New Materialist Network Approaches in Science Education: A Method to Construct Network Data from Video
Main Article Content
Abstract
Lately, new materialism has been proposed as a theoretical framework to better understand material-dialogic relationships in learning, and concurrently network analysis has emerged as a method in science education research. This paper explores how to include materiality in network analysis and reports the development of a method to construct network data from video. The approaches, 1) information flow, 2) material semantic and 3) material engagement, were identified based on the literature on network analysis and new materialism in science education. The method was applied and further improved with a video segment from an upper secondary school physics lesson. The example networks from the video segment show that network analysis is a potential research method within the materialist framework and that the method allows studies into the material and dialogic relationships that emerge when students are engaged in investigations in school.
Article Details
FLR adopts the Attribution-NonCommercial-NoDerivs Creative Common License (BY-NC-ND). That is, Copyright for articles published in this journal is retained by the authors with, however, first publication rights granted to the journal. By virtue of their appearance in this open access journal, articles are free to use, with proper attribution, in educational and other non-commercial settings.
References
Ash, D. (2007). Using video data to capture discontinuous science meaning making in non-school settings. In Video Research in the Learning Sciences (pp. 221–240). Routledge.
https://doi.org/10.4324/9780203877258
Barabási, A.-L. (2011). The network takeover. Nature Physics, 8 (1), 14–16.
https://doi.org/10.1038/nphys2188
Barrat, A., Barthélemy, M., Pastor-Satorras, R., & Vespignani, A. (2004). The architecture of complex weighted networks. Proceedings of the National Academy of Sciences of the United States of America, 101(11), 3747–3752. https://doi.org/10.1073/pnas.0400087101
Bennett, J. (2010). Vibrant Matter: A Political Ecology of Things. Durham: Duke University Press. https://doi.org/10.2307/j.ctv111jh6w
Bokhove, C. (2018). Exploring classroom interaction with dynamic social network analysis. International Journal of Research and Method in Education, 41(1), 17–37.
https://doi.org/10.1080/1743727X.2016.1192116
Borgatti, S. P. (2005). Centrality and network flow. Social Networks, 27 (1), 55–71.
https://doi.org/10.1016/j.socnet.2004.11.008
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. https://doi.org/10.1007/s10956-019-09786-8
Bruun, J., Lindahl, M., & Linder, C. (2019). Network analysis and qualitative discourse analysis of a classroom group discussion. International Journal of Research and Method in Education, 42(3), 317–339. https://doi.org/10.1080/1743727X.2018.1496414
Caballero, D., Pikkarainen, T., Araya, R., Viiri, J., & ... (2020). Conceptual network of teachers’ talk: Automatic analysis and quantitative measures. FMSERA Journal, 3(1), 18–31. Retrieved from https://journal.fi/fmsera/article/view/79630
Cook, V., Warwick, P., Vrikki, M., Major, L., & Wegerif, R. (2019). Developing material-dialogic space in geography learning and teaching: Combining a dialogic pedagogy with the use of a microblogging tool. Thinking Skills and Creativity, 31, 217-231. https://doi.org/10.1016/j.tsc.2018.12.005
Derry, S. J., Pea, R. D., Barron, B., Engle, R. A., Erickson, F., Goldman, R., Hall, R., Koschmann, T., Lemke, J. L., Sherin, M. G., & Sherin, B. L. (2010). Conducting video research in the learning sciences: guidance on selection, analysis, technology, and ethics. Journal of the Learning Sciences, 19 (1), 3–53. https://doi.org/10.1080/10508400903452884
Dou, R., & Zwolak, J. P. (2019). Practitioner’s guide to social network analysis: Examining physics anxiety in an active-learning setting. Physical Review Physics Education Research, 15 (2), 20105. https://doi.org/10.1103/PhysRevPhysEducRes.15.020105
ELAN (Version 5.4) [Computer software.] (2019). Nijmegen: Max Planck Institute for Psycholinguistics, the Language Archive. Retrieved from https://archive.mpi.nl/tla/elan
Erickson, F. (2012). Definition and analysis of data from videotape: Some research procedures and their
rationales. In Green, J.L., Green, J., Camilli, G., Camilli, G., Elmore, P.B., & Elmore, P. (Eds.),
Handbook of Complementary Methods in Education Research, (3rd ed.). Routledge. 177–191.
