Special Interest Groups (SIGs) provide a forum within AERA for the involvement of individuals drawn together by a common interest in a field of study, teaching, or research when the existing divisional structure may not directly facilitate such activity. The Association provides SIGs program time at the Annual Meeting, publicity, scheduling, staff support, viability, and the prestige of AERA affiliation.
We are pleased to offer five webinars intended to familiarize you with the concept of a Networked Improvement Community, and each of the four important components and elements of a successful NIC. An introductory 30-minute webinar will feature one or two experts from out team providing key background information about the focal challenges of building a NIC. A facilitated discussion forum will continue for two weeks after the video is posted to this site. At the end of the two weeks, another live webinar with the same expert will be featured. This follow-up webinar will focus on the topics that have arisen through the online forum, as well as questions that are asked live during the webinar.
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Krumm, A., Penuel, W. R., Pazera, C., & Landel, C. (2020). Measuring Equitable Science Instruction at Scale. The Interdisciplinarity of the Learning Sciences, 4, 2461–2468. https://repository.isls.org//handle/1/6607
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Bowers, A. J., & Krumm, A. E. (2021). Supporting the Initial Work of Evidence-Based Improvement Cycles Through a Data-Intensive Partnership. Information and Learning Sciences, 122(9/10), 629–650. https://doi.org/10.1108/ILS-09-2020-0212
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Barnes, G. D., Acosta, J., Kurlander, J. E., & Sales, A. E. (2021). Using Health Systems Engineering Approaches to Prepare for Tailoring of Implementation Interventions. Journal of General Internal Medicine, 36(1), 178–185. https://doi.org/10.1007/s11606-020-06121-5
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Baker, R. S. (2016). Stupid Tutoring Systems, Intelligent Humans. International Journal of Artificial Intelligence in Education, 26(2), 600–614. https://doi.org/10.1007/s40593-016-0105-0
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Fischer, C., Pardos, Z. A., Baker, R. S., Williams, J. J., Smyth, P., Yu, R., Slater, S., Baker, R., & Warschauer, M. (2020). Mining Big Data in Education: Affordances and Challenges. Review of Research in Education, 44(1), 130–160. https://doi.org/10.3102/0091732X20903304
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George, B. C., Bohnen, J. D., Williams, R. G., Meyerson, S. L., Schuller, M. C., Clark, M. J., Meier, A. H., Torbeck, L., Mandell, S. P., Mullen, J. T., Smink, D. S., Scully, R. E., Chipman, J. G., Auyang, E. D., Terhune, K. P., Wise, P. E., Choi, J. N., Foley, E. F., Dimick, J. B., … Collaborative (PLSC), on behalf of the P. L. and S. (2017). Readiness of US General Surgery Residents for Independent Practice. Annals of Surgery, 266(4), 582–594. https://doi.org/10.1097/SLA.0000000000002414
Due to the increasing amount of available published evidence and the continual need to apply and update evidence in practice, we propose a shift in the way evidence generated by learning health systems can be integrated into more traditional evidence reviews. This paper discusses two main mechanisms to close the evidence-to-practice gap: (1) integrating Learning Health System (LHS) results with existing systematic review evidence and (2) providing this combined evidence in a standardized, computable data format. We believe these efforts will better inform practice, thereby improving individual and population health.
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Koedinger, K. R., Baker, R. S. J. d, Cunningham, K., Skogsholm, A., Leber, B., & Stamper, and J. (2010). A Data Repository for the EDM Community: The PSLC DataShop. In C. Romero, S. Ventura, M. Pechenizkiy, & R. S. J. d. Baker (Eds.), Handbook of Educational Data Mining (pp. 43–56). CRC Press.
