Abstract
The Next Generation Science Standards propose an integrated and holistic view of science education that teaches science through three-dimensional learning. In this vision of science, content and practices are interconnected and inseparable. While the NGSS has influenced K-12 education standards in 40 states, there has not been a systematic analysis of the standards themselves. In this study, we investigate three-dimensional learning in order to identify new insights into underlying relationships between science concepts as well as make comparisons between different science disciplines. We used Epistemic Network Analysis to measure and models the structure of connections among crosscutting concepts and practices within and across disciplines. Results show systematic differences between how Physical and Life Sciences use and describe cause and effect relationships in which Physical Sciences predominantly focuses on the generation of causal relationships while Life Sciences focuses on the explanation of causal relationships.
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Acknowledgements
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.
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Siebert-Evenstone, A., Shaffer, D.W. (2019). Cause and Because: Using Epistemic Network Analysis to Model Causality in the Next Generation Science Standards. In: Eagan, B., Misfeldt, M., Siebert-Evenstone, A. (eds) Advances in Quantitative Ethnography. ICQE 2019. Communications in Computer and Information Science, vol 1112. Springer, Cham. https://doi.org/10.1007/978-3-030-33232-7_19
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DOI: https://doi.org/10.1007/978-3-030-33232-7_19
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