Prompting collaborative and exploratory discourse: An epistemic network analysis study | International Journal of Computer-Supported Collaborative Learning Skip to main content
Springer Nature Link
Log in

Prompting collaborative and exploratory discourse: An epistemic network analysis study

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

Abstract

By encouraging elementary students to work collaboratively, they can gain essential skills such as perspective taking, conflict negotiation, and asking for and receiving assistance. Epistemic Network Analysis (ENA) is an analytic technique that provides an alternative to more typical approaches to analyzing and synthesizing coded dialogue. This study used an easy-to-implement prompting intervention in the context of collaborative (pair) programming with upper elementary students to demonstrate the potential of ENA to understand the impact of the intervention. We found that intervention students—those given empirically-derived prompts in support of collaborative and exploratory talk—asked questions, justified their thinking, and offered alternative ideas in ways that were both qualitatively and quantitatively different from control students.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
¥17,985 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Japan)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

Notes

  1. See Shaffer et al., (2016) for a more detailed explanation of the mathematical models utilized in this analytic approach; see Arastoopour Irgens et al. (2015) and Sullivan et al. (2018) for examples of this kind of analysis

References

  • Adamson, D., Dyke, G., Jang, H., & Rosé, C.P. (2014). Towards an agile approach to adapting dynamic collaboration support to student needs. International Journal of Artificial Intelligence in Education, 24(1), 92–124.

    Article  Google Scholar 

  • Arastoopour, G., Shaffer, D.W., Swiecki, Z., Ruis, A., & Chesler, N.C. (2016). Teaching and assessing engineering design thinking with virtual internships and epistemic network analysis. International Journal of Engineering Education, 32(3), 1492–1501.

    Google Scholar 

  • Arastoopour Irgens, G., Shaffer, D.W., Swiecki, Z., Ruis, A., & Chesler, N.C. (2015). Teaching and assessing engineering design thinking with virtual internships and epistemic network analysis. International Journal of Engineering Education.

  • Asterhan, C.S., Schwarz, B.B., & Cohen-Eliyahu, N. (2014). Outcome feedback during collaborative learning: Contingencies between feedback and dyad composition. Learning and Instruction, 34, 1–10.

    Article  Google Scholar 

  • Baron, R.S. (2005). So right it’s wrong: Groupthink and the ubiquitous nature of polarized group decision making. Advances in Experimental Social Psychology.

  • Barron, B. (2003). When smart groups fail. The Journal of the Learning Sciences, 12(3), 307–359.

    Article  Google Scholar 

  • Bell, P. (2004). Promoting students’ argument construction and collaborative debate in the science classroom. Internet Environments for Science Education, 3, 115–143.

    Google Scholar 

  • Bennett, N., & Cass, A. (1989). The effects of group composition on group interactive processes and pupil understanding. British Educational Research Journal, 15(1), 19–32.

    Article  Google Scholar 

  • Branaghan, R.J. (1990). Pathfinder networks and multidimensional spaces: Relative strengths in representing strong associates. In Ablex series in computational sciences. Pathfinder associative networks. Studies in knowledge organization (pp. 111–120). Ablex Publishing.

  • Bressler, D.M., Bodzin, A.M., Eagan, B., & Tabatabai, S. (2019). Using epistemic network analysis to examine discourse and scientific practice during a collaborative game. Journal of Science Education and Technology, 28(5), 553–566.

    Article  Google Scholar 

  • Bungum, B., Bøe, M.V., & Henriksen, E.K. (2018). Quantum talk: How small-group discussions may enhance students’ understanding in quantum physics. Science Education, 102(4), 856–877.

    Article  Google Scholar 

  • Campe, S., Denner, J., Green, E., & Torres, D. (2020). Pair programming in middle school: variations in interactions and behaviors. Computer Science Education, 30(1), 22–46.

    Article  Google Scholar 

  • Colfer, C. (2011). What types of talk are boys and girls using when engaged in a collaborative design and technology task? PATT 25: CRIPT8 pp 113.

  • Cress, U., Stahl, G., Ludvigsen, S., & Law, N. (2015). The core features of cscl: Social situation, collaborative knowledge processes and their design. International Journal of Computer-Supported Collaborative Learning, 10 (2), 109–116.

