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Critical Reviews with Quantitative Ethnography: Theory Use in Literature on Quantified Group Work in Educational Settings

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Advances in Quantitative Ethnography (icqe 2024)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 2278))

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Abstract

Mapping the evolving landscape of academic fields is crucial for understanding existing knowledge and identifying gaps for further research exploration. This paper explores the use of quantitative ethnography (QE) as an analysis strategy to bring together networked mappings of articles with qualitative interpretations of their content. QE enriches the common use of keyword or citation network models in literature reviews. Using the case of quantification of group work in educational settings, we employ Modular Analysis and Epistemic Network Analysis to find patterns in research methodologies, data types, and research aims, which we interpret iteratively through qualitative and quantitative tools. We identify three clusters of codes, which we identify as being focused on methodological advancement, assessments, and specific learning aims. One key difference we find setting these clusters apart is the articles’ use of learning theory, which is a difference that emerges from our QE-informed analysis and which elaborates on a trend noted in other reviews.

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References

  1. Alfredo, R.D., et al.: "That Student Should be a Lion Tamer!" StressViz: designing a stress analytics dashboard for teachers. In: LAK23: 13th International Learning Analytics and Knowledge Conference, pp. 57–67. LAK2023, Association for Computing Machinery, New York (2023). https://doi.org/10.1145/3576050.3576058

  2. Brewe, E., Bruun, J., Bearden, I.G.: Using module analysis for multiple choice responses: a new method applied to force concept inventory data. Phys. Rev. Phys. Educ. Res. 12(2), 020131 (2016). https://doi.org/10.1103/PhysRevPhysEducRes.12.020131

    Article  Google Scholar 

  3. Cao, D., Shao, S.: Towards complexity and dynamics: a bibliometric-qualitative review of network research in construction. Complexity 2020, 8812466 (2020). https://doi.org/10.1155/2020/8812466

    Article  Google Scholar 

  4. Chen, B., Teasley, S.D.: Learning analytics for understanding and supporting collaboration. In: Lang, C., Siemens, G., Wise, A.F. (eds.) The Handbook of Learning Analytics, 2nd edn., pp. 86–95. SOLAR (2022). https://doi.org/10.18608/hla22.009

    Chapter  Google Scholar 

  5. Chiu, M.M.: Effects of argumentation on group micro-creativity: statistical discourse analyses of algebra students’ collaborative problem solving. Contemp. Educ. Psychol. 33(3), 382–402 (2008). https://doi.org/10.1016/j.cedpsych.2008.05.001

    Article  Google Scholar 

  6. Chiu, M.M.: Effects of social metacognition on micro-creativity: Statistical discourse analyses of group problem solving. In: Proceedings of the 8th International Conference for the Learning Sciences. vol. 1, pp. 144–152 (Jun 2008)

    Google Scholar 

  7. Chiu, M.M.: Flowing toward correct contributions during group problem solving: a statistical discourse analysis. J. Learn. Sci. 17(3), 415–463 (2008). https://doi.org/10.1080/10508400802224830

    Article  Google Scholar 

  8. Chiu, M.M., Lehmann-Willenbrock, N.: Statistical discourse analysis: modeling sequences of individual actions during group interactions across time. Group Dyn. Theory Res. Pract. 20(3), 242–258 (2016). https://doi.org/10.1037/gdn0000048

    Article  Google Scholar 

  9. Echeverria, V., Martinez-Maldonado, R., Chiluiza, K., Buckingham Shum, S.: DBCollab: automated feedback for face-to-face group database design. In: Proceedings of the 25th International Conference on Computers in Education. Asia-Pacific Society for Computers in Education (2017)

    Google Scholar 

  10. Fernandez-Nieto, G.M., Martinez-Maldonado, R., Kitto, K., Buckingham Shum, S.: Modelling Spatial Behaviours in Clinical Team Simulations using Epistemic Network Analysis: Methodology and Teacher Evaluation. In: LAK21: 11th International Learning Analytics and Knowledge Conference. pp. 386–396. LAK21, Association for Computing Machinery, New York, NY, USA (Apr 2021), https://doi.org/10.1145/3448139.3448176

