This paper investigates an in-service teacher and her student’s abilities to utilize, implement, and enact a participatory agent-based modeling program, developed as part of the group-based cloud computing (GbCC) for STEM Education Project funded by the National Science Foundation. In this first cycle of design-based implementation research with an in-service teacher and her 300 students, we examine student participatory learning and teacher experience. By implementing models with teachers, we intend to 1) improve iteratively the GbCC learning technologies and 2) develop more informed and aligned pedagogies for teaching in socially mediated and generative learning environments.
References
[1]
Collins, A. (1990). Toward a Design Science of Education. Technical Report No. 1. New York, NY: Center for Technology in Education.
[2]
Fishman, B. J., Penuel, W. R., Allen, A.-R., Cheng, B. H., & Sabelli, N. (2013). Design-Based Implementation Research: An Emerging Model for Transforming the Relationship of Research and Practice. Yearbook of the National Society for the Study of Education, 112, 136-156.
[3]
How Wolves Change Rivers (2014).
https://sustainablehuman.tv/remix/how-wolves-change-rivers
[4]
Next Generation Science Standards Lead States (2013). Next Generation Science Standards: For States, by States. Washington DC: The National Academies Press.
[5]
Petrosino, A. J., & Stroup, W. M. (2017). Group-Based Cloud Computing for STEM Education. Columbus: Poster at the Annual Convention of the American Society of Engineering Education.
https://www.asee.org/public/conferences/78/papers/19018/view
[6]
Philip, T., & Garcia, A. (2013). The Importance of Still Teaching the iGeneration: New Technologies and the Centrality of Pedagogy. Harvard Educational Review, 83, 300-319. https://doi.org/10.17763/haer.83.2.w221368g1554u158
[7]
Ripple, W. J., & Beschata, R. L. (2012). Trophic Cascades in Yellowstone: The First 15 Years after Wolf Reintroduction. Biological Conservation, 145, 205-213.
https://doi.org/10.1016/j.biocon.2011.11.005
[8]
Schwarz, C. V., Reiser, B. J., Davis, E. A., Kenyon, L., Achér, A., Fortus, D., Krajcik, J. et al. (2009). Developing a Learning Progression for Scientific Modeling: Making Scientific Modeling Accessible and Meaningful for Learners. Journal of Research in Science Teaching, 46, 632-654. https://doi.org/10.1002/tea.20311
[9]
Stroup, W. M., Ares, N., & Hurford, A. C. (2004). A Taxonomy of Generative Activity Design Supported by Next-Generation Classroom Networks. Proceedings of the 28th Annual Conference of Psychology in Mathematics Education-North America, Ontario, 837-846.
[10]
Stroup, W. M., Ares, N., Lesh, R., & Hurford, A. (2007). Diversity by Design: Generativity in Next-Generation Classroom Networks. In R. Lesh, E. Hamilton, & J. J. Kaput (Eds.), Models and Modeling as Foundations for the Future in Mathematics Education (pp. 367-393). Mahwah, NJ: Erlbaum.
[11]
Wells, G. (1993). Reevaluating the IRF Sequence: A Proposal for the Articulation of Theories of Activity and Discourse for the Analysis of Teaching and Learning in the Classroom. Linguistics and Education, 5, 1-37.
https://doi.org/10.1016/S0898-5898(05)80001-4
[12]
Wilensky, U. (1997). NetLogo Wolf Sheep Predation Model. Evanston, IL: Northwestern University, Center for Connected Learning and Computer-Based Modeling.
http://ccl.northwestern.edu/netlogo/models/WolfSheepPredation
[13]
Wilensky, U., & Reisman, K. (2006). Thinking Like a Wolf, a Sheep, or a Firefly: Learning Biology through Constructing and Testing Computational Theories—An Embodied Modeling Approach. Cognition and Instruction, 24, 171-209.
https://doi.org/10.1207/s1532690xci2402_1