    Article  Google Scholar 

  • Creswell, J.W., & Clark, V.L.P. (2017). Designing and conducting mixed methods research. Los Angeles: Sage Publications.

    Google Scholar 

  • Davidson, K., Larzon, L., & Ljunggren, K. (2010). Self-efficacy in programming among sts students. Retrieved August, 12, 2013.

    Google Scholar 

  • Deiglmayr, A., & Spada, H. (2010). Developing adaptive collaboration support: The example of an effective training for collaborative inferences. Educational Psychology Review, 22(1), 103–113.

    Article  Google Scholar 

  • Fernández, M, Wegerif, R., Mercer, N., & Rojas-Drummond, S. (2001). Re-conceptualizing “scaffolding” and the zone of proximal development in the context of symmetrical collaborative learning. The Journal of Classroom Interaction pp 40–54.

  • Fisher, E. (1993). Distinctive features of pupil-pupil classroom talk and their relationship to learning: How discursive exploration might be encouraged. Language and Education, 7(4), 239–257.

    Article  Google Scholar 

  • Frisby, B.N., & Martin, M.M. (2010). Instructor–student and student–student rapport in the classroom. Communication Education, 59(2), 146–164.

    Article  Google Scholar 

  • Goldsmith, T.E., Johnson, P.J., & Acton, W.H. (1991). Assessing structural knowledge. Journal of Educational Psychology, 83(1), 88.

    Article  Google Scholar 

  • Gweon, G., Rose, C., Carey, R., & Zaiss, Z. (2006). Providing support for adaptive scripting in an on-line collaborative learning environment. In Proceedings of the SIGCHI conference on human factors in computing systems (pp. 251–260).

  • Hardy, C., Harley, B., & Phillips, N. (2004). Discourse analysis and content analysis: Two solitudes. Qualitative Methods, 2(1), 19–22.

    Google Scholar 

  • Hennessy, S., Rojas-Drummond, S., Higham, R., Márquez, A.M., Maine, F., Ríos, R.M., García-Carrión, R., Torreblanca, O., & Barrera, M.J. (2016). Developing a coding scheme for analysing classroom dialogue across educational contexts. Learning Culture and Social Interaction, 9, 16–44.

    Article  Google Scholar 

  • Knight, S., Arastoopour, G., Williamson Shaffer, D., Buckingham Shum, S., & Littleton, K. (2014). Epistemic networks for epistemic commitments. In International conference of the learning sciences.

  • Maguire, P., Maguire, R., Hyland, P., & Marshall, P. (2014). Enhancing collaborative learning using paired-programming: Who benefits? AISHE-J: The All Ireland Journal of Teaching and Learning in Higher Education, 6(2), 1411–14125.

    Google Scholar 

  • Marquart, C., Hinojosa, C., Swiecki, Z., Eagan, B., & Shaffer, D. (2018). Epistemic network analysis (version 1.7.0)[software].

  • Marwan, S., Gao, G., Fisk, S., Price, T.W., & Barnes, T. (2020). Adaptive immediate feedback can improve novice programming engagement and intention to persist in computer science. In Proceedings of the 2020 ACM conference on international computing education research (pp. 194–203).

  • McDowell, C., Werner, L., Bullock, H.E., & Fernald, J. (2006). Pair programming improves student retention, confidence, and program quality. Communications of the ACM, 49(8), 90–95.

    Article  Google Scholar 

  • Mendes, E., Al-Fakhri, L.B., & Luxton-Reilly, A. (2005). Investigating pair-programming in a 2nd-year software development and design computer science course. In Proceedings of the 10th annual SIGCSE conference on Innovation and technology in computer science education (pp. 296–300).

  • Mercer, N. (2000). Words and minds–how we use words to think together.

  • Mercer, N. (2002). Words and minds: How we use language to think together. Evanston: Routledge.

    Book  Google Scholar 

  • Mercer, N. (2007). Sociocultural discourse analysis: Analysing classroom talk as a social mode of thinking. Journal of Applied Linguistics and Professional Practice, 1(2), 137–168.

    Article  Google Scholar 

  • Mercer, N., & Littleton, K. (2007). Dialogue and the development of children’s thinking: A sociocultural approach. Evanston: Routledge.

