Název: Exploring leadership influence within data-informed decision-making practices in Australian independent schools
Zdrojový dokument: Studia paedagogica. 2021, roč. 26, č. 4, s. [139]-159
Rozsah
[139]-159
-
ISSN1803-7437 (print)2336-4521 (online)
Trvalý odkaz (DOI): https://doi.org/10.5817/SP2021-4-7
Trvalý odkaz (handle): https://hdl.handle.net/11222.digilib/144772
Type: Článek
Jazyk
Licence: Neurčená licence
Upozornění: Tyto citace jsou generovány automaticky. Nemusí být zcela správně podle citačních pravidel.
Abstrakt(y)
There is increasingly strong pressure on schools to use data within their decision-making processes; the pressure comes not just from high-stakes testing but also from the subsequent comparative analysis conducted in the international, national, state, and local jurisdictions that represent the educational systems responsible for ensuring that students continue to receive quality education (Harris & Jones, 2017). There is paucity in empirical research within Australia on the practice of data use within schools; research is lacking on data interactions among school leaders in their workplace settings (Coburn & Turner, 2012). This study contributes toward this identified gap in Australian research literature on the practice of data-informed decision making (DIDM) in schools. Using a case-study approach at two K-12 independent schools in Victoria, Australia, the study sought to understand the "how" and "why" of DIDM systems that are currently in use within Australian independent schools in order to better understand what data-informed school improvement processes are being used in practice in this sector of Australian schooling. Based on the findings, we offer recommendations for developing improved system capabilities that make schools data literate and numerate and identify the important transformational role that senior and middle-level school leaders play in building up data-informed collaborative school cultures within their schools.
Note
This project was funded under the Dean's Early Career Research Project Award from Monash University, Australia, in the amount of AUD $30,336 over 2017-2018.
Reference
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[17] Fernandes, V., & Henderson, M. (2020). Activating turnaround leadership solicitation of datainformed decision-making within Australian public schools. In C. V. Meyers & M. J. Darwin (Eds.), School turnaround in secondary schools: Possibilities, complexities, and sustainability (1st Ed.), (pp. 59–81). Information Age Publishing.
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[19] Hansen, J. M., Gentry, R., & Dalley, T. (2003). Mindful change in a data-driven school. Principal Leadership, 3(6), 37–41.
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[23] Honig, M. I., & Coburn, C. E. (2008). Evidence-based decision making in school district central offices. Educational Policy, 22(4), 578–608. https://doi.org/10.1177/0895904807307067 | DOI 10.1177/0895904807307067
[24] Independent Schools Council of Australia (ISCA). (2018). Independent Schooling in Australia – Snapshot 2018. ISCA. http://isca.edu.au/wp-content/uploads/2018/05/18189-ISCA-2018-Snapshot-A4-2pp.pdf
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[26] Independent Schools Queensland (ISQ). (2017, May). Autonomy and school leadership: An independent schooling perspective [Discussion paper]. Independent Schools Queensland.
[27] Lai M., & Schildkamp, K. (2013). Data-based decision making: An overview. In K. Schildkamp, M. Lai, & L. Earl (Eds.), Data-based decision making in education. Studies in educational leadership (pp. 9–21). Springer. https://doi.org/10.1007/978-94-007-4816-3_2 | DOI 10.1007/978-94-007-4816-3_2
[28] Lai, M. K., Wilson, A., McNaughton, S., & Hsiao, S. (2014). Improving achievement in secondary schools: Impact of a literacy project on reading comprehension and secondary schools' qualifications. Reading Research Quarterly, 49(3), 305–334. https://doi.org/10.1002/rrq.73 | DOI 10.1002/rrq.73
[29] Lincoln, S. Y., & Guba, E. G. (1985). Naturalistic inquiry. Sage.
[30] Mandinach, E. B., & Gummer, E. S. (2013). A systemic view of implementing data literacy in educator preparation. Educational Researcher, 42(1), 30–37. https://doi.org/10.3102/0013189X12459803 | DOI 10.3102/0013189X12459803
[31] Mandinach, E. B., Parton, B. M., Gummer, E. S., & Anderson, R. (2015). Ethical and appropriate data use requires data literacy. Phi Delta Kappan, 96(5), 25–28. https://doi.org/10.1177/0031721715569465 | DOI 10.1177/0031721715569465
[32] Mann, S. (2016). The research interview: Reflective practice and reflexivity in research processes. PalgraveMacmillan. https://doi.org/10.1057/9781137353368 | DOI 10.1057/9781137353368
[33] Marsh, J. A., Pane, J. F., & Hamilton, L. S. (2006). Making sense of data-driven decision making in education: Evidence from Recent RAND Research (OP-170). RAND Corporation. https://doi.org/10.7249/OP170 | DOI 10.7249/OP170
[34] Maxwell, J. A. (2011). Epistemological heuristics for qualitative research. In H. Soini, E. L. Kronqvist, & G. L. Huber (Eds.), Epistemological heuristics for qualitative research (pp. 10–27). Center for Qualitative Psychology.
[35] Means, B., Padilla, C., DeBarger, A., & Bakia, M. (2009). Implementing data-informed decision making in schools—Teacher access, supports and use. Report prepared for U.S. Department of Education, Office of Planning, Evaluation and Policy Development. SRI International. https://files.eric.ed.gov/fulltext/ED504191.pdf
[36] Park, V., & Datnow, A. (2009). Co-constructing distributed leadership: district and school connections in data-driven decision-making, School Leadership & Management: Formerly School Organisation, 29(5), 477–494. https://doi.org/10.1080/13632430903162541 | DOI 10.1080/13632430903162541
[37] Pawson, R. (2006). Evidence-based policy: A realist perspective. SAGE.
[38] Phillips, J. (2003). Powerful learning: Creating learning communities in urban school reform. Journal of Curriculum and Supervision, 18(3), 240–258.
[39] Ponelis, S. R. (2015). Using interpretive qualitative case studies for exploratory research in doctoral studies: A case of Information Systems research in small and medium enterprises. International Journal of Doctoral Studies, 10, 535–550. | DOI 10.28945/2339
[40] Poortman, C. L., & Schildkamp, K. (2016). Solving student achievement problems with a data use intervention for teachers. Teaching and Teacher Education, 60, 425–433. https://doi.org/10.1016/j.tate.2016.06.010 | DOI 10.1016/j.tate.2016.06.010
[41] Robinson, V. M. J., & Walker J. C. (1999). Theoretical privilege and researchers' contribution to educational change. In J. S. Gaffney & B. J. Askew (Eds.), Stirring the waters: The influence of Marie Clay (pp. 239–259). Heinemann.
[42] Schildkamp, K., & Kuiper, W. (2010). Data-informed curriculum reform: Which data, what purposes, and promoting and hindering factors. Teaching and Teacher Education, 26(3), 482–496. https://doi.org/10.1016/j.tate.2009.06.007 | DOI 10.1016/j.tate.2009.06.007
[43] 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). Springer. https://doi.org/10.1007/978-94-007-4816-3_10 | DOI 10.1007/978-94-007-4816-3_10
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