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Teacher capacity for and beliefs about data-driven decision making: A literature review of international research

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Abstract

Data-driven decision making continues to be a growing educational reform initiative across the globe. The effective use of data requires that teachers develop the knowledge and skills to analyze and use data to improve instruction. The purpose of this article is to examine teachers’ capacity for and beliefs about data use. These issues are examined through a review of research in the past decade. We find that teachers’ beliefs about and capacity for data use are often not connected within the literature or in practice, but we argue they are the heart of the connection between data and instructional change. Teachers’ capacity to use data and their beliefs about data use are shaped within their professional communities, in training sessions, and in their interactions with coaches, consultants, and principals. However, efforts to develop teachers’ capacity for data use often fall short of their goals. Correspondingly, teachers have varied beliefs about data use, and some feel they lack the ability to use data to inform instruction. In order to be more successful, capacity building should directly address teachers’ beliefs, and data use must be decoupled from external accountability demands and involve a variety of information on student learning.

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References

  • Bambrick-Santoyo, P. (2010). Driven by data: A practice guide to improve instruction. San Francisco: Jossey Bass Publishers.

    Google Scholar 

  • Bernhardt, V. (2013). Data analysis for continuous improvement (3rd ed.). New York: Routledge.

    Google Scholar 

  • Blanc, S., Christman, J. B., Liu, R., Mitchell, C., Travers, E., & Bulkley, K. E. (2010). Learning to learn from data: Benchmarks and instructional communities. Peabody Journal of Education, 85(2), 205–225.

    Article  Google Scholar 

  • Bocala, C., & Boudett, K. P. (2015). Teaching educators habits of mind for using data wisely. Teachers College Record, 117(4), 1–20.

    Google Scholar 

  • Brookhart, S. M. (2011). Educational assessment knowledge and skills for teachers. Educational Measurement: Issues and Practice, 30(1), 3–12.

    Article  Google Scholar 

  • Brown, G. T., Lake, R., & Matters, G. (2011). Queensland teachers’ conceptions of assessment: The impact of policy priorities on teacher attitudes. Teaching and Teacher Education, 27(1), 210–220.

    Article  Google Scholar 

  • Bruning, R., Schraw, G., & Ronning, R. (1999). Cognitive psychology and instruction. Upper Saddle River, NJ: Prentice Hall.

    Google Scholar 

  • Cho, V., & Wayman, J. (2014). District efforts for data use and computer data systems: The role of sensemaking in system use and implementation. Teachers College Record, 116, 020306.

    Google Scholar 

  • Christman, J. B., Neild, R. C., Bulkley, K., Blanc, S., Liu, R., Mitchell, C., & Travers, E. (2009). Making the most of interim assessment data. Lessons from Philadelphia. Retrieved from http://www.researchforaction.org/wp-content/uploads/publication-photos/41/Christman_J_Making_the_Most_of_Interim_Assessment_Data.pdf.

  • Coburn, C., & Talbert, J. (2006). Conceptions of evidence use in school districts: Mapping the terrain. American Journal of Education, 112(4), 469–495.

    Article  Google Scholar 

  • Coburn, C. E., & Turner, E. O. (2011). Research on data use: A framework and analysis. Measurement: Interdisciplinary Research and Perspectives, 9(4), 173–206.

    Google Scholar 

  • Cosner, S. (2011a). Teacher learning, instructional considerations and principal communication: Lessons from a longitudinal study of collaborative data use by teachers. Educational Management Administration and Leadership, 39(5), 568–589.

    Article  Google Scholar 

  • Cosner, S. (2011b). Supporting the initiation and early development of evidence-based grade-level collaboration in urban elementary schools: Key roles and strategies of principals and literacy coordinators. Urban Education, 46(4), 786–827.

    Article  Google Scholar 

  • Daly, A. J. (2012). Data, dyads, and dynamics: Exploring data use and social networks in educational improvement. Teachers College Record, 114(11), 110305.

    Google Scholar 

  • Datnow, A., & Hubbard, L. (2015). Teachers’ use of data to inform instruction: Lessons from the past and prospects for the future. Teachers College Record, 117(4), 1–26.

    Google Scholar 

  • Datnow, A., & Park, V. (2014). Data-driven leadership. San Francisco: Jossey Bass.

