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Conclusions and a Data Use Framework

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Book cover Data-based Decision Making in Education

Part of the book series: Studies in Educational Leadership ((SIEL,volume 17))

Abstract

In this chapter, the results of all the studies presented in this book are summarized. What are the lessons learned? Based on the lessons learned, we developed a data use framework. In this framework, data use is influenced by several enablers and barriers (e.g., the school organization context, data and data systems, and user characteristics). Data can be used in a desirable as well as undesirable manner, but what happens a lot in schools as well is that data are not used. Policy may also influence the use of data, as well as its enablers and barriers. Finally, we argue that if data are used in a desirable manner this can lead to school leader, teacher, and student learning (e.g., increased student achievement).

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References

  • Breiter, A., & Light, D. (2006). Data for school improvement: Factors for designing effective information systems to support decision-making in schools. Educational Technology & Society, 9(3), 206–217.

    Google Scholar 

  • Carlson, D., Borman, G., & Robinson, M. (2011). A multistate district-level cluster randomized trial of the impact of data-driven reform on reading and mathematics achievement. Education and Evaluation and Policy Analysis, 33(3), 378–398.

    Article  Google Scholar 

  • Chen, E., Heritage, M., & Lee, J. (2005). Identifying and monitoring students’ learning needs with technology. Journal of Education for Students Placed at Risk, 10(3), 309–332.

    Article  Google Scholar 

  • Comenius project using data for improving school and student performance. (2011). Comparative analysis data use in Germany, the Netherlands, Lithuania, Poland and England. Retrieved from: http://www.datauseproject.eu/home/documents. Accessed 4 Jan 2012

    Google Scholar 

  • Datnow, A., Park, V., & Wohlstetter, P. (2007). Achieving with data. How-high performing school systems use data to improve instruction for elementary students. San Francisco: Center on Educational Governance University of California.

    Google Scholar 

  • Diamond, J. B., & Spillane, J. P. (2004). High-stakes accountability in urban elementary schools: challenging or reproducing inequality. Teachers College Record, 106(6), 1145–1176.

    Article  Google Scholar 

  • Earl, L. M. (August 7–9, 2005). From accounting to accountability: Harnessing data for school improvement. Paper presented at the ACER research conference, Melbourne.

    Google Scholar 

  • Earl, L. M., & Katz, S. (2006). Leading schools in a data-rich world. Harnessing data for school improvement. Thousand Oaks: Corwin.

    Google Scholar 

  • Ehren, M. C. M., & Swanborn, M. S. L. (2012). Strategic data use in accountability systems. School Effectiveness and School Improvement, 23(2), 257–280.

    Google Scholar 

  • Feldman, J., Tung, R. (April 10–14, 2001). Whole school reform: How schools use the data-based inquiry and decision making process. Paper presented at the American educational research association conference, Seattle.

    Google Scholar 

  • Hamilton, L. S., Stecher, B. M., & Yuan, K. (2009). Standards-Based Reform in the United States: History, Research, and Future Directions. Santa Monica: RAND Corporation. Retrieved http://www.rand.org/pubs/reprints/RP1384. Accessed 15 Nov 2011

    Google Scholar 

  • Handelzalts, A. (2009). Collaborative curriculum development in teacher design teams. Enschede: Universiteit Twente.

    Google Scholar 

  • Huffman, D., & Kalnin, J. (2003). Collaborative inquiry to make data-based decisions in schools. Teaching and Teacher Education, 19(6), 569–580.

    Article  Google Scholar 

  • Kelly, A., Downey, C and Rietdijk, W. (2010). Data dictatorship and data democracy: Understanding professional attitudes to the use of pupil performance data in English secondary schools. Reading: CfBT Education Trust.

    Google Scholar 

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

    Article  Google Scholar 

  • King, M. B. (2002). Professional development to promote schoolwide inquiry. Teaching and Teacher Education, 18(3), 243–257.

    Article  Google Scholar 

  • Lachat, M.A., & Smith, S. (2005). Practices that support data use in urban high schools. Journal of Education for Students Placed at Risk, 10(3), 333–349.

    Article  Google Scholar 

  • Lai, M. K., & McNaughton, S. (2008). Raising student achievement in poor, urban communities through evidence-based conversations. In L. Earl & H. Timperley (Eds.), Evidence-based conversations to improve educational practices (pp. 13–27). Netherlands: Kluwer/Springer Academic.

    Google Scholar 

  • Lai, M. K., McNaughton, S., Amituanai-Toloa, M., Turner, R., & Hsiao, S. (2009). Sustained acceleration of achievement in reading comprehension: The New Zealand experience. Reading Research Quarterly, 44(1), 30–56.

    Article  Google Scholar 

  • Leithwood, K., Jantzi, D., & McElheron-Hopkins, C. (2006). The development and testing of a school improvement model. School Effectiveness and School Improvement, 17(4), 441–464.

    Article  Google Scholar 

  • Levin, J. A., & Datnow, A. (2012). The principal role in data-driven decision making: using case-study data to develop multi-mediator models of educational reform. School Effectiveness and School Improvement, 23(2), 179–202.

