Implementing Computer Science Literature
Implementing Computer Science Literature Review What questions need to be answered?
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What makes organizational change in schools effective?
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There is a long history of technology not leading to organizational change in schools.
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Cuban, L. (2009). Oversold and underused. Harvard University Press.
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Throughout much of the 20th century, change was largely driven by superintendents beholden to the values of business.
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Callahan, R. E. (1964). Education and the cult of efficiency. University of Chicago Press.
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Teacher practices have a big impact on student learning.
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Boaler, J. (2002). Experiencing school mathematics: Traditional and reform approaches to teaching and their impact on student learning. Routledge.
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… endless others…
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Past computer science educational offerings have been characterized by structural inequalities, belief systems, inequality, and segregation.
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Margolis, J., & Fisher, A. (2003). Unlocking the clubhouse: Women in computing. MIT press.
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Margolis, J., Estrella, R., Goode, J., Holme, J. J., & Nao, K. (2010). Stuck in the shallow end: Education, race, and computing. MIT Press.
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Margolis, J., Goode, J., & Chapman, G. (2015). An equity lens for scaling: a critical juncture for exploring computer science. ACM Inroads, 6(3), 58-66.
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What’s necessary for an effective computer science learning environment?
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There is widespread disagreement about the nature of computational thinking, how it should be taught, and how it should be assessed.
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National Research Council. (2010). Report of a workshop on the scope and nature of computational thinking. National Academies Press.
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National Research Council. (2011). Report of a workshop on the pedagogical aspects of computational thinking. National Academies Press.
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Grover, S., & Pea, R. (2013). Computational thinking in K–12: A review of the state of the field. Educational Researcher, 42(1), 38-43.
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Proctor, C., & Blikstein, P. (2018). How broad is computational thinking? A longitudinal study of practices shaping computer science learning. Full paper to be presented at International Conference of the Learning Sciences (ICLS) 2018, London, UK. http://chrisproctor.net/media/publications/proctor_2018_icls.pdf
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Blikstein, P. (2018). Pre-College Computer Science Education: A Survey of the Field. Mountain View, CA: Google LLC. Retrieved from https://goo.gl/gmS1Vm.
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There are several models of computer science designed with equity and inclusion as a primary goal.
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Goode, J., Chapman, G., Margolis, J., Landa, J., Ullah, T., Watkins, D., & Stephenson, C. (2011). Exploring computer science. ACM Transactions on Computing Education, 11(2), 1-16.
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Kafai, Y. B., & Burke, Q. (2013, March). The social turn in K-12 programming: moving from computational thinking to computational participation. In Proceeding of the 44th ACM technical symposium on computer science education (pp. 603-608). ACM.
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K-12 Computer Science Framework Steering Committee. (2016). K-12 computer science framework.
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How can computer science pedagogy be cultivated in a community of educators without such a background?
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Computer science can be seen as an interdisciplinary practice or as part of a literacy approach.
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Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., & Wilensky, U. (2016). Defining computational thinking for mathematics and science classrooms. Journal of Science Education and Technology, 25(1), 127-147.
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Proctor, C. (2018) Unfold.studio: Developing critical literacies of text and code. Manuscript in preparation. http://chrisproctor.net/media/publications/proctor_2018_qp.pdf
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Communities of educators can prioritize computational thinking in professional development.
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Proctor, C. (2018) Ten micro-credentials to support teaching computational thinking across the K-12 curriculum. Unpublished manuscript. http://chrisproctor.net/media/publications/ct_microcredentials.pdf (These were published here: http://digitalpromise.org/2017/12/06/advancing-computational-thinking-across-k-12-education/; there’s ongoing research on their effectiveness.)