    Google Scholar 

  • Datnow, A., Park, V., & Kennedy-Lewis, B. (2013). Affordances and constraints in the context of teacher collaboration for the purpose of data use. Journal of Educational Administration, 51(3), 341–362.

    Article  Google Scholar 

  • Davidson, K. L., & Frohbieter, G. (2011). District adoption and implementation of interim and benchmark assessments (Report No. 806). Los Angeles, CA: National Center for Research on Evaluation, Standards, and Student Testing (CRESST).

  • Diamond, J. B., & Cooper, K. (2007). The uses of testing data in urban elementary schools: Some lessons from Chicago. National Society for the Study of Education Yearbook, 106(1), 241–263.

    Article  Google Scholar 

  • Dunn, K. E., Airola, D. T., Lo, W., & Garrison, M. (2012). What teachers think about what they can do with data: Development and validation of the data-driven decision making efficacy and anxiety inventory. Contemporary Educational Psychology, 38, 87–98.

    Article  Google Scholar 

  • Earl, L., & Katz, S. (2006). Leading schools in a data-rich world. Thousand Oaks, CA: Corwin Press.

    Google Scholar 

  • Elmore, R. E. (1996). Getting to scale with good educational practice. Harvard Educational Review, 66(1), 1–26.

    Article  Google Scholar 

  • Farley-Ripple, E., & Buttram, J. (2015). The development of capacity for data use: The role of teacher networks in an elementary school. Teachers College Record, 117(4), 1–34.

    Google Scholar 

  • Firestone, W. A., & González, R. A. (2007). Culture and processes affecting data use in school districts. In P. A. Moss (Ed.), Evidence and decision making. Yearbook of the National Society for the Study of Education (pp. 132–154). Malden, MA: Blackwell.

    Google Scholar 

  • Gummer, E., & Mandinach, E. (2015). Building a conceptual framework for data literacy. Teachers College Record, 117(4), 1–22.

    Google Scholar 

  • Halverson, R., Grigg, J., Prichett, R., & Thomas, C. (2007). The new instructional leadership: Creating data-driven instructional systems in schools. Journal of School Leadership, 17(2), 159–193.

    Google Scholar 

  • Hamilton, L., Halverson, R., Jackson, S. S., Mandinach, E., Supovitz, J., & Wayman, J. (2009). IES Practice Guide: Using student achievement data to support instructional decision making (NCEE 2009-4067). Washington, DC: National Center for Education Evaluation and Regional Assistance. Retrieved from http://ies.ed.gov/ncee/wwc/pdf/practice_guides/dddm_pg_092909.pdf.

  • Honig, M. I., & Ikemoto, G. (2008). Adaptive assistance for learning improvement efforts: The case of the Institute for Learning. Peabody Journal of Education, 83(3), 328–363.

    Article  Google Scholar 

  • Honig, M. I., & Venkateswaran, N. (2012). School–central office relationships in evidence use: Understanding evidence use as a systems problem. American Journal of Education, 118(2), 199–222.

    Article  Google Scholar 

  • Horn, I. S., Kane, B. D., & Wilson, J. (2015). Making sense of student performance data: Data use logics and mathematics teachers’ learning opportunities. American Educational Research Journal, 52(2), 208–242.

    Article  Google Scholar 

  • Horn, I. S., & Little, J. W. (2010). Attending to problems of practice: Routines and resources for professional learning in teachers’ workplace interactions. American Educational Research Journal, 47(1), 181–217.

    Article  Google Scholar 

  • Hubbard, L., Datnow, A., & Pruyn, L. (2014). Multiple initiatives, multiple challenges: The promise and pitfalls of implementing data use. Studies in Educational Evaluation, 42, 54–62.

    Article  Google Scholar 

  • Huguet, A., Marsh, J. A., & Farrell, C. C. (2015) Building teachers’ data-use capacity: Insights from strong and struggling coaches. Education Policy Analysis Archives, 22(52), 1–26. http://epaa.asu.edu/ojs/index.php/epaa/article/view/1600/1315.

  • Ingram, D., Louis, K. S., & Schroeder, R. (2004). Accountability policies and teacher decision making: Barriers to the use of data to improve practice. Teachers College Record, 106(6), 1258–1287.