https://doi.org/10.4324/9780203874769
Fenwick, T. (2011). Reading educational reform with actor network theory: Fluid spaces, otherings, and ambivalences. Educational Philosophy and Theory, 43(SUPPL. 1), 114–134.
https://doi.org/10.1111/j.1469-5812.2009.00609.x
Fenwick, T., & Edwards, R. (2010). Actor–Network Theory in Education.
https://doi.org/10.4324/9780203849088
Fruchterman, T. M., & Reingold, E. M. (1991). Graph drawing by force-directed placement. Software: Practice and Experience, 21 (11), 1129–1164. https://doi.org/10.1002/spe.4380211102
Gamble, C. N., Hanan, J. S., & Nail, T. (2019). What is new materialism? Angelaki: Journal of the Theoretical Humanities, 24 (6), 111–134. https://doi.org/10.1080/0969725X.2019.1684704
González-Howard, M. (2019). Exploring the utility of social network analysis for visualizing interactions during argumentation discussions. Science Education, 103 (3), 503–528.
https://doi.org/10.1002/sce.21505
Heritage, J. (1984). Garfinkel and Ethnomethodology. Cambridge: Polity Press.
Hetherington, L., Hardman, M., Noakes, J., & Wegerif, R. (2018). Making the case for a material-dialogic approach to science education. Studies in Science Education, 54 (2), 141–176.
https://doi.org/10.1080/03057267.2019.1598036
Hetherington, L., & Wegerif, R. (2018). Developing a material-dialogic approach to pedagogy to guide science teacher education. Journal of Education for Teaching: JET, 44 (1), 27–43.
https://doi.org/10.1080/02607476.2018.1422611
Jordan, B., & Henderson, A. (1995). Interaction Analysis: foundations and practice. Journal of the Learning Sciences, 4(1), 39–103. https://doi.org/10.1207/s15327809jls0401_2
Juuti, K., Lavonen, J., Salonen, V., Salmela-Aro, K., Schneider, B., & Krajcik, J. (2021). A teacher– researcher partnership for professional learning: co-designing project-based learning units to increase student engagement in science classes. Journal of Science Teacher Education, 32:6, 625-641. https://doi.org/10.1080/1046560X.2021.1872207
Knoke, D., & Yang, S. (2008). Social Network Analysis. Los Angeles, CA; London: SAGE Publications, Inc. https://dx.doi.org/10.4135/9781412985864
Koponen, I. T., & Mäntylä, T. (2020). Editorial: Networks applied in science education research. Education Sciences, 10 (5), 142. https://doi.org/10.3390/educsci10050142
Koponen, I. T., & Nousiainen, M. (2019). Pre-service teachers’ knowledge of relational structure of physics concepts: finding key concepts of electricity and magnetism. Education Sciences, 9(1), [18]. https://doi.org/10.3390/educsci9010018
Krajcik, J. S., & Shin, N. (2014). Project-based learning. In The Cambridge Handbook of the Learning Sciences (pp. 275–297). Cambridge: Cambridge University Press.