    Book  Google Scholar 

  • Mercer, N., Wegerif, R., & Dawes, L. (1999). Children’s talk and the development of reasoning in the classroom. British Educational Research Journal, 25 (1), 95–111.

    Article  Google Scholar 

  • Miyake, N. (1997). Making internal processes external for constructive collaboration. In Proceedings second international conference on cognitive technology humanizing the information age (pp. 119–123). IEEE.

  • Nikolaidou, G.N. (2012). Complus model: A new insight in pupils’ collaborative talk, actions and balance during a computer-mediated music task. Computers & Education, 58(2), 740–765.

    Article  Google Scholar 

  • Paulus, T.M., & Wise, A.F. (2019). Looking for insight, transformation, and learning in online talk. Evanston: Routledge.

    Book  Google Scholar 

  • Polo, C., Lund, K., Plantin, C., & Niccolai, G.P. (2016). Group emotions: The social and cognitive functions of emotions in argumentation. International Journal of Computer-Supported Collaborative Learning, 11(2), 123–156.

    Article  Google Scholar 

  • Price, T.W., Dong, Y., & Lipovac, D. (2017). isnap: towards intelligent tutoring in novice programming environments. In Proceedings of the 2017 ACM SIGCSE technical symposium on computer science education (pp. 483–488).

  • Resnick, M., Maloney, J., Monroy-Hernández, A., Rusk, N., Eastmond, E., Brennan, K., Millner, A., Rosenbaum, E., Silver, J., Silverman, B., & et al (2009). Scratch: programming for all. Communications of the ACM, 52(11), 60–67.

    Article  Google Scholar 

  • Rojas-Drummond, S., & Mercer, N. (2003). Scaffolding the development of effective collaboration and learning. International Journal of Educational Research, 39(1-2), 99–111.

    Article  Google Scholar 

  • Rojas-Drummond, S., & Zapata, M.P. (2004). Exploratory talk, argumentation and reasoning in mexican primary school children. Language and Education, 18(6), 539–557.

    Article  Google Scholar 

  • Roschelle, J., & Teasley, S.D. (1995). The construction of shared knowledge in collaborative problem solving. In Computer supported collaborative learning (pp. 69–97). Springer.

  • Ruvalcaba, O., Werner, L., & Denner, J. (2016). Observations of pair programming: Variations in collaboration across demographic groups. In Proceedings of the 47th ACM technical symposium on computing science education (pp. 90–95).

  • Schegloff, E.A. (1991). Conversation analysis and socially shared cognition. In Socially shared cognition. Washington: American Psychological Association.

  • Shaffer, D.W. (2006). Epistemic frames for epistemic games. Computers & Education, 46(3), 223–234.

    Article  Google Scholar 

  • Shaffer, D.W. (2017). Quantitative ethnography. Madison, Wisconsin: Cathcart Press.

    Google Scholar 

  • Shaffer, D.W., Hatfield, D., Svarovsky, G.N., Nash, P., Nulty, A., Bagley, E., Frank, K., Rupp, A.A., & Mislevy, R. (2009). Epistemic network analysis: A prototype for 21st-century assessment of learning. International Journal of Learning and Media 1(2).

  • 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.

    Article  Google Scholar 

  • Shawky, D., Badawi, A., Said, T., & Hozayin, R. (2014). Affordances of computer-supported collaborative learning platforms: a systematic review. In 2014 international conference on interactive collaborative learning (ICL) (pp. 633–651). IEEE.

  • Siebert-Evenstone, A.L., Irgens, G.A., Collier, W., Swiecki, Z., Ruis, A.R., & Shaffer, D.W. (2017). In search of conversational grain size: Modelling semantic structure using moving stanza windows. Journal of Learning Analytics, 4 (3), 123–139.

    Article  Google Scholar 

  • Sullivan, S., Warner-Hillard, C., Eagan, B., Thompson, R.J., 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.

    Article  Google Scholar 

  • Syed, M., & Nelson, S.C. (2015). Guidelines for establishing reliability when coding narrative data. Emerging Adulthood, 3(6), 375–387.

    Article  Google Scholar 

  • Teasley, S.D. (1995). The role of talk in children’s peer collaborations. Developmental Psychology, 31(2), 207.

