Abstract
In New Zealand, there is evidence that analysing data in teams can lead to improvements in student achievement. In this country, data discussions in professional learning communities were an important component of research and development interventions in three clusters of schools (n = 48 schools). These interventions significantly improved student achievement over 3 years, and these achievement gains were sustained after the interventions. In this chapter, the authors focus on a central feature of these data discussions, understanding classroom instruction in relation to student achievement patterns. The importance of inter-dependence between schools and external experts, greater pedagogical content knowledge to link classroom instruction to achievement results and the creation and use of school artefacts (e.g., data analysis reports) to facilitate effective data use are also discussed.
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Notes
- 1.
A fictional school.
- 2.
In our publications, we use several statistical models of varying complexities depending on the manuscript focus. The models used here takes into account growth over the summer holidays as well as during the academic years (see Lai et al. 2009a, for a description of the statistical model).
- 3.
Syndicate teams comprise teachers and leaders that teach 2–3 year levels in the school (e.g. teachers of year levels 4–6 in the school).
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We wish to acknowledge the support received through the New Zealand Council for Educational Research ‘Teaching, Learning and Research Initiative’ projects on sustainability and improving literacy, and the Ministry of Education.
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Lai, M., McNaughton, S. (2013). Analysis and Discussion of Classroom and Achievement Data to Raise Student Achievement. 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_3
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