https://doi.org/10.1017/CBO9781139519526
Latour, B. (2005). Reassembling the Social: An Introduction to Actor-Network-Theory. Oxford; New York: Oxford University Press. https://doi.org/2027/heb32135.0001.001
Latour, B., & Woolgar, S. (1986). Laboratory Life: The Construction of Scientific Facts. Princeton: Princeton University Press. https://doi.org/10.2307/j.ctt32bbxc
Martínez, A., Dimitriadis, Y., Rubia, B., Gómez, E., & De la Fuente, P. (2003). Combining qualitative evaluation and social network analysis for the study of classroom social interactions. Computers and Education, 41 (4), 353–368. https://doi.org/10.1016/j.compedu.2003.06.001
McDonnell, M.D., Yaveroglu, Ö. N., Schmerl, B. A., Iannella, N. & Ward, L. M. (2014).Motif-role- fingerprints: The building-blocks of motifs, clustering-coefficients and transitivities in directed networks. PLoS ONE, 9 (12). https://doi.org/10.1371/journal.pone.0114503
Milo, R., Shen-Orr, S., Itzkovitz, S., & Kashtan, N. (2002). Network motif: simple building blocks of complex networks. Science, 298 (5594), 824–827. https://doi.org/10.1126/science.298.5594.824
Milne, C. (2019). The materiality of scientific instruments and why it might matter to science education. In C. Milne & K. Scantlebury (eds.), Material Practice and Materiality: Too Long Ignored in Science Education (pp. 9–23). Cham, Switzerland: Springer. https://doi.org/10.1007/978-3-030-01974-7_2
Milne, & Scantlebury, K. (2019). Material Practice and Materiality: Too Long Ignored in Science Education. Cham, Switzerland: Springer. https://doi.org/10.1007/978-3-030-01974-7
Moore, R. J. (2015). Automated transcription and conversation analysis. Research on Language and Social Interaction, 48(3), 253–270. https://doi.org/10.1080/08351813.2015.1058600
Nespor, J. (2002). Networks and contexts of freedom. Journal of Educational Change, 3(Ccl), 365–382.
https://doi.org/10.1023/A:1021281913741
Oshima, J., Oshima, R., & Saruwatari, S. (2020). Analysis of students’ ideas and conceptual artifacts in knowledge-building discourse. British Journal of Educational Technology, 51(4), 1308–1321. https://doi.org/10.1111/bjet.12961
Peixoto, T. P. (2014). The graph-tool python library. figshare.
https://doi.org/10.6084/m9.figshare.1164194
Schneider, B., Krajcik, J., Lavonen, J., & Salmela-Aro, K. (2020). Learning Science: The Value of Crafting Engagement in Science Environments. Yale University Press.
https://doi.org/10.12987/9780300252736
Shaffer, D. W., Hatfield, D., Svarovsky, G. N., Nash, P., Nulty, A., Bagley, E., … Mislevy, R. (2009).
Epistemic network analysis: a prototype for 21st-century assessment of learning. International
Journal of Learning and Media, 1(2), 33–53. https://doi.org/10.1162/ijlm.2009.0013
Turkkila, M., & Lommi, H. (2020). Student participation in online content-related discussion and its relation to students’ background knowledge. Education Sciences, 10 (4), 106.
https://doi.org/10.3390/educsci10040106
Vicsek, L., Király, G., & Kónya, H. (2016). Networks in the social sciences. Corvinus Journal of Sociology and Social Policy, 7(2). https://doi.org/10.14267/CJSSP.2016.02.04
Wagner, S., Kok, K., & Priemer, B. (2020). Measuring characteristics of explanations with element maps.
Education Sciences, 10 (2). https://doi.org/10.3390/educsci10020036
Wasserman, S. (1994). Social Network Analysis: Methods and Applications. Cambridge: Cambridge University Press. https://doi.org/10.1017/CBO9780511815478
Yun, E., & Park, Y. (2018). Extraction of scientific semantic networks from science textbooks and comparison with science teachers’ spoken language by text network analysis. International Journal of Science Education, 40 (17), 2118–2136. https://doi.org/10.1080/09500693.2018.1521536
Zweig, K. A. (2016). Network Analysis Literacy: A Practical Approach to the Analysis of Networks. Vienna: Springer. https://doi.org/10.1007/978-3-7091-0741-6