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Feedback of Monitoring Data and Its Role in Decision Making at School and Classroom Level

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Book cover Monitoring the Quality of Education in Schools

Abstract

This chapter focusses on how data from monitoring systems, such as assessment results, can be used as a form of feedback. Teachers and school leaders can use this feedback in their decision making at school and classroom level.

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References

  • Alkin, M. C., & Daillak, R. H. (1979). A study of evaluation utilization. Educational Evaluation and Policy Analysis, 1(4), 41–49.

    Article  Google Scholar 

  • Alkin, M. C., & Taut, S. M. (2003). Unbundling evaluation use. Studies in Educational Evaluation, 29, 1–12.

    Article  Google Scholar 

  • Archer, E. (2010). Bridging the gap: Optimising a feedback system for monitoring learning performance (Doctoral dissertation). University of Pretoria, Pretoria. Retrieved from http://repository.up.ac.za/handle/2263/26608

    Google Scholar 

  • Archer, E., Scherman, V., & Howie, S. (2013). Approaches to effective data use: Does one size fit all? In K. Schildkamp, M. K. Lai, & L. Earl (Eds.), Data-based decision making in education: Challenges and opportunities (pp. 91–112). Dordrecht, The Netherlands: Springer.

    Chapter  Google Scholar 

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

    Google Scholar 

  • Campbell, C., & Levin, B. (2009). Using data to support educational improvement. Educational Assessment, Evaluation and Accountability, 21, 47–65.

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Centre for Educational Research and Innovation. (2008). 21st century learning: Research, innovation and policy: Directions from recent OECD analyses. Paris, France: OECD.

    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, 309–332.

    Article  Google Scholar 

  • Coburn, C. E. (2010). The partnership for district change: The challenges of evidence use in a major urban district. In C. E. Coburn & M. K. Stein (Eds.), Research and practice in education: Building alliances, bridging the divide (pp. 167–182). New York, NY: Rowman & Littlefield.

    Google Scholar 

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

    Google Scholar 

  • Coburn, C. E., & Turner, E. O. (2012). The practice of data use: An introduction. American Journal of Education, 118, 99–111.

    Article  Google Scholar 

  • Copland, M. A. (2003). The Bay area school reform collaborative: Building the capacity to lead. In J. Murphy & A. Datnow (Eds.), Leadership lessons from comprehensive school reforms (pp. 159–183). Thousand Oaks, CA: Corwin Press.

    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, 341–362.

    Article  Google Scholar 

  • Earl, L., & Fullan, M. (2003). Using data in leadership for learning. Cambridge Journal of Education, 33, 383–394.

    Article  Google Scholar 

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

    Google Scholar 

  • Fitz-Gibbon, C. T., & Tymms, P. (2002). Technical and ethical issues in indicator systems. Education Policy Analysis Archives, 10(6), 1–28.

    Google Scholar 

  • Goldstein, H., & Spiegelhalter, D. J. (1996). League tables and their limitations: Statistical issues in comparisons of institutional performance. Journal of the Royal Statistical Society: Series A (Statistics in Society), 159, 385–443.

    Article  Google Scholar 

  • Harnar, M. A., & Preskill, H. (2007). Evaluators’ descriptions of process use: An exploratory study. New Directions for Evaluation, 116, 27–44.

    Article  Google Scholar 

  • Hattie, J. (2005, August). What is the nature of evidence that makes a difference to learning? Paper presented at the 2005 ACER Research Conference, Melbourne, Australia.

    Google Scholar 

  • Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77, 81–112.

    Article  Google Scholar 

  • Hellrung, K., & Hartig, J. (2013). Understanding and using feedback – A review of empirical studies concerning feedback from external evaluations to teachers. Educational Research Review, 9, 174–190.

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Howie, S. J. (2002). English language proficiency and contextual factors influencing mathematics achievement of secondary school pupils in South Africa (Doctoral thesis). Enschede, The Netherlands: PrintPartners Ipskamp.

    Google Scholar 

  • Hulpia, H., & Valcke, M. (2004). The use of performance indicators in a school improvement policy: The theoretical and empirical context. Evaluation & Research in Education, 18, 102–119.

