Items

• INCLUDES Center Webinar Series

  INCLUDES Center. (n.d.). Webinars. https://includescenter.org/webinars/
  

• Validity in Action: Lessons From Studies of Data Use

  Moss, Pamela A. (2013). Validity in Action: Lessons From Studies of Data Use. Journal of Educational Measurement, 50(1), 91-98.
  

• Using Student-Assessment Results to Improve Instruction: Lessons From a Workshop

  Murnane, R. J., Sharkey, N. S., & Boudett, K. P. (2005). Using Student-Assessment Results to Improve Instruction: Lessons From a Workshop. Journal of Education for Students Placed at Risk (JESPAR), 10(3), 269–280. https://doi.org/10.1207/s15327671espr1003_3
  

• Shifting the Focus of Validity for Test Use

  Moss, P. A. (2016). Shifting the Focus of Validity for Test Use. Assessment in Education: Principles, Policy & Practice, 23(2), 236–251. https://doi.org/10.1080/0969594X.2015.1072085
  

• Explicating Validity

  Kane, M. T. (2016). Explicating Validity. Assessment in Education: Principles, Policy & Practice, 23(2), 198–211. https://doi.org/10.1080/0969594X.2015.1060192
  

• When Should I Use a Measure to Support Instructional Improvement at Scale? The Importance of Considering Both Intended and Actual Use in Validity Arguments

  Ing, M., Chinen, S., Jackson, K., & Smith, T. M. (2021). When Should I Use a Measure to Support Instructional Improvement at Scale? The Importance of Considering Both Intended and Actual Use in Validity Arguments. Educational Measurement: Issues and Practice, 40(1), 92–100. https://doi.org/10.1111/emip.12393
  

• Continuous Improvement in Practice

  Hough, H. J., Willis, J., Grunow, A., Krausen, K., Kwon, S., Mulfinger, L. S., & Park, S. (2017). Continuous Improvement in Practice (Policy Analysis for California Education). https://edpolicyinca.org/publications/continuous-improvement-practice
  

• Expanding Views of Interpretation/Use Arguments

  Haertel, E. (2013). Expanding Views of Interpretation/Use Arguments. Measurement: Interdisciplinary Research and Perspectives, 11(1–2), 68–70. https://doi.org/10.1080/15366367.2013.790729
  

• Research on Data Use: A Framework and Analysis

  Coburn, C. E., & Turner, E. O. (2011). Research on Data Use: A Framework and Analysis. Measurement: Interdisciplinary Research and Perspectives, 9(4), 173–206. https://doi.org/10.1080/15366367.2011.626729
  

• What’s the Evidence on Districts’ Use of Evidence?

  Coburn, C. E., Honig, M. I., & Stein, M. K. (2009). What’s the Evidence on Districts’ Use of Evidence? In J. D. Bransford, D. J. Stipek, N. J. Vye, L. M. Gomez, & D. Lam (Eds.), The Role of Research in Educational Improvement (pp. 67–86). Harvard Education Press.
  

• Learning From Early Adopters in the New Accountability Era: Insights From California’s CORE Waiver Districts

  Marsh, J. A., Bush-Mecenas, S., & Hough, H. (2017). Learning From Early Adopters in the New Accountability Era: Insights From California’s CORE Waiver Districts. Educational Administration Quarterly, 53(3), 327–364. https://doi.org/10.1177/0013161X16688064
  

• Improvement Analytics: Learning from Data to Drive Improvement

  Krumm, A. E., & Grunow, A. (2017). Improvement Analytics: Learning from Data to Drive Improvement [Webinar]. https://includescenter.org/webinars/improvement-analytics-learning-from-data-to-drive-improvement/
  

• INCLUDES Center

  INCLUDES Center. (n.d.). https://includescenter.org/
  

• Making Sense of Sensemaking: Understanding How K–12 Teachers and Coaches React to Visual Analytics

  Campos, F. C., Ahn, J., DiGiacomo, D. K., Nguyen, H., & Hays, M. (2021). Making Sense of Sensemaking: Understanding How K–12 Teachers and Coaches React to Visual Analytics. Journal of Learning Analytics, 8(3), 60–80. https://doi.org/10.18608/jla.2021.7113
  

• Edsight

  EdSight(n.d.). Retrieved August 20, 2022, from https://edsight.io/
  

• Practice-Driven Data: Lessons from Chicago's Approach to Research, Data, and Practice in Education

  Moeller, E., Seeskin, A., & Nagaoka, J. (2018). Practice-Driven Data: Lessons from Chicago’s Approach to Research, Data, and Practice in Education. UChicago Consortium on School Research.
  

• Data-Intensive Improvement: The Intersection of Data Science and Improvement Science

  Krumm, A. E., & Bowers, A. J. (2022). Data-Intensive Improvement: The Intersection of Data Science and Improvement Science. In D. J. Peurach, J. L. Russell, L. Cohen-Vogel, & W. R. Penuel (Eds.), The Foundational Handbook on Improvement Research in Education (pp. 465-483). Rowman & Littlefield Publishers. https://rowman.com/ISBN/9781538152348/The-Foundational-Handbook-on-Improvement-Research-in-Education
  

• Measurement for Improvement

  Takahashi, S., Jackson, K., Norman, J. R., & Ing, M. (2022). Measurement for Improvement. In D. J. Peurach, J. L. Russell, L. Cohen-Vogel, & W. R. Penuel (Eds.), The Foundational Handbook on Improvement Research in Education (p. 423-442). Rowman & Littlefield Publishers. https://rowman.com/ISBN/9781538152348/The-Foundational-Handbook-on-Improvement-Research-in-Education
  

• Just Schools: Building Equitable Collaborations with Families and Communities

  Ishimaru, A. M. (2019). Just Schools: Building Equitable Collaborations with Families and Communities. Teachers College Press.
  

• Personalization for Academic and Social Emotional Learning (PASL) Toolkit

  What is PASL? (n.d.). Vanderbilt University. Retrieved December 24, 2021, from https://my.vanderbilt.edu/pasltoolkit/