Testing the effectiveness of an intervention model based on data use: a replication series across clusters of schools

Abstract

Intervention models based on data use can be effective in raising student achievement. This article presents 3 studies of one such model which had reported improved reading comprehension levels in 7 poor urban multicultural schools serving indigenous and ethnic minority communities. The intervention (the Learning Schools Model) used a process comprising critical discussions of achievement and teacher observation data to develop specific and contextualized content for fine-tune instruction. The reliability and generality of the effects of the model were tested in a cluster of “like” schools and a cluster of “unlike” schools. The growth models showed similar effects to the original schools, with gains of between 3 to 4 months additional progress per year over 3 years. The replications show that models that use data to design local program content can be reliably and generally effective, but also there is a need to examine differential effects.

Keywords:

• intervention
• replication
• reading comprehension

Acknowledgements

We wish to acknowledge the professional expertise and collaboration of the teachers and leaders in the three clusters. The support and contributions from their school communities including their Boards of Trustees is acknowledged also. Similarly, colleagues from the New Zealand Ministry of Education have been valued members of the collaboration and provided high-level policy and research-based contributions.

 The three research and development interventions received funding from the Teaching and Learning Research Initiative (New Zealand Council for Educational Research), the Woolf Fisher Trust, Development West Coast, and the New Zealand Ministry of Education.

Notes

1. Raw scores of the STAR test can be converted to 9-point normalized stanine scores based on New Zealand national norms (Elley, 2001).