The trials of evidence-based education : the promises, opportunities and problems of trials in education

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書誌事項

The trials of evidence-based education : the promises, opportunities and problems of trials in education

Stephen Gorard, Beng Huat See and Nadia Siddiqui

Routledge, 2017

  • pbk

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注記

Includes bibliographical references (pages [175]-198) and index

内容説明・目次

内容説明

The Trials of Evidence-based Education explores the promise, limitations and achievements of evidence-based policy and practice, as the attention of funders moves from a sole focus on attainment outcomes to political concern about character-building and wider educational impacts. Providing a detailed look at the pros, cons and areas for improvement in evidence-based policy and practice, this book includes consideration of the following: What is involved in a robust evaluation for education. The issues in conducting trials and how to assess the trustworthiness of research findings. New methods for the design, conduct, analysis and use of evidence from trials and examining their implications. What policy-makers, head teachers and practitioners can learn from the evidence to inform practice. In this well-structured and thoughtful text, the results and implications of over 20 studies conducted by the authors are combined with a much larger number of studies from their systematic reviews, and the implications are spelled out for the research community, policy-makers, schools wanting to run their own evaluations, and for practitioners using evidence.

目次

1. Introduction: the state of education research 2. The changing incentives and infrastructure for robust evaluations 3. Problems, abuses and limitations in the conduct of trials 4. Assessing the trustworthiness of a research finding 5. In-depth evidence and process evaluations 6. A short sharp shock?: the transition to secondary school 7. What works for catch-up literacy and numeracy? 8. More of the same or radical changes to the way we teach? 9. Educating the whole person or just a cheap way to improve results? 10. What are the lessons for those concerned with robust evaluations?

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