Teacher capacity for and beliefs about data-driven decision making: A literature review of international research
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.
KeywordsData-driven decision making Teacher capacity Teacher beliefs
- 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
- Bocala, C., & Boudett, K. P. (2015). Teaching educators habits of mind for using data wisely. Teachers College Record, 117(4), 1–20.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. E., & Turner, E. O. (2011). Research on data use: A framework and analysis. Measurement: Interdisciplinary Research and Perspectives, 9(4), 173–206.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
- 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).Google Scholar
- Earl, L., & Katz, S. (2006). Leading schools in a data-rich world. Thousand Oaks, CA: Corwin Press.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.
- 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.
- 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
- 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.Google Scholar
- 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.CrossRefGoogle 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., & 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
- 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.Google Scholar
- 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.Google Scholar
- 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
- 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
- Senge, P. (1990). The fifth discipline: The art and practice of the learning organization. New York: Doubleday.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.Google Scholar
- TERC. (n.d.). Using data to improve learning for all. Retrieved from http://usingdata.terc.edu/.
- 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
- 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.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.