. E. (2010b). An overview of CSCL methodologies. In Proceedings of the 9th International Conference of the Learning Sciences, International Society of the Learning Sciences.

  • Jeong, H., & Hmelo-Silver, C. E. (2011). A portrait of CSCL methodologies. In Proceedings of the 10th International Conference of the Learning Sciences. International Society of the Learning Sciences.

  • Jeong, H., & Hmelo-Silver, C. E. (2012). Technology supports in CSCL. In Proceedings of the 11th International Conference of the Learning Sciences. International Society of the Learning Sciences.

  • Jermann, P., & Dillenbourg, P. (2008). Group mirrors to support interaction regulation in collaborative problem solving. Computers and Education, 51, 279–296.

    Google Scholar 

  • Johnson, R., & Christensen, L. (2008). Educational research: Quantitative, qualitative, and mixed approaches. Thousand Oaks: Sage.

    Google Scholar 

  • Johnson, R., & Onwuegbuzie, A. J. (2004). Mixed method research: A research paradigm whose time has come. Educational Researcher, 33(7), 14–26.

    Google Scholar 

  • Jordan, B., & Henderson, A. (1995). Interaction analysis: Foundations and practice. The Journal of the Learning Science, 4(1), 39–103.

    Google Scholar 

  • Kelly, A. (2004). Design research in education: Yes, but is it methodological? Journal of the Learning Sciences, 13(1), 115–128.

    Google Scholar 

  • Keppel, G., & Wickens, T. D. (2004). Design and analysis. Upper Saddle River: Prentice Hall.

    Google Scholar 

  • Koschmann, T. (2013). Conversation analysis and collaborative learning. In C. Hmelo-Silver, A. M. O’Donnell, C. Chan, & C. Chinn (Eds.), International handbook of collaborative learning. London: Taylor and Francis.

    Google Scholar 

  • Koschmann, T., & LeBaron, C. D. (2003). Reconsidering common ground: Examining Clark’s contribution theory in the OR. In K. Kuutti, E. Karsten, G. Fitzpatrick, P. Dourish, & K. Schmidt (Eds.), ECSCW 2003 (pp. 81–98). Amsterdam: Kluwer Academic Publishing.

    Google Scholar 

  • Krauss, R. M., & Fussell, S. R. (1990). Mutual knowledge and communicative effectiveness. In J. Galegher, R. E. Kraut, & C. Edigo (Eds.), Intellectual teamwork: Social and technological foundations of cooperative work. Hillsdale: Erlbaum.

    Google Scholar 

  • Lee, E. Y. C., Chan, C. K. K., & van Aalst, J. (2006). Students assessing their own collaborative knowledge building. International Journal of Computer-Supported Collaborative Learning, 1, 57–87.

    Google Scholar 

  • Levine, J. M., & Thompson, L. (1996). Conflict in groups. In E. T. Higgins & A. Kruglanski (Eds.), Social psychology: Handbook of basic principles. New York: The Guilford Press.

    Google Scholar 

  • Lim, C. P., & Barnes, S. (2005). A collective case study of the use of ICT in economics courses: A sociocultural approach. Journal of the Learning Sciences, 14(4), 489–526.

    Google Scholar 

  • Long, P., & Siemens, G. (2011). Penetrating the fog: Analytics in learning and education. EDUCAUSE Review, 46(5), 30–32.

    Google Scholar 

  • Markett, C., Sanchez, I. A., Weber, S., & Tangney, B. (2006). Using short message service to encourage interactivity in the classroom. Computers and Education, 46, 280–293.

    Google Scholar 

  • Martin, T., & Sherin, B. (2013). Learning analytics and computational techniques for detecting and evaluating patterns in learning: an introduction to the special issue. Journal of the Learning Sciences, 22(4), 511–520. doi:10.1080/10508406.2013.840466.

    Google Scholar 

  • Martinez, A., Dimitriadis, Y., & Fuente, P. d. l. (2003). Interaction analysis for formative evaluation in CSCL. In M. Llamas, M. J. Fernández & L. E. Anido (Eds.), Computers and Education. Towards a Lifelong Learning Society (pp. 227–238): Kluwer Academic.

  • Martinez, A., Dimitriadis, Y., Gomez-Sanchez, E., Rubia-Avi, B., Jorrin-Abellan, I., & Marcos, J. A. (2006). Studying participation networks in collaborating using mixed methods. International Journal of Computer-Supported Collaborative Learning, 1, 383–408.

    Google Scholar 

  • Mayring, P. (2000). Qualitative content analysis. Forum: Qualitative Social Research, 1(2). Art. 20, http://nbn-resolving.de/urn:nbn:de:0114-fqs0002204.

  • McCarthy, C., Bligh, J., Jennings, K., & Tangney, B. (2005). Virtual collaborative learning environments for music networked drumsteps. Computers and Education, 44, 173–195.

    Google Scholar 

  • Meier, A., Spada, H., & Rummel, N. (2007). A rating scheme for assessing the quality of computer-supported collaboration processes. International Journal of Computer-Supported Collaborative Learning, 2, 63–86.