    Article  Google Scholar 

  • Tsan, J., Vandenberg, J., Zakaria, Z., Wiggins, J.B., Webber, A.R., Bradbury, A., Lynch, C., Wiebe, E., & Boyer, K.E. (2020). A comparison of two pair programming configurations for upper elementary students. In Proceedings of the 51st ACM technical symposium on computer science education (pp. 346–352).

  • T’Sas, J. (2018). Learning outcomes of exploratory talk in collaborative activities. Unpublished PhD dissertation, university of Antwerp.

  • Tseng, H., Ku, H.Y., Wang, C.H., & Sun, L. (2009). Key factors in online collaboration and their relationship to teamwork satisfaction. Quarterly Review of Distance Education 10(2).

  • Van Eaton, G., Clark, D.B., & Smith, B.E. (2015). Patterns of physics reasoning in face-to-face and online forum collaboration around a digital game. International Journal of Education in Mathematics Science and Technology, 3(1), 1–13.

    Article  Google Scholar 

  • Warwick, P., Mercer, N., & Kershner, R. (2013). ‘wait, let’s just think about this’: Using the interactive whiteboard and talk rules to scaffold learning for co-regulation in collaborative science activities. Learning Culture and Social Interaction, 2(1), 42–51.

    Article  Google Scholar 

  • Wegerif, R. (2005). Reason and creativity in classroom dialogues. Language and Education, 19(3), 223–237.

    Article  Google Scholar 

  • Xun, G., & Land, S.M. (2004). A conceptual framework for scaffolding iii-structured problem-solving processes using question prompts and peer interactions. Educational Technology Research and Development, 52(2), 5–22.

    Article  Google Scholar 

  • Zakaria, Z., Boulden, D., Vandenberg, J., Tsan, J., Lynch, C., Wiebe, E., & Boyer, K. (2019). Collaborative talk across two pair-programming configurations. In A wide lens: Combining embodied, enactive extended, and embedded learning in collaborative settings, 13th international conference on computer supported collaborative learning (CSCL), (Vol. 1 p. 2019).

  • Zakaria, Z., Vandenberg, J., Tsan, J., Boulden, D.C., Lynch, C.F., Boyer, K.E., & Wiebe, E.N. (2021). Two-computer pair programming: Exploring a feedback intervention to improve collaborative talk in elementary students. Computer Science Education, pp. 1–28.

  • Zhang, S., Liu, Q., & Cai, Z. (2019). Exploring primary school teachers’ technological pedagogical content knowledge (tpack) in online collaborative discourse: An epistemic network analysis. British Journal of Educational Technology, 50 (6), 3437–3455.

    Article  Google Scholar 

Download references

Acknowledgements

This material is based upon work supported by the National Science Foundation under Grant No DRL-1721160. Additionally, this work was funded in part by the National Science Foundation (DRL-1661036, DRL-1713110), the Wisconsin Alumni Research Foundation, and the Office of the Vice Chancellor for Research and Graduate Education at the University of Wisconsin-Madison. The opinions, findings, and conclusions do not reflect the views of the funding agencies, cooperating institutions, or other individuals.

Author information

Authors and Affiliations

  1. North Carolina State University, Raleigh, NC, 27695, USA

    Jessica Vandenberg, Zarifa Zakaria, Collin Lynch & Eric Wiebe

  2. University of Chicago, Chicago, IL, 60637, USA

    Jennifer Tsan

  3. University of Wisconsin-Madison, Madison, WI, USA

    Anna Iwanski

  4. University of Florida, Gainesville, FL, 32611, USA

    Kristy Elizabeth Boyer

Authors
  1. Jessica Vandenberg
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zarifa Zakaria
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jennifer Tsan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Anna Iwanski
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Collin Lynch
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Kristy Elizabeth Boyer
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Eric Wiebe
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jessica Vandenberg.

Ethics declarations

Conflict of Interests

The authors declare that they have no conflict of interest.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Vandenberg, J., Zakaria, Z., Tsan, J. et al. Prompting collaborative and exploratory discourse: An epistemic network analysis study. Intern. J. Comput.-Support. Collab. Learn 16, 339–366 (2021). https://doi.org/10.1007/s11412-021-09349-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11412-021-09349-3

Keywords

Search

Navigation