Is engaging in evidence-informed practice in education rational? What accounts for discrepancies in teachers' attitudes towards evidence use and actual instances of evidence use in schools?
Brown, C. and Zhang, Dell (2016) Is engaging in evidence-informed practice in education rational? What accounts for discrepancies in teachers' attitudes towards evidence use and actual instances of evidence use in schools? British Educational Research Journal 42 (5), pp. 780-801. ISSN 0141-1926.
Abstract
Whilst beneficial, the consistent and regular use of evidence to improve teaching and learning in schools is proving difficult to achieve in practice. This paper attempts to shed new light on this issue by examining the applicability of a model of rational behaviour as it relates to the notion of evidence-informed practice (EIP). Specifically, exploring the question: ‘if EIP is rational behavior, why aren't all teachers engaged in it?’, we examine whether the beliefs and perspectives of teachers in relation to EIP, align with their evidence-use behaviours. We then assess what factors (if any) prevent teachers/schools who wish to engage in EIP from doing so. To examine beliefs, instances of, and barriers to evidence use, we employ a Gradient Boosted Tree predictive model to analyse data from a survey of 696 practitioners in 79 schools. Our findings suggest that, should they wish to increase EIP within their schools, school leaders need to: 1) promote the vision for evidence-use (i.e. actively encourage its use); 2) illustrate how research and evidence can be effectively employed to enhance aspects of teaching and learning; and 3) establish effective learning environments, in which learning conversations around the use of evidence, can flourish. Simultaneously we caution that evidence use will never be fully or meaningfully realised unless school leaders prioritise EIP as a school commitment. Simultaneously, it is unlikely that such prioritisation will occur until EIP forms part of any education system's accountability regime.
Metadata
Item Type: | Article |
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School: | Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences |
Research Centres and Institutes: | Data Analytics, Birkbeck Institute for |
Depositing User: | Administrator |
Date Deposited: | 09 Mar 2017 15:00 |
Last Modified: | 09 Aug 2023 12:41 |
URI: | https://eprints.bbk.ac.uk/id/eprint/17721 |
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