    Google Scholar 

  • Miyake, N. (2006). Computer supported collaborative learning. In R. Andrew & C. Haythornwaite (Eds.), Sage handbook of e-learning research. London: Sage.

    Google Scholar 

  • Morken, E. M., Divitini, M., & Haugalokken. (2007). Enriching spaces in practice-based education to support collaboration while mobile: the case of teacher education. Journal of Computer Assisted Learning, 23, 300–311.

    Google Scholar 

  • Morrow, R. A., & Brown, D. B. (1994). Deconstructing the conventional discourse of methodology. Critical theory and methodology. Thousand Oaks: Sage Publication.

    Google Scholar 

  • Munneke, L., Andriessen, J., Kanselaar, G., & Kirschner, P. (2007). Supporting interactive argumentation: influence of representational tools on discussing a wicked problem. Computers in Human Behavior, 23, 1072–1088.

    Google Scholar 

  • Naidu, S., & Jarvela, S. (2006). Analyzing CMC for what? Computers and Education, 46, 96–103.

    Google Scholar 

  • Neuendorf, K. A. (2002). The content analysis: Guidebook. London: Thousand Oaks.

    Google Scholar 

  • Pintrich, P. R. (1999). The role of motivation in prompting and sustaining self-regulated learning. International Journal of Educational Research, 31, 459–470.

    Google Scholar 

  • Plomp, T., & Nieveen, N. (2007). An introduction to educational design research. In Proceedings of the Seminar Conducted at the East China Normal University. Netherlands: SLO-Netherlands Institute for Curriculum Development.

  • Powell, W. W., Koput, K. W., & Smith-Doerr, L. (1996). Interorganizational collaboration and the locus of innovation: networks of learning in biotechnology. Administrative Science Quarterly, 41(1), 116–145.

    Google Scholar 

  • Puntambekar, S. (2013). Mixed methods for analyzing collaborative learning. In C. Hmelo-Silver, A. M. O’Donnell, C. Chan, & C. Chinn (Eds.), The international handbook of collaborative learning. London: Taylor and Francis.

    Google Scholar 

  • Raffleff. (2007). The reliability of content analysis of computer conference communication. Computers and Education, 49, 230–242.

    Google Scholar 

  • Rick, M., & Guzdial, M. (2006). Situating coweb: A scholarship of application. International Journal of Computer-Supported Collaborative Learning, 1, 89–115.

    Google Scholar 

  • Robertson, J., & Howells, C. (2008). Computer game design: Opportunities for successful learning. Computers and Education, 50, 559–578.

    Google Scholar 

  • Rogoff, B. (1998). Cognition as a collaborative process. In W. Damon (Ed.), Handbook of child psychology (pp. 679–744). New York: Wiley.

    Google Scholar 

  • Romero, C., Ventura, S., & Garcia, E. (2008). Data mining in course management systems: Moodle case study and tutorial. Computers and Education, 51, 368–384.

    Google Scholar 

  • Rosé, C., Wang, Y.-C., Cui, Y., Arguello, J., Stegmann, K., Weinberger, A., et al. (2008). Analyzing collaborative learning processes automatically: Exploiting the advances of computational linguistics in computer-supported collaborative learning. International Journal of Computer-Supported Collaborative Learning, 3, 237–271.

    Google Scholar 

  • Rummel, N., & Spada, H. (2005). Learning to collaborate: An instructional approach to promoting collaborative problem solving in computer-mediated settings. Journal of the Learning Sciences, 14(2), 201–241.

    Google Scholar 

  • Sacks, H. (1992). Lectures on conversation. Malden: Blackwell.

    Google Scholar 

  • Salomon, G. (Ed.). (1993). Dsitributed cognitions: Psychological and educational considerations. Cambridge: Cambridge University Press.

    Google Scholar 

  • Sandoval, W. A. (2014). Conjecture mapping: An approach to systematic educational design research. Journal of the Learning Sciences, 23, 18–36.

    Google Scholar 

  • Schmid, E. C. (2008). Potential pedagogical benefits and drawbacks of multimedia use in the English language classroom equipped with interactive whiteboard technology. Computers and Education, 51, 1553–1568.

    Google Scholar 

  • Schwarz, B. B., & Glassner, A. (2007). The role of floor control and of ontology in argumentative activities with discussion-based tools. International Journal of Computer-Supported Collaborative Learning, 2, 449–478.

    Google Scholar 

  • Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental designs for generalized causal inference. New York: Houghton Mifflin Company.

    Google Scholar 

  • Shavelson, R. J. (1996). Statistical reasoning for the behavioral sciences (3rd ed.). Boston: Allyn & Bacon.

    Google Scholar 

  • Shavelson, R. J., Phillips, D. C., Towne, L., & Feuer, M. J. (2003). On the science of education design studies. Educational Researcher, 32(1), 25–28.

    Google Scholar 

  • Shiffrin, R. M., & Schneider, W. (1977). Controlled and automatic human information processing: II. Perceptual learning, automatic attending, and a general theory. Psychological Review, 84(2), 127–190.