    Google Scholar 

  • Louis, K., & Marks, H. (1998). Does professional learning community affect the classroom teachers’ work and student experience in restructured schools? American Journal of Education, 106(4), 532–575.

    Article  Google Scholar 

  • Mingchu, L. (2008). Structural equation modeling for high school principals’ data-driven decision making: An analysis of information use environments. Educational Administration Quarterly, 44(5), 603–634.

    Article  Google Scholar 

  • Robinson, V. M. J, & Lai, M. K. (2006). Practitioner research for educators: A guide to improving classrooms and schools. Thousand Oaks: Corwin.

    Google Scholar 

  • Robinson, V. M. J., Phillips, G., & Timperley, H. (2002). Using achievement data for school-based curriculum review: A bridge too far? Leadership and Policy in Schools, 1(1), 3–29.

    Article  Google Scholar 

  • Rossi, P. H., Freeman, H. E., & Lisey, M. W. (1999). Evaluation: A systematic approach. Thousand Oaks: Sage.

    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, 482–496.

    Article  Google Scholar 

  • Schildkamp, K., & Teddlie, C. (2008). School performance feedback systems in the USA and in the Netherlands: A comparison. Educational Research and Evaluation, 14(3), 255–282.

    Article  Google Scholar 

  • Schildkamp, K., & Handelzalts, A. (2011, April). Data teams for school improvement. Paper presented at the American Educational Research Association Conference, New Orleans, USA.

    Google Scholar 

  • Sharkey, N. S., & Murnane, R. J. (2006). Tough choices in designing a formative assessment system. American Journal of Education, 112, 572–588.

    Article  Google Scholar 

  • Sutherland, S. (2004). Creating a culture of data use for continuous improvement: a case study of an Edison project school. The American Journal of Evaluation, 25(3), 277–293.

    Article  Google Scholar 

  • Tokar, D. M., Fischer, A. R., & Mezydlo Subich, L. (1998). Personality and vocational behavior: A selective review of the literature, 1993–1997. Journal of Vocational Behavior, 53, 115–153.

    Google Scholar 

  • Tolley, H. & Shulruf, B. (2009). From data to knowledge: the interaction between data management systems in educational institutions and the delivery of quality education. Computers & Education, 53(4), 1199–1206.

    Article  Google Scholar 

  • Verhaeghe, G., Vanhoof, J., Martin, V., & van Petegem, P. (2010). Using school performance feedback: Perceptions of primary school principals. School Effectiveness and School Improvement, 21(2), 167–188.

    Article  Google Scholar 

  • Visscher, A. J. (2002). A framework for studying school performance feedback systems. In A. J. Visscher & R. Coe (Eds.), School improvement through performance feedback (pp. 41–72). Lisse: Swets & Zeitlinger B.V.

    Google Scholar 

  • Wayman, J. C., & Stringfield, S. (2006a). Data use for school improvement: School practices and research perspectives. American Journal of Education, 112, 463–468.

    Article  Google Scholar 

  • Wayman, J. C., & Stringfield, S. (2006b). Technology-supported involvement of entire faculties in examination of student data for instructional improvement. American Journal of Education, 112(4), 549–571.

    Article  Google Scholar 

  • Wayman, J. C., Midgley, S., Stringfield, S. (April 11–15, 2005). Collaborative teams to support data-based decision making and instructional improvement. Paper presented at the American educational research association conference, Montreal.

    Google Scholar 

  • Wayman, J. C., Cho, V., & Johnston, M. T. (2007). The data-informed district: A districtwide evaluation of data use in the Natrona County School District. Austin: The University of Texas.

    Google Scholar 

  • Weiss, C.H. (1998). Have we learned anything new about the use of evaluation? American Journal of Evaluation, 19(1), 21–33.

    Google Scholar 

  • Wohlstetter, P., Datnow, A., & Park, V. (2008). Creating a system for data-driven decision-making: Applying the principal-agent framework. School Effectiveness and School Improvement, 19(3), 239–259.

    Article  Google Scholar 

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

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Faculty of Behavioural Sciences, University of Twente, Enschede, Netherlands

    Kim Schildkamp

  2. Woolf Fisher Research Centre, The University of Auckland, Auckland, New Zealand

    Mei Kuin Lai

Authors
  1. Kim Schildkamp
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  2. Mei Kuin Lai
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Correspondence to Kim Schildkamp .

Editor information

Editors and Affiliations

  1. , Curriculum Design & Educational Innovati, University of Twente, P.O. Box 217, Enschede, 7500 AE, Netherlands

    Kim Schildkamp

  2. School of Curriculum and Pedagogy, The University of Auckland, Symonds Street, Auckland, 1150, New Zealand

    Mei Kuin Lai

  3. Aporia Consulting Ltd., Yonge St. Suite # 240 3219, Toronto, M4N 3S1, Canada

    Lorna Earl

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Schildkamp, K., Lai, M. (2013). Conclusions and a Data Use Framework. In: Schildkamp, K., Lai, M., Earl, L. (eds) Data-based Decision Making in Education. Studies in Educational Leadership, vol 17. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-4816-3_10

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