  11. Foti, N.J., Hughes, J.M., Rockmore, D.N.: Nonparametric sparsification of complex multiscale networks. PLoS One 6(2), e16431 (2011)

    Article  Google Scholar 

  12. Froehlich, D.E.: Mapping mixed methods approaches to social network analysis in learning and education. In: Mixed Methods Social Network Analysis, p. 12. Routledge (2019)

    Google Scholar 

  13. Giannakos, M., Cukurova, M.: The role of learning theory in multimodal learning analytics. Br. J. Educ. Technol. 54(5), 1246–1267 (2023). https://doi.org/10.1111/bjet.13320

    Article  Google Scholar 

  14. Grant, M.J., Booth, A.: A typology of reviews: an analysis of 14 review types and associated methodologies. Health Inf. Lib. J. 26(2), 91–108 (2009). https://doi.org/10.1111/j.1471-1842.2009.00848.x

    Article  Google Scholar 

  15. Hausberg, J.P., Liere-Netheler, K., Packmohr, S., Pakura, S., Vogelsang, K.: Research streams on digital transformation from a holistic business perspective: a systematic literature review and citation network analysis. J. Bus. Econ. 89(8–9), 931–963 (2019). https://doi.org/10.1007/s11573-019-00956-z

    Article  Google Scholar 

  16. Kaliisa, R., Rienties, B., Mørch, A.I., Kluge, A.: Social learning analytics in computer-supported collaborative learning environments: a systematic review of empirical studies. Comput. Educ. Open 3, 100073 (2022). https://doi.org/10.1016/j.caeo.2022.100073

    Article  Google Scholar 

  17. Lozano, S., Calzada-Infante, L., Adenso-Díaz, B., García, S.: Complex network analysis of keywords co-occurrence in the recent efficiency analysis literature. Scientometrics 120(2), 609–629 (2019). https://doi.org/10.1007/s11192-019-03132-w

    Article  Google Scholar 

  18. Mariegaard, S., Seidelin, L.D., Bruun, J.: Identification of positions in literature using thematic network analysis: the case of early childhood inquiry-based science education. Int. J. Res. Method Educ. 45(5), 518–534 (2022). https://doi.org/10.1080/1743727X.2022.2035351

    Article  Google Scholar 

  19. Misfeldt, M., et al.: Addressing Shared Reflective Persistence Through Three Different Lenses (In-press)

    Google Scholar 

  20. Molenaar, I., Chiu, M.M.: Dissecting sequences of regulation and cognition: statistical discourse analysis of primary school children’s collaborative learning. Metacogn. Learn. 9(2), 137–160 (2014). https://doi.org/10.1007/s11409-013-9105-8

    Article  Google Scholar 

  21. Morency, L.P., Oviatt, S., Scherer, S., Weibel, N., Worsley, M.: ICMI 2013 grand challenge workshop on multimodal learning analytics. In: Proceedings of the 15th ACM on International conference on multimodal interaction, pp. 373–378. ACM, Sydney Australia (2013). https://doi.org/10.1145/2522848.2534669

  22. Nguyen, A., Järvelä, S., Rosé, C., Järvenoja, H., Malmberg, J.: Examining socially shared regulation and shared physiological arousal events with multimodal learning analytics. Br. J. Educ. Technol. 54(1), 293–312 (2023). https://doi.org/10.1111/bjet.13280

    Article  Google Scholar 

  23. Nguyen, H., Lim, K.Y., Wu, L.L., Fischer, C., Warschauer, M.: “We’re looking good”: social exchange and regulation temporality in collaborative design. Learn. Instr. 74 (2021). https://doi.org/10.1016/j.learninstruc.2021.101443

  24. Oraee, M., Hosseini, M.R., Papadonikolaki, E., Palliyaguru, R., Arashpour, M.: Collaboration in BIM-based construction networks: a bibliometric-qualitative literature review. Int. J. Proj. Manag. 35(7), 1288–1301 (2017). https://doi.org/10.1016/j.ijproman.2017.07.001