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Jansen, J. D. (2001). On the politics of performance in South African education: Autonomy, accountability and assessment. PROSPECTS, 31, 553–564.

    Article  Google Scholar 

  • Johnson, R. B. (1998). Toward a theoretical model of evaluation utilization. Evaluation and Program Planning, 21, 93–110.

    Article  Google Scholar 

  • Karsten, S., Visscher, A. J., Dijkstra, A. B., & Veenstra, R. (2010). Towards standards for the publication of performance indicators in the public sector: The case of schools. Public Administration, 88, 90–112.

    Article  Google Scholar 

  • Kluger, A. N., & DeNisi, A. (1996). The effects of feedback interventions on performance: A historical review, a meta-analysis, and a preliminary feedback intervention theory. Psychological Bulletin, 119, 254–284.

    Article  Google Scholar 

  • Kyriakides, L., & Campbell, R. J. (2004). School self-evaluation and school improvement: A critique of values and procedures. Studies in Educational Evaluation, 30, 23–36.

    Article  Google Scholar 

  • Lai, M. K., & Schildkamp, K. (2013). Data-based decision making: An overview. In K. Schildkamp, M. K. Lai, & L. Earl (Eds.), Data-based decision making in education: Challenges and opportunities (pp. 9–21). Dordrecht, The Netherlands: Springer.

    Chapter  Google Scholar 

  • Lai, M. K., McNaughton, S., Timperley, H., & Hsiao, S. (2009). Sustaining continued acceleration in reading comprehension achievement following an intervention. Educational Assessment, Evaluation and Accountability, 21, 81–100.

    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, 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, 179–201.

    Article  Google Scholar 

  • Mandinach, E. B. (2012). A perfect time for data use: Using data-driven decision making to inform practice. Educational Psychologist, 47, 71–85.

    Article  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., Pane, J. F., & Hamilton, L. S. (2006). Making sense of data-driven decision making in education: Evidence from recent RAND research. Santa Monica, CA: RAND Corporation.

    Google Scholar 

  • Marsh, J. A., McCombs, J. S., & Martorell, F. (2010). How instructional coaches support data-driven decision making: Policy implementation and effects in Florida middle schools. Educational Policy, 24, 872–907.

    Article  Google Scholar 

  • Park, V., & Datnow, A. (2009). Co-constructing distributed leadership: District and school connections in data-driven decision-making. School Leadership & Management, 29, 477–494.

    Article  Google Scholar 

  • Patton, M. Q. (1991). Towards utility in reviews of multivocal literatures. Review of Educational Research, 61, 287–292.

    Article  Google Scholar 

  • Patton, M. Q. (1997). Utilization-focused evaluation: The new century text (3rd ed). Thousand Oaks, CA: Sage.

    Google Scholar 

  • Poortman, C. L., Ebbeler, J., & Schildkamp, K. (2015, April). School improvement effects of a data use intervention for teachers. Paper presented at the Annual Meeting of the American Educational Research Association, Chicago, IL.

    Google Scholar 

  • Ragland, M. A., Clubine, B., Constable, D., & Smith, P. A. (2002). Expecting success: A study of five high performing, high poverty schools. Washington, DC: Council of Chief State School Officers. Retrieved from ERIC http://eric.ed.gov/?id=ED468010

    Google Scholar 

  • Reed, Y., Destefano, L., Taylor, N., Abel, L., & Howie, S. (2007, June). Systemic assessments and social justice: Strange bedfellows, or not? Paper presented at the Fourteenth International Conference on Learning, Johannesburg, South Africa.

    Google Scholar 

  • Rossi, P. H., Lipsey, M. W., & Freeman, H. E. (2004). Evaluation: A systemic approach (7th ed). Thousand Oaks, CA: Sage.

    Google Scholar 

  • Rowe, K. (2004, April). Analysing and reporting performance indicator data: “Caress” the data and user beware! Paper presented at the Public Sector Performance & Reporting Conference, Sydney, Australia.

    Google Scholar 

  • Rowe, K., & Lievesley, D. (2002, April). Constructing and using educational performance indicators. Paper presented at the Asia-Pacific Educational Research Association (APERA), Melbourne, Australia.

