When coding-and-counting is not enough: using epistemic network analysis (ENA) to analyze verbal data in CSCL research
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Andrist, S., Collier, W., Gleicher, M., Mutlu, B., & Shaffer, D. W. (2015). Look together: Analyzing gaze coordination with epistemic network analysis. Frontiers in Psychology, 6(1016).
Arastoopour, G., Shaffer, D. W., Swiecki, Z., Ruis, A. R., & Chesler, N. C. (2016). Teaching and assessing engineering design thinking with virtual internships and epistemic network analysis. International Journal of Engineering Education, 32(3B), 1492–1501.
Bakeman, R., & Gottman, J. M. (1997). Observing interaction: An introduction to sequential analysis (2nd ed.). New York, NY: Cambridge University Press.
Bannert, M., Reimann, P., & Sonnenberg, C. (2014). Process mining techniques for analysing patterns and strategies in students’ self-regulated learning. Metacognition and learning, 9(2), 161–185.
Bause, I. M., Brich, I. R., Wesslein, A. K., & Hesse, F. W. (2018). Using technological functions on a multi-touch table and their affordances to counteract biases and foster collaborative problem solving. International Journal of Computer-Supported Collaborative Learning, 13(1), 7–33.
Chi, M. T. H. (1997). Quantifying qualitative analyses of verbal data: A practical guide. Journal of the Learning Sciences, 6(3), 271–315.
Chiu, M. M., & Khoo, L. (2005). A new method for analyzing sequential processes: Dynamic multilevel analysis. Small Group Research, 36(5), 600–631.
Collier, W., Ruis, A. R., & Shaffer, D. W. (2016). Local versus global connection making in discourse. In C. K. Looi, J. L. Polman, U. Cress, & P. Reimann (Eds.), Transforming learning, empowering learners: The International Conference of the Learning Sciences (ICLS) 2016, volume 1 (pp. 426–433). Singapore: International Society of the Learning Sciences.
Cress, U., & Hesse, W. (2013). Quantitative methods for studying small groups. In C. A. Hmelo-Silver, C. Chinn, C. Chan, & A. M. O’Donnell (Eds.), The international handbook of collaborative learning (pp. 93–111). New York, NY: Routledge.
Csanadi, A., Kollar, I., & Fischer, F. (2015). Internal scripts and social context as antecedents of teacher students’ scientific reasoning. Paper presented at the 16th Biennial Conference of the European Association for Research on Learning and Instruction (EARLI), Limassol, Cyprus.
Csanadi, A., Kollar, I., & Fischer, F. (2016). Scientific reasoning and problem solving in a practical domain: Are two heads better than one? In C. K. Looi, J. L. Polman, U. Cress, & P. Reimann (Eds.), Transforming learning, empowering learners: The International Conference of the Learning Sciences (ICLS) 2016, volume 1 (pp. 50–57). Singapore: International Society of the Learning Sciences.
Csanadi, A., Eagan, B., Shaffer, D., Kollar, I., & Fischer, F. (2017). Collaborative and individual scientific reasoning of pre-service teachers: New insights through epistemic network analysis (ENA). In B. K. Smith, M. Borge, E. Mercier, & K. Y. Lim (Eds.), Making a Difference: Prioritizing Equity and Access in CSCL, 12 th International Conference on Computer-Supported Collaborative Learning (CSCL) 2017, volume 1 (pp. 215–222). Philadelphia: International Society of the Learning Sciences.
Dyke, G., Kumar, R., Ai, H., & Rosé, C. P. (2012). Challenging assumptions: Using sliding window visualizations to reveal time-based irregularities in CSCL processes. In J. van Aalst, K. Thompson, M. J. Jacobson, & P. Reimann (Eds.), The future of learning: Proceedings of the 10th international conference of the learning sciences (ICLS) 2012 (Vol. 1, pp. 363–370). Sydney: International Society of the Learning Sciences.
Eagan, B., & Hamilton, E. (2018). Epistemic Network Analysis of an International Digital Makerspace in Africa, Europe, and the US. Paper presented at the annual meeting of the American education research association. New York: NY.
