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Extending the Utility of the Views of Nature of Science Assessment through Epistemic Network Analysis

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Abstract

An understanding of how science is enacted and how scientific knowledge is generated, or the nature of science (NOS), is a major goal of science education. NOS views have almost exclusively been assessed using the Views of Nature of Science (VNOS) suite of instruments, which consists of open-ended questions. The purpose of this study was to investigate the utility of performing an Epistemic Network Analysis (ENA) from VNOS-B responses, using the group as the unit of analysis. Traditional scoring of the VNOS responses demonstrated that overall, participants shifted from emerging to more sophisticated views across all elements. An ENA provided a quick visualization of how participants connected NOS ideas. With regard to accuracy of participants’ NOS understandings as a group, findings from traditional VNOS analysis and ENA converged on two main points, improvement of overall quality of knowledge and the identification of missing elements of NOS from responses. Some changes in participants’ NOS understanding were identifiable in results from only the ENA. For example, prior to instruction, ENA showed three naive ideas about empiricism. After instruction, no naive statements remained in the responses about the empirical nature of science. ENA extends the traditional VNOS analysis by enabling the pinpointing of particular ideas that are meaningful to the group, indicating clusters of ideas that are related, and illustrating the way informed, transitional and naïve ideas intermingle.

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Correspondence to Erin E. Peters-Burton.

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Appendix

Appendix

Table 6 Pre-course statements (45) for network model from VNOS-B administration with researcher rating and main NOS element
Table 7 Post-course statements (41) for network model from VNOS-B administration with researcher rating and main NOS element

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Peters-Burton, E.E., Parrish, J.C. & Mulvey, B.K. Extending the Utility of the Views of Nature of Science Assessment through Epistemic Network Analysis. Sci & Educ 28, 1027–1053 (2019). https://doi.org/10.1007/s11191-019-00081-x

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