Items

• 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
• 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.
• What's Your Theory? Driver Diagram Serves as Tool for Building and Testing Theories for Improvement
  Bennett, B., & Provost, L. (2015). What’s Your Theory? Driver Diagram Serves as Tool for Building and Testing Theories for Improvement. Quality Progress, 48(7), 36–43.
• Validity in Educational Assessment
  Moss, P. A., Girard, B. J., & Haniford, L. C. (2006). Validity in Educational Assessment. Review of Research in Education, 30, 109–162.
• Validity by Design
  Mislevy, R. J. (2007). Validity by Design. Educational Researcher, 36(8), 463–469.
• 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
• Toward Information Infrastructure Studies: Ways of Knowing in a Networked Environment
  Bowker, G. C., Baker, K., Millerand, F., & Ribes, D. (2010). Toward Information Infrastructure Studies: Ways of Knowing in a Networked Environment. In J. Hunsinger, L. Klastrup, & M. Allen (Eds.), International Handbook of Internet Research (pp. 97–117). Springer Netherlands. https://doi.org/10.1007/978-1-4020-9789-8_5
• The Uses of Argument
  Toulmin, S. E. (2003). The Uses of Argument (2nd ed.). Cambridge University Press. https://doi.org/10.1017/CBO9780511840005
• The Use of Ninth-Grade Early Warning Indicators to Improve Chicago Schools
  Allensworth, E. (2013). The Use of Ninth-Grade Early Warning Indicators to Improve Chicago Schools. Journal of Education for Students Placed at Risk (JESPAR), 18(1), 68–83. https://doi.org/10.1080/10824669.2013.745181
• The Three Faces of Performance Measurement: Improvement, Accountability, and Research
  Solberg, L. I., Mosser, G., & McDonald, S. (1997). The Three Faces of Performance Measurement: Improvement, Accountability, and Research. The Joint Commission Journal on Quality Improvement, 23(3), 135–147. https://doi.org/10.1016/S1070-3241(16)30305-4
• 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
• 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
• Principles to Actions: Ensuring Mathematical Success for All
  Leinwand, S., Brahier, D., & Huinker, D. (2014). Principles to Actions: Ensuring Mathematical Success for All. National Council of Teachers of Mathematics.
• Practical Measurement
  Yeager, D., Bryk, A., Muhich, J., Hausman, H., & Morales, L. (2013). Practical Measurement. Carnegie Foundation for the Advancement of Teaching.
• Measuring Motivation in Educational Settings: A Case for Pragmatic Measurement
  Kosovich, J. J., Hulleman, C. S., & Barron, K. E. (2019). Measuring Motivation in Educational Settings: A Case for Pragmatic Measurement. In K. A. Renninger & S. E. Hidi (Eds.), The Cambridge Handbook of Motivation and Learning (pp. 713–738). Cambridge University Press. https://doi.org/10.1017/9781316823279.030
• Measuring for Excellence
  Struebing, L. (1996). Measuring for Excellence. Quality Progress, 25–28.
• Measuring Equitable Science Instruction at Scale
  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
• Making Sense of Teachers’ Varied Responses to Representations of Practice
  Jackson, K., Nieman, H. J., & Kochmanski, N. (2019). Making Sense of Teachers’ Varied Responses to Representations of Practice. National Council of Teachers of Mathematics Research Conference.
• Improvement on the Front Lines: Using Learning Huddles to Shift Instruction
  Austin, K., & Bolte, J. (2019). Improvement on the Front Lines: Using Learning Huddles to Shift Instruction. https://ies.ed.gov/ncee/edlabs/regions/west/Publications/Details/270
• 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
• 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
• Evidence in Practice: A Framing of the Terrain
  Spillane, J. P., & Miele, D. B. (2007). Evidence in Practice: A Framing of the Terrain. Teachers College Record, 109(13), 46–73. https://doi.org/10.1177/016146810710901303
• Developing a Validity Argument for Practical Measures of Student Experience in Project-Based Science Classrooms
  Penuel, W. R., Van Horne, K., Jacobs, J. J., & Turner, M. (2018). Developing a Validity Argument for Practical Measures of Student Experience in Project-Based Science Classrooms. American Educational Research Association Annual Meeting.
• Designing in Context: Reaching Beyond Usability in Learning Analytics Dashboard Design
  Ahn, J., Campos, F., Hays, M., & Digiacomo, D. (2019). Designing in Context: Reaching Beyond Usability in Learning Analytics Dashboard Design. Journal of Learning Analytics, 6(2), 70–85. https://doi.org/10.18608/jla.2019.62.5
• Controlling Variation in Health Care: A Consultation from Walter Shewhart
  Berwick, D. M. (1991). Controlling Variation in Health Care: A Consultation from Walter Shewhart. Medical Care, 29(12), 1212–1225.
• 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
• Branching Out: Use Measurement Trees to Determine Whether Your Improvement Efforts Are Paying Off
  Bennett, B. (2018). Branching Out: Use Measurement Trees to Determine Whether Your Improvement Efforts Are Paying Off. Quality Progress, 19–23.
• Assessment to Promote Equity and Epistemic Justice: A Use-Case of a Research-Practice Partnership in Science Education
  Penuel, W. R., & Watkins, D. A. (2019). Assessment to Promote Equity and Epistemic Justice: A Use-Case of a Research-Practice Partnership in Science Education. The ANNALS of the American Academy of Political and Social Science, 683(1), 201–216. https://doi.org/10.1177/0002716219843249
• Aspects of High-Quality Mathematics Coaching: What Coaches Need to Know and Be Able to Do to Support Individual Teachers' Learning
  Kochmanski, N. (2020). Aspects of High-Quality Mathematics Coaching: What Coaches Need to Know and Be Able to Do to Support Individual Teachers’ Learning [Thesis]. https://ir.vanderbilt.edu/handle/1803/16114