    Article  Google Scholar 

  • Jimerson, J. B. (2014). Thinking about data: Exploring the development of mental models for “data use” among teachers and school leaders. Studies in Educational Evaluation, 42, 5–14.

    Article  Google Scholar 

  • Jimerson, J. B., & Wayman, J. C. (2015). Professional learning for using data: Examining teacher needs and supports. Teachers College Record, 117(4), 1–36.

    Google Scholar 

  • Kerr, K. A., Marsh, J. A., Ikemoto, G. S., Darilek, H., & Barney, H. (2006). Strategies to promote data use for instructional improvement: Actions, outcomes, and lessons from three urban districts. American Journal of Education, 112(3), 496–520.

    Article  Google Scholar 

  • Knapp, M. S., Copland, M. A., Swinnerton, J. A. (2007). School district roles and resources: Understanding the promise and dynamics of data-informed leadership. In P. A. Moss (Ed.), Evidence and decision making (National Society for the Study of Education Yearbook, Vol. 106, Issue 1, pp. 74–104). Chicago: National Society for the Study of Education.

  • Lachat, M. A., & Smith, S. (2005). Practices that support data use in urban high schools. Special issue on transforming data into knowledge: Applications of data-based decision making to improve instructional practice. Journal of Education Change for Students Placed At-Risk, 10(3), 333–349.

    Article  Google Scholar 

  • Levin, J., & Datnow, A. (2012). The principal as agent of mediated educational reform: Dynamic models of case Studies of data driven decision making. School Effectiveness and School Improvement, 23(2), 179–201.

    Article  Google Scholar 

  • Long, L., Rivas, L. M., Light, D., & Mandinach, E. B. (2008). The evolution of the homegrown data warehouse: TUSDSstats. In E. B. Mandinach & M. Honey (Eds.), Data-driven school improvement: Linking data and learning. New York: Teachers College Press.

    Google Scholar 

  • Mandinach, E. B., & Gummer, E. S. (2013). A systemic view of implementing data literacy in educator preparation. Educational Researcher, 42(1), 30–37.

    Article  Google Scholar 

  • Mandinach, E. B., Gummer, E. S., & Friedman, J. M. (2015). How can schools of education help to build educators’ capacity to use data: A systemic view of the issue. Teachers College Record, 117(4), 1–50.

    Google Scholar 

  • Mandinach, E. B., & Honey, M. (Eds.). (2008). Data driven school improvement: Linking data and learning. New York, NY: Teachers College Press.

    Google Scholar 

  • Marsh, J. A. (2012). Interventions promoting educators’ use of data: Research insights and gaps. Teachers College Record, 114(11), 1–48.

    Google Scholar 

  • Marsh, J. A., Bertrand, M., & Huguet, A. (2015). Using data to alter instructional practice: The mediating role of coaches and professional learning communities. Teachers College Record, 117(4), 1–40.

    Google Scholar 

  • Marsh, J. A., & Farrell, C. C. (2015). Supporting teachers with data-driven decision making: A framework for understanding capacity-building. Education Management Administration and Leadership, 43(2), 269–289.

    Article  Google Scholar 

  • Means, B., Chen, E., DeBarger, A. & Padilla, C. (2011). Teachers’ ability to use data to inform instruction: Challenges and supports. US Department of Education, Office of Planning, Evaluation, and Policy Development, Washington, DC.

  • Means, B., Padilla, C., DeBarger, A., & Bakia, M. (2009). Implementing data-informed decision making in schools—Teacher access, supports and use. Washington, DC: US Department of Education, Office of Planning, Evaluation, and Policy Development.

    Google Scholar 

  • Means, B., Padilla, C., & Gallagher, L. (2010). Use of education data at the local level: From accountability to instructional improvement. US Department of Education, Office of Planning, Evaluation, and Policy Development, Washington, DC.

  • Nelson, T. H., & Slavit, D. (2007). Collaborative inquiry among science and mathematics teachers in the USA: Professional learning experiences through cross-grade, cross-discipline dialogue. Professional Development in Education, 33(1), 23–39.

    Google Scholar 

  • Park, V., Daly, A. J., & Guerra, A. W. (2012). Strategic framing: How leaders craft the meaning of data use for equity and learning. Educational Policy, 27(4), 645–675. doi:10.1177/0895904811429295.