    Article  Google Scholar 

  25. Ouyang, F., Dai, X., Chen, S.: Applying multimodal learning analytics to examine the immediate and delayed effects of instructor scaffoldings on small groups’ collaborative programming. International Journal of STEM Education 9(1), 45 (Dec 2022), https://doi.org/10.1186/s40594-022-00361-z

  26. Riquelme, F., Munoz, R., Mac Lean, R., Villarroel, R., Barcelos, T.S., de Albuquerque, V.H.C.: Using multimodal learning analytics to study collaboration on discussion groups. Univ. Access Inf. Soc. 18(3), 633–643 (2019). https://doi.org/10.1007/s10209-019-00683-w

  27. Schneider, B.: A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers. Journal of Visualized Experiments: JoVE (155) (Jan 2020), https://doi.org/10.3791/60670

  28. Schneider, B., Sung, G., Chng, E., Yang, S.: How can high-frequency sensors capture collaboration? A review of the empirical links between multimodal metrics and collaborative constructs. Sensors 21(24), 8185 (2021). https://doi.org/10.3390/s21248185

    Article  Google Scholar 

  29. Shaffer, D.W.: Quantitative Ethnography. Cathcart Press, Madison, Wisconsin (2017)

    Google Scholar 

  30. Shiau, W.L., Wang, X., Zheng, F.: What are the trend and core knowledge of information security? A citation and co-citation analysis. Inf. Manag. 60(3), 103774 (2023). https://doi.org/10.1016/j.im.2023.103774

    Article  Google Scholar 

  31. Spikol, D., Ruffaldi, E., Cukurova, M.: Using Multimodal Learning Analytics to Identify Aspects of Collaboration in Project-Based Learning (Jun 2017), https://doi.org/10.22318/cscl2017.37

  32. Sun, M., Wang, M., Wegerif, R., Peng, J.: How do students generate ideas together in scientific creativity tasks through computer-based mind mapping? Comput. Educ. 176, 104359 (2022). https://doi.org/10.1016/j.compedu.2021.104359

    Article  Google Scholar 

  33. Vujovic, M., Hernández-Leo, D., Tassani, S., Spikol, D.: Round or rectangular tables for collaborative problem solving? A multimodal learning analytics study. Br. J. Educ. Technol. 51(5), 1597–1614 (2020). https://doi.org/10.1111/bjet.12988

    Article  Google Scholar 

  34. Wise, A.F., Shaffer, D.W.: Why theory matters more than ever in the age of big data. J. Learn. Anal. 2(2), 5–13 (2015). https://doi.org/10.18608/jla.2015.22.2

    Article  Google Scholar 

  35. Yan, L., et al.: The role of indoor positioning analytics in assessment of simulation-based learning. Br. J. Educ. Technol. 54(1), 267–292 (2023). https://doi.org/10.1111/bjet.13262

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Acknowledgements

This study was funded by the Novo Nordisk Foundation (grant number NNF23OC0081371). The authors have no competing interests to declare that are relevant to the content of this article.

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Authors and Affiliations

  1. University of Copenhagen, Copenhagen, Denmark

    Liv Nøhr, Viktor Holm-Janas, Adrienne Traxler, Jesper Bruun, Daniel Spikol & Morten Misfeldt

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  1. Liv Nøhr
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  3. Adrienne Traxler
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  6. Morten Misfeldt
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Correspondence to Liv Nøhr .

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Editors and Affiliations

  1. University of Wisconsin, Madison, WI, USA

    Yoon Jeon Kim

  2. Monash University, Clayton, VIC, Australia

    Zachari Swiecki

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Nøhr, L., Holm-Janas, V., Traxler, A., Bruun, J., Spikol, D., Misfeldt, M. (2024). Critical Reviews with Quantitative Ethnography: Theory Use in Literature on Quantified Group Work in Educational Settings. In: Kim, Y.J., Swiecki, Z. (eds) Advances in Quantitative Ethnography. icqe 2024. Communications in Computer and Information Science, vol 2278. Springer, Cham. https://doi.org/10.1007/978-3-031-76335-9_6

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  • DOI: https://doi.org/10.1007/978-3-031-76335-9_6

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