Suchergebnisse

Cover -- Half Title -- Dedication -- Title Page -- Copyright Page -- Contents -- Figures and tables -- Preface -- Acknowledgements -- List of abbreviations -- Part One: Introducing the research -- Introduction -- The research questions -- The organisation of the book -- 1 Markets in education -- Introduction -- Choice in education -- Problems with marketisation -- The limitations of rational decision-making -- Conclusion -- 2 The prevailing evidence -- Introduction -- Who chooses? -- The process of choice -- The reasons for choice -- Conclusion -- 3 The need for a fresh approach -- Introduction -- Quantitative or qualitative research? -- Problems of sampling -- Instrument design -- Ethnostatistics -- Problems with qualitative analