Abstract
This study discusses the temporal analysis method with data on collected on a real-time scale to investigate learning as knowledge-creation. During collaborative learning, collaboratively building ideas is important for learners. Thus, collaborative learning strategies must consider learners’ discourses temporally. Therefore, this study used data collected in real-time and two analysis methods: the combination of socio-semantic network analysis (SSNA) and in-depth dialogical discourse analysis. Especially, the authors used the SSNA combined with the moving stanza window method and the network lifetime in this study. The goal of this study was to examine the possibility of analyzing data with timestamp information. For this goal, the authors conducted a comparative study by analyzing the same dataset using the following steps. First, the authors visualized the data gathered from collaborative learning. Second, the authors conducted a comparison between the analyzed results of the ordered data and of data with timestamp information. Third, the authors detected the pivotal points from the results of analyzing data with timestamp information using the SSNA combined with the moving stanza window method and the network lifetime, and the discourse data was analyzed in great depth. The first finding of this study is that the proposed analysis method can effectively represent the process of ideas improvement. The second finding is that analysis using timestamp information is effective for assessing the similarities and differences between each group. This study suggests the effectiveness of temporal analysis and analyzing data gathered in real-time.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Scardamalia, M.: Collective cognitive responsibility for the advancement of knowledge. In: Smith, B. (ed.) Liberal Education in a Knowledge Society, pp. 67–98. Open Court, Chicago (2002)
Paavola, S., Lipponen, L., Hakkarainen, K.: Models of innovative knowledge communities and three metaphors of learning. Rev. Edu. Res. 74, 557–576 (2004)
Hakkarainen, K., Paavola, S., Kangas, K., Seitamaa-Hakkarainen, P.: Socio-cultural perspectives on collaborative learning: toward knowledge creation. In: Hmelo-Silver, C., Chinn, C.A., Chan, C., O’donnell, A. (eds.) The International Handbook of Collaborative Learning, pp. 57–73. Routledge, New York (2013)
Scardamalia, M., Bereiter, C.: Knowledge building and knowledge creation: theory, pedagogy, and technology. In: Sawyer, K. (ed.) The Cambridge Handbook of the Learning Sciences, 2nd edn., pp. 397–417. Cambridge University Press, New York (2014)
Csanadi, A., Eagan, B., Kollar, I., Shaffer, D.W., Fischer, F.: When coding-and-counting is not enough: using epistemic network analysis (ENA) to analyze verbal data in CSCL research. Int. J. Comput.-Support. Collab. Learn. 13, 419–438 (2018)
Ohsaki, A., Oshima, J.: A socio-semantic network analysis of discourse using the network lifetime and the moving stanza window method. In: Eagan, B., Misfeldt, M., Siebert-Evenstone, A. (eds.) ICQE 2019. CCIS, vol. 1112, pp. 326–333. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-33232-7_29
Oshima, J., Oshima, R., Fujita, W.: A mixed-methods approach to analyze shared epistemic agency in jigsaw instruction at multiple scales of temporality. J. Learn. Anl. 5, 10–24 (2018)
Zhang, J., Scardamalia, M., Reeve, R., Messina, R.: Designs for collective cognitive responsibility in knowledge-building communities. J. Learn. Sci. 18, 7–44 (2009)
Hong, H.Y., Chen, F.C., Chai, C.S., Chan, W.C.: Teacher-education students’ views about knowledge building theory and practice. Instr. Sci. 39, 467–482 (2011)
Chen, B., Scardamalia, M., Bereiter, C.: Advancing knowledge-building discourse through judgments of promising ideas. Int. J. Comput. Support. Collab. Learn. 10, 345–366 (2015)
Oshima, J., Oshima, R., Matsuzawa, Y.: Knowledge building discourse explorer: a social network analysis application for knowledge building discourse. Edu. Tech. Res. Dev. 60, 903–921 (2012)
Siebert-Evenstone, A.L., Irgens, G.A., Collier, W., Swiecki, Z., Ruis, A.R., Shaffer, D.W.: In search of conversational grain size: modeling semantic structure using moving stanza windows. J. Learn. Anl. 4, 123–139 (2017)
Shaffer, D.W.: Quantitative Ethnography. Cathcart, Madison (2017)
Barabási, A.: Network Science. Cambridge University Press, Cambridge (2016)
Morris, M., Kretzschmar, M.: Concurrent partnerships and transmission dynamics in networks. Soc. Netw. 17, 299–318 (1995)
Masuda, N., Holme, P.: Predicting and controlling infectious diseases epidemics using temporal networks. F1000 Prime Rep. 5,6 (2013)
Holme, P., Saramäki, J.: Temporal networks. Phys. Rep. 519, 97–125 (2012)
Dyke, G., Kumar, R., Ai, H., Rose, C.: Challenging assumptions: using sliding window visualizations to reveal time-based irregularities in CSCL processes. In: the Future of Learning: Proceedings of the 10th International Conference of the Learning Sciences (ICLS 2012), vol. 1, pp. 363–370, International Society of the Learning Sciences, Sydney (2012)
Oshima, J., Ohsaki, A., Yamada, Y., Oshima, R.: Collective knowledge advancement and conceptual understanding of complex scientific concepts in the jigsaw instruction. In: Making a Difference: Prioritizing Equity and Access in CSCL, 12th International Conference on Computer Supported Collaborative Learning (CSCL) 2017, vol. 1, pp. 57–64. International Society of the Learning Sciences, Philadelphia (2017)
Miyake, N., Kirschner, P.A.: The social and interactive dimensions of collaborative learning. In: Sawyer, K. (ed.) The Cambridge Handbook of the Learning Sciences (Second edition), pp. 418–438. Cambridge University Press, New York (2014)
Barabási, A.: The origin of bursts and heavy tails in human dynamics. Nature 435, 207–211 (2005)
Acknowledgments
This work was supported by JSPS KAKENHI Grant Numbers JP16H0187, JP18K13238, and JP19H01715.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Ohsaki, A., Oshima, J. (2021). Socio-semantic Network Analysis of Knowledge-Creation Discourse on a Real-Time Scale. In: Ruis, A.R., Lee, S.B. (eds) Advances in Quantitative Ethnography. ICQE 2021. Communications in Computer and Information Science, vol 1312. Springer, Cham. https://doi.org/10.1007/978-3-030-67788-6_12
Download citation
DOI: https://doi.org/10.1007/978-3-030-67788-6_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-67787-9
Online ISBN: 978-3-030-67788-6
eBook Packages: Computer ScienceComputer Science (R0)