    Article  Google Scholar 

  • Pierce, R., & Chick, H. (2011). Teachers’ intentions to use national literacy and numeracy assessment data: A pilot study. Australian Educational Research, 38(3), 433–477.

    Article  Google Scholar 

  • Remesal, A. (2011). Primary and secondary teachers’ conceptions of assessment: A qualitative study. Teaching and Teacher Education, 27(2), 472–482.

    Article  Google Scholar 

  • Schildkamp, K., & Kuiper, W. (2010). Data-informed curriculum reform: Which data, what purposes, and promoting and hindering factors. Teaching and Teacher Education, 26(3), 482–496.

    Article  Google Scholar 

  • Schildkamp, K., & Lai, M. K. (2012). Introduction. In K. Schildkamp, M. K. Lai, & L. Earl (Eds.), Data-based decision making in education: Challenges and opportunities (pp. 1–9). Dordrecht: Springer.

    Google Scholar 

  • Schildkamp, K., & Poortman, C. (2015). Factors influencing the functioning of data teams. Teachers College Record, 117(4), 1–42.

    Google Scholar 

  • Schnellert, L. M., Butler, D. L., & Higginson, S. K. (2008). Co-constructors of data, co-constructors of meaning: Teacher professional development in an age of accountability. Teaching and Teacher Education, 24(3), 725–750.

    Article  Google Scholar 

  • Senge, P. (1990). The fifth discipline: The art and practice of the learning organization. New York: Doubleday.

    Google Scholar 

  • Spillane, J. (2012). Data in practice: Conceptualizing the data-based decision-making phenomena. American Journal of Education, 118, 113–141.

    Article  Google Scholar 

  • Spillane, J., & Miele, D. (2007). Evidence in practice: A framing of the terrain. In P. A. Moss (Ed.), Evidence and decision making (National Society for the Study of Education Yearbook, Vol. 106, Issue 1, pp. 46–73). Chicago: National Society for the Study of Education.

  • Takahashi, S. (2011). Co-constructing efficacy: A “communities of practice” perspective on teachers’ efficacy beliefs. Teaching and Teacher Education, 27, 732–741.

    Article  Google Scholar 

  • TERC. (n.d.). Using data to improve learning for all. Retrieved from http://usingdata.terc.edu/.

  • Timperley, H. (2009). Evidence-informed conversations making a difference to student achievement. In L. Earl & H. Timperley (Eds.), Professional learning conversations: Challenges in using evidence for improvement (pp. 69–79). New York: Springer.

    Chapter  Google Scholar 

  • Tschannen-Moran, M., & Woolfolk-Hoy, A. (2001). Teacher efficacy: Capturing an elusive construct. Teaching and Teacher Education, 17, 783–805.

    Article  Google Scholar 

  • Wayman, J. C., & Cho, V. (2008). Preparing educators to effectively use student data systems. In T. J. Kowalski & T. J. Lasley (Eds.), Handbook on data-based decision-making in education (pp. 89–104). New York: Routledge.

    Google Scholar 

  • Wenger, E. (1998). Communities of practice: Learning, meaning and identity. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • White, P. A. U. L., & Anderson, J. U. D. Y. (2011). Teachers’ use of national test data to focus numeracy instruction. Mathematics: Traditions and [new] practices, 777–785.

  • Woolfolk, A. E., Rossoff, B., & Hoy, W. K. (1990). Teachers’ sense of efficacy and their beliefs about managing students. Teaching and Teacher Education, 6, 137–148.

    Article  Google Scholar 

  • Young, V. M. (2006). Teachers’ use of data: Loose coupling, agenda setting, and team norms. American Journal of Education, 112(4), 521–548.

    Article  Google Scholar 

  • Young, V. M. & Kim, D. H. (2010). Using assessments for instructional improvement: A literature review. Educational Policy Analysis Archives, 18(19). Retrieved from http://epaa.asu.edu/ojs/article/view/809/852.

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Datnow, A., Hubbard, L. Teacher capacity for and beliefs about data-driven decision making: A literature review of international research. J Educ Change 17, 7–28 (2016). https://doi.org/10.1007/s10833-015-9264-2

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