    Google Scholar 

  • Schaffer, E., Reynolds, D., & Stringfield, S. (2012). Sustaining turnaround at the school and district levels: The High Reliability Schools Project at Sandfields secondary school. Journal of Education for Students Placed at Risk, 17, 108–127.

    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, 482–496.

    Article  Google Scholar 

  • Schildkamp, K., & Lai, M. K. (2013). Conclusions and a data use framework. In K. Schildkamp, M. K. Lai., & L. Earl (Eds.), Data-based decision making in education: Challenges and opportunities (pp. 177–191). Dordrecht, The Netherlands: Springer.

    Chapter  Google Scholar 

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

    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, 255–282.

    Article  Google Scholar 

  • Shute, V. J. (2008). Focus on formative feedback. Review of Educational Research, 78, 153–189.

    Article  Google Scholar 

  • Snipes, J., Doolittle, F., & Herlihy, C. (2002). Foundations for success: Case studies of how urban school systems improve student achievement. Washington, DC: MDRC and the Council of Great City Schools.

    Google Scholar 

  • Taut, S. M., & Alkin, M. C. (2003). Program staff perceptions of barriers to evaluation implementation. American Journal of Evaluation, 24, 213–226.

    Article  Google Scholar 

  • Tymms, P. (1999). Baseline assessment and monitoring in primary schools: Achievements, attitudes and value-added indicators. London, UK: David Fulton.

    Google Scholar 

  • Tymms, P., & Albone, S. (2002). Performance indicators in primary schools. In A. J. Visscher & R. Coe (Eds.), School improvement through performance feedback (pp. 191–218). Lisse, The Netherlands: Swets & Zeitlinger.

    Google Scholar 

  • Verhaeghe, G., Schildkamp, K., Luyten, H., & Valcke, M. (2015). Diversity in school performance feedback systems. School Effectiveness and School Improvement, 26, 612–638.

    Article  Google Scholar 

  • Visscher, A. J., & Coe, R. (2002a). Drawing up the balance sheet for school performance feedback systems. In A. J. Visscher & R. Coe (Eds.), School improvement through performance feedback (pp. 221–254). Lisse, The Netherlands: Swets & Zeitlinger.

    Google Scholar 

  • Visscher, A. J., & Coe, R. (Eds.). (2002b). School improvement through performance feedback. Lisse, The Netherlands: Swets & Zeitlinger.

    Google Scholar 

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

    Article  Google Scholar 

  • Wayman, J. C., Jimerson, J. B., & Cho, V. (2012). Organizational considerations in establishing the Data-Informed District. School Effectiveness and School Improvement, 23, 159–178.

    Article  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, 239–259.

    Article  Google Scholar 

  • Yang, M., Goldstein, H., Rath, T., & Hill, N. (1999). The use of assessment data for school improvement purposes. Oxford Review of Education, 25, 469–483.

    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 

  • Zupanc, D., Urank, M., & Bren, M. (2009). Variability analysis for effectiveness and improvement in classrooms and schools in upper secondary education in Slovenia: Assessment of/for Learning Analytic Tool. School Effectiveness and School Improvement, 20, 89–122.

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Faculty of Behavioural, Management & Social Sciences, University of Twente, Netherlands

    Kim Schildkamp

  2. Department of Institutional Statistics and Analysis, University of South Africa, South Africa

    Elizabeth Archer

Authors
  1. Kim Schildkamp
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  2. Elizabeth Archer
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Editor information

Editors and Affiliations

  1. University of South Africa, South Africa

    Vanessa Scherman

  2. University of Groningen, Netherlands

    Roel J. Bosker

  3. University of Pretoria, South Africa

    Sarah J. Howie

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Schildkamp, K., Archer, E. (2017). Feedback of Monitoring Data and Its Role in Decision Making at School and Classroom Level. In: Scherman, V., Bosker, R.J., Howie, S.J. (eds) Monitoring the Quality of Education in Schools. SensePublishers, Rotterdam. https://doi.org/10.1007/978-94-6300-453-4_2

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  • DOI: https://doi.org/10.1007/978-94-6300-453-4_2

  • Publisher Name: SensePublishers, Rotterdam

  • Online ISBN: 978-94-6300-453-4

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