Assessment for Learning in K-12 Science Departments: A Case Study

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William Glenn

Abstract




This paper discusses the efforts of science departments in two secondary schools to implement data-driven decision making at the department level. It covers the first year of the process and identifies the successes and barriers to success experienced by the two departments. The catalyst for the change at each school was the department chair studying data analysis and applying the newly learned techniques to stimulate their science departments to study assessment data. The departments were surprised by some of their findings. For example, the faculty at one school found that their students performed poorly on one strand covered in the state’s science assessment. However, their data analysis showed that their students scored about equally well on each strand. The findings led both schools to consider and implement various changes. Both departments saw the need to use shorter and timelier formative assessments to drive instruction throughout the year. The departments encountered several barriers to using data-driven decision making to guide instruction. They found it easier to identify issues that needed to be addressed than implementing solutions.




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How to Cite
Glenn, W. (2009). Assessment for Learning in K-12 Science Departments: A Case Study. Journal of MultiDisciplinary Evaluation, 6(12), 44–51. https://doi.org/10.56645/jmde.v6i12.214
Section
Assessment for Learning

References

Ainsworth, L. (2007). Common formative assessments: The centerpiece of an integrated standards-based assessment system. In D. Reeves (Ed.), Ahead of the curve: The power of assessment to transform teaching and learning (pp. 79-102). Bloomington, IN: Solution Tree.

Basham, C., & Fathman, A. K. (2008). The latent speaker: Attaining adult fluency in an endangered language. International Journal of Bilingual Education and Bilingualism, 11(5), 577-597.

https://doi.org/10.1080/13670050802149192 DOI: https://doi.org/10.1080/13670050802149192

Boudett, K. P., City, E. A., & Murnane, R. J. (2007). Introduction. In K. P. Boudett, E. A. City, & R. J. Murnane (Eds.), Data wise: A step-by-step guide to using assessment results to improve teaching and learning (pp. 1-8). Cambridge, MA: Harvard Education Press.

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

Glenn, W. & Creighton, T. (2008). University teaching that improves school leadership: Basic techniques to help principals use data effectively. NCPEA Education Leadership Review 9(2) 129-142.

Kowalski, T. J., Lasley, II, T. J., & Mahoney, J. W. (2008). Data-driven decisions and school leadership: Best practices for school improvement. Boston: Pearson/Allyn and Bacon.

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.

https://doi.org/10.1207/s15327671espr1003_7 DOI: https://doi.org/10.1207/s15327671espr1003_7

Mandinach, E., Honey, M., Light, D., & Brunner, C. (2008). A conceptual framework for data-driven decision making. In E. Mandinach & M. Honey, Eds. Data- driven school improvement: Linking data and learning (pp. 13-31). New York: Teachers College Press.

Wayman, J. C., & Stringfield, S. (2006). Data use for school improvement: School practices and research perspectives. American Journal of Education, 112(4), 463-468.

https://doi.org/10.1086/505055 DOI: https://doi.org/10.1086/505055

Wayman, J. C., Stringfield, S., & Yakimowski, M. (2004). Software enabling school improvement through the analysis of student data (Report No. 67). Baltimore, MD: Johns Hopkins University, Center for Research on the Education of Students Placed At Risk.

Yin, R. K. (2009). Case study research: Design and methods (4th ed.). Thousand Oaks, CA: Sage.