Abstract
Schools these days are confronted with a lot of data, which they have to transform into information to be used for school improvement. However, research shows that most teachers do not use data properly, or do not use data at all. In the Netherlands, a data team intervention was developed and piloted to support schools in the use of data.
A data team is a team, consisting of 4–6 teachers, a data expert, an (assistant) school leader, and a researcher, who work together to solve a certain educational problem, following a structured approach. This approach involves: defining the problem, coming up with hypotheses concerning what causes the problem, collecting data to test the hypotheses, analyzing and interpreting data, drawing conclusions, and implementing measures to improve education. This study focuses on the following research questions: How do these teams function? Which factors influence the work of these data teams? What are the effects of these data teams?
The results show the data team intervention led to an increase in effective data use, changes in classroom instruction, and to school improvement (e.g., a significant increase in mathematic achievement). Due to the small sample of this study, the increase in student achievement cannot directly be linked to the work of the data teams, but it is likely that the use of data contributed to these effects.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Criteria are: insufficient student achievement results for 3 subsequent years, declining student achievement results, which are below average for the last 2 years, insufficient student achievement results in math, language, or in the final examinations, or above average number of drop outs or retentions.
References
Black, P., & Wiliam, D. (1998). Inside the black box: Raising standards through classroom assessment. Phi Delta Kappan, 80(2), 139–148.
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.
Brunner, C., Fasca, C., Heinze, J., Honey, M., Light, D., Mandinach, E. et al. (2005). Linking data and learning: The grow network study. Journal of Education for Students Placed at Risk, 10(3), 241–267.
Campbell, C., & Levin, B. (2009). Using data to support educational improvement. Educational Assessment, Evaluation and Accountability, 21, 47–65.
Cawelti, G., & Protheroe, N. (2001). High student achievement: How six school districts changed into high-performance systems. Arlington: Educational Research Service.
Coburn, C. E., & Talbert, J. E. (2006). Conceptions of evidence use in school districts: mapping the terrain. American Journal of Education, 112, 469–495.
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.
Earl, L. M., & Katz, S. (2006). Leading schools in a data-rich world. Harnessing data for school improvement. Thousand Oaks: Corwin.
Ehren, M. C. M., & Swanborn, M.S.L. (2012). Strategic data use of schools in accountability systems. School Effectiveness and School Improvement, 23(2), 257–280.
Eurydice. (2009). Organisation of the Education system in the Netherlands. The Haugue: European Commission. Retrieved from http://eacea.ec.europa.eu/education/eurydice/eurybase_en.php#description. Accessed 15 Nov 2011.
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.
Ikemoto, G. S., & Marsh, J. A. (2007). Cutting through the data-driven mantra: Different conceptions of data-driven decision making. In P. A. Moss (Ed.), Evidence and decision making. Malden: Wiley-Blackwell.
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.
Ledoux, G., Blok, H., Boogaard, M., & Krüger, M. (2009). Opbrengstgericht werken. Over de waarde van meetgestuurd onderwijs (Data-driven decission making: the value of data-driven education). Amsterdam: SCO-Kohnstamm Instituut.
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.
McNaughton, S., Lai, M. K. & Hsiao, S. (2012). Testing the effectiveness of an intervention model based on data use: A replication series across clusters of schools. School effectiveness and School Improvement, 23(2), 203–228.
Ministerie, van Onderwijs Cultuur & Wetenschappen. (1999). Variëteit en waarborg: Voorstellen voor de ontwikkeling van het toezicht oponderwijs (Diversity and a guarantee: Proposals for the development of the supervision of education). Zoetermeer: Ministerie van Onderwijs, Cultuur & Wetenschappen.
Schildkamp, K., & Ehren, M.C.M. (submitted). An exploratory study into the use of accountability data in the Netherlands.
Schildkamp, K., & Handelzalts, A. (2011, April). Data teams for school improvement. Paper presented at the American Educational Research Association Conference, New Orleans, USA.
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.
Wayman, J. C. (2005). Involving teachers in data-driven decision making: using computer data systems to support teacher inquiry and reflection. Journal of Education for Students Placed at Risk, 10(3), 295–308.
Wayman, J. C., & Stringfield, S. (2006a). Data use for school improvement: school practices and research perspectives. American Journal of Education, 112, 463–468.
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, 549–571.
Wayman, J. C., Midgley, S., & Stringfield, S. (2006). Leadership for data-based decision making: Collaborative educator teams. In A. Danzig, K. Borman, B. Jones, & B. Wright (Eds.), New models of professional development for learner centered leadership (pp. 189–205). Hillsdale: Erlbaum.
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.
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.
Young, V. M. (2006). Teachers’ use of data: loose coupling, agenda setting, and team norms. American Journal of Education, 112, 521–548.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer Science+Business Media Dordrecht
About this chapter
Cite this chapter
Schildkamp, K., Ehren, M. (2013). From “Intuition”- to “Data”-based Decision Making in Dutch Secondary Schools?. 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_4
Download citation
DOI: https://doi.org/10.1007/978-94-007-4816-3_4
Published:
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-007-4815-6
Online ISBN: 978-94-007-4816-3
eBook Packages: Humanities, Social Sciences and LawEducation (R0)