Ericsson, K. A., & Simon, H. A. (1980). Verbal reports as data. Psychological Review, 87(3), 215–251.
Fischer, F., Kollar, I., Ufer, S., Sodian, B., & Hussmann, H. (2014). Pekrun, R.,…Eberle, J. Scientific reasoning and argumentation: Advancing an interdisciplinary research agenda in education. Frontline Learning Research, 5, 28–45.
Fox, M. C., Ericsson, K. A., & Best, R. (2011). Do procedures for verbal reporting of thinking have to be reactive? A meta-analysis and recommendations for best reporting methods. Psychological Bulletin, 137(2), 316–344.
Hmelo-Silver, C. E., Jordan, R., Liu, L., & Chernobilsky, E. (2011). Representational tools for understanding complex computer-supported collaborative learning environments. In.: Puntambekar S., Erkens G., Hmelo-silver C. (Eds). Analyzing Interactions in CSCL. Computer-Supported Collaborative Learning, 12, 83–106.
Hmelo-Silver, C. E., Jordan, R., & Sinha, S. (2013). Seeing to understand. Using visualizations to understand learning in technology-rich learning environments. In R. Luckin, S. Puntambekar, P. Goodyear, B. Grabowski, J. Underwood, & N. Winters (Eds.), Handbook of Design in Educational Technology (pp. 457–471). New York, NY: Routledge.
Jeong, A. (2005). A guide to analyzing message–response sequences and group interaction patterns in computer-mediated communication. Distance Education, 26(3), 367–383.
Kapur, M. (2011). Temporality matters: Advancing a method for analyzing problem-solving processes in a computer-supported collaborative environment. International Journal of Computer-Supported Collaborative Learning, 6(1), 39–56.
Klahr, D., & Dunbar, K. (1988). Dual space search during scientific reasoning. Cognitive Science, 12(1), 1–48.
Kollar, I., Fischer, F., & Slotta, J. D. (2007). Internal and external scripts in computer-supported collaborative inquiry learning. Learning and Instruction, 17(6), 708–721.
Lämsä, J., Hämäläinen, R., Koskinen, P., & Viiri, J. (2018). Visualising the temporal aspects of collaborative inquiry-based learning processes in technology-enhanced physics learning. International Journal of Science Education, 40(14), 1697–1717.
Marquart, C. L., Hinojosa, C., Swiecki, Z., & Shaffer, D. W. (2018). Epistemic Network Analysis (Version 0.1.0) [Software]. Available from http://app.epistemicnetwork.org
Mercer, N. (2008). The seeds of time: Why classroom dialogue needs a temporal analysis. Journal of the Learning Sciences, 17(1), 33–59.
Mullins, D., Rummel, N., & Spada, H. (2011). Are two heads always better than one? Differential effects of collaboration on students’ computer-supported learning in mathematics. International Journal of Computer-Supported Collaborative Learning, 6(3), 421–443.
Reimann, P. (2009). Time is precious: Variable-and event-centred approaches to process analysis in CSCL research. International Journal of Computer-Supported Collaborative Learning, 4(3), 239–257.
Reimann, P., & Yacef, K. (2013). Using process mining for understanding learning. In R. Luckin, S. Puntambekar, P. Goodyear, B. Grabowski, J. D. M. Underwood, & N. Winters (Eds.), Handbook of design in educational technology (pp. 472–481). New York, NY: Routledge.
Roschelle, J., & Teasley, S. D. (1995). The construction of shared knowledge in collaborative problem solving. In C. O’Malley (Ed.), Computer supported collaborative learning (pp. 69–97). Berlin: Springer.
Ruis, A.R., Rosser, A.A., Quandt-Walle, C., Nathwani, J.N., Shaffer, D.W., & Pugh, C.M. (2018). The hands and head of a surgeon: Modeling operative competency with multimodal epistemic network analysis. American Journal of Surgery.
Schwaighofer, M., Bühner, M., & Fischer, F. (2017). Executive functions in the context of complex learning: Malleable moderators? Frontline Learning Research, 5(1), 58–75.