    Google Scholar 

  • Shih, M., Feng, J., & Tsai, C.-C. (2008). Research and trends in the field of e-learning from 2001 to 2005: A content analysis of cognitive studies in selected journals. Computers and Education, 51, 955–967.

    Google Scholar 

  • Stahl, G. (2006). Group cognition: Computer support for building collaborative knowledge. Cambridge: MIT Press.

    Google Scholar 

  • Stahl, G. (2013). Learning across levels. International Journal of Computer-Supported Collaborative Learning, 8(1), 2–11.

    Google Scholar 

  • Stahl, G., Koschmann, T., & Suthers, D. D. (2006). Computer-supported collaborative learning: A historical perspective. In R. K. Sawyer (Ed.), Cambridge handbook of the learning sciences. New York: Cambridge University Press.

    Google Scholar 

  • Straus, A., & Corbin, J. (1990). Basics of qualitative research. Newbury Park: Sage publication.

    Google Scholar 

  • Strijbos, J., & Stahl, G. (2007). Methodological issues in developing a multi-dimensional coding procedure for small-group chat communication. Learning and Instruction, 17, 394–404.

    Google Scholar 

  • Strijbos, J., Martens, R. L., Prins, F. J., & Jochems, W. M. G. (2006). Content analysis: What are they talking about? Computers and Education, 46, 29–48.

    Google Scholar 

  • Sung, S., Shen, J., & Zhang, D. (2012). Toward a cognitive framework of interdisciplinary understanding. In Proceedings of the 11th International Conference of the Learning Sciences. International Society of the Learning Sciences.

  • Suthers, D. D. (2006). Technology affordances for intersubjective meaning making: A research agenda for CSCL. International Journal of Computer-Supported Collaborative Learning, 1, 315–337.

    Google Scholar 

  • Suthers, D. D., Lund, K., Rose, C., Teplovs, C., & Law, N. (2013). Productive multivocality in the analysis of group interactions. Cambridge: MIT Press.

    Google Scholar 

  • Swinglehurst, D., Russell, J., & Greenhalgh, T. (2008). Peer observation of teaching in the online environment: An action research approach. Journal of Computer Assisted Learning, 24, 383–393.

    Google Scholar 

  • The Secretary’s Commission on Achieving Necessary Skills. (1991). What work require of schools: A SCANS report for America 2000. Washington: US Department of Labor.

    Google Scholar 

  • Tulving, E., & Madigan, S. A. (1970). Memory and verbal learning. Annual Review of Psychology, 21, 437–484.

    Google Scholar 

  • Van der Meij, H., de Vries, B., Boersma, K., Pieters, J., & Wegerif, R. (2005). An examination of interactional coherence in email use in elementary school. Computers in Human Behavior, 21, 417–439.

    Google Scholar 

  • Van der Pol, J., Van den Berg, B., Admiraal, W. F., & Simons, P. R. J. (2008). The nature, reception, and use of online peer feedback in higher education. Computers and Education, 51(4), 1804–1817.

  • Van Drie, J., van Boxtel, C., Jaspers, J., & Kanselaar, G. (2005). Effect of representational guidance on domain specific reasoning in CSCL. Computers in Human Behavior, 21, 575–602.

    Google Scholar 

  • Von Glaserfeld, E. (1987). Learning as a constructive activity. In C. Janvier (Ed.), Problems of representation in the teaching and learning of mathematics (pp. 3–38). Hillsdale: Erlbaum.

    Google Scholar 

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

    Google Scholar 

  • What Works Clearninghouse. (2008). Procedures and standards handbook (version 2.1) Retrieved February 14, 2013, from http://ies.ed.gov/ncee/wwc/DocumentSum.aspx?sid=19.

  • Yanchar, S. C., & Williams, D. D. (2006). Reconsidering the compatibility thesis and electicism: Five proposed guidelines for method use. Educational Researcher, 35(9), 3-12.

  • Yang, Z., & Liu, Q. (2007). Research and development of web-based virtual online classroom. Computers and Education, 48(2), 171–184.

    Google Scholar 

  • Yukawa, J. (2006). Co-reflection in online learning: Collaborative critical thinking as narrative. International Journal of Computer-Supported Collaborative Learning, 1, 203–228.

    Google Scholar 

Download references

Acknowledgments

Preliminary findings from this research were published in Jeong and Hmelo-Silver (2010a, 2011). This research was funded in part by the National Research Foundation of Korea under Grant No. 2009-0068919 awarded to the first author and also by the US National Science Foundation under Grant No. 1249492 awarded to the first two authors. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the funding agencies. We thank Andrew Walker for his assistance with the cluster analysis.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Heisawn Jeong.

Electronic supplementary material

Below is the link to the electronic supplementary material.

ESM 1

(DOC 160 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jeong, H., Hmelo-Silver, C.E. & Yu, Y. An examination of CSCL methodological practices and the influence of theoretical frameworks 2005–2009. Intern. J. Comput.-Support. Collab. Learn. 9, 305–334 (2014). https://doi.org/10.1007/s11412-014-9198-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11412-014-9198-3

Keywords

Navigation