Shaffer, D. W. (2007). How computer games help children learn. New York, NY: Palgrave Macmillan.
Shaffer, D. W. (2012). Models of situated action: Computer games and the problem of transfer. In C. Steinkuehler, K. Squire, & S. Barab (Eds.), Games learning, and society: Learning and meaning in the digital age (pp. 403–433). Cambridge, UK: Cambridge University Press.
Shaffer, D. W. (2017). Quantitative ethnography. Madison, WI: Cathcart.
Shaffer, D. W., & Ruis, A. R. (2017). Epistemic network analysis: A worked example of theory-based learning analytics. In C. Lang, G. Siemens, A. F. Wise, & D. Gasevic (Eds.), Handbook of learning analytics (pp. 175–187) Society for Learning Analytics Research.
Shaffer, D. W., Hatfield, D., Svarovsky, G., Nash, P., Nulty, A., Bagley, E., Frank, K., Rupp, A., & Mislevy, R. (2009). Epistemic network analysis: A prototype for 21st century assessment of learning. International Journal of Learning and Media, 1(2), 33–53.
Shaffer, D. W., Collier, W., & Ruis, A. R. (2016). A tutorial on epistemic network analysis: Analyzing the structure of connections in cognitive, social, and interaction data. Journal of Learning Analytics, 3(3), 9–45.
Shaffer, D. W., & Serlin, R. C. (2004). What Good are Statistics that Don’t Generalize? Educational Researcher, 33(9), 14–25.
Siebert-Evenstone, A. L., Arastoopour, G., Collier, W., Swiecki, Z., Ruis, A. R., & Shaffer, D. W. (2016). In search of conversational grain size: Modeling semantic structure using moving stanza windows. In C. K. Looi, J. L. Polman, U. Cress, & P. Reimann (Eds.), Transforming learning, empowering learners: The International Conference of the Learning Sciences (ICLS) 2016, volume 1 (pp. 631–638). Singapore: International Society of the Learning Sciences.
Siebert-Evenstone, A., Arastoopour Irgens, G., Collier, W., Swiecki, Z., Ruis, A. R., & Williamson Shaffer, D. (2017). In search of conversational grain size: Modelling semantic structure using moving stanza windows. Journal of Learning Analytics, 4(3), 123–139.
Stegmann, K., Wecker, C., Weinberger, A., & Fischer, F. (2012). Collaborative argumentation and cognitive elaboration in a computer-supported collaborative learning environment. Instructional Science, 40(2), 297–323.
Strijbos, J. W., Martens, R. L., Prins, F. J., & Jochems, W. M. (2006). Content analysis: What are they talking about? Computers & Education, 46(1), 29–48.
Sullivan, S. A., Warner-Hillard, C., Eagan, B. R., Thompson, R., Ruis, A. R., Haines, K., & Jung, H. S. (2018). Using epistemic network analysis to identify targets for educational interventions in trauma team communication. Surgery, 163(4), 938–943.
Suthers, D. D. (2005). Technology affordances for intersubjective learning: A thematic agenda for CSCL. In T. Koschmann, D. Suthers, & T. W. Chan (Eds.), Computer supported collaborative learning 2005: The next 10 years (pp. 662–671). Mahwah, NJ: Lawrence Erlbaum Associates.
Suthers, D., & Medina, R. (2011). Tracing interaction in distributed collaborative learning. In.: Puntambekar S., Erkens G., Hmelo-silver C. (Eds). Analyzing Interactions in CSCL. Computer-Supported Collaborative Learning, 12, 341–366.
Teasley, S. D. (1995). The role of talk in children’s peer collaborations. Developmental Psychology, 31(2), 207–220.
Vogel, F., & Weinberger, A. (2018). Quantifying qualities of collaborative learning processes. In F. Fischer, C. E. Hmelo-Silver, S. R. Goldman, & P. Reimann (Eds.), International handbook of the learning sciences. New York, NY: Routledge.
Wegerif, R., & Mercer, N. (1997). Using computer-based text analysis to integrate qualitative and quantitative methods in research on collaborative learning. Language and Education, 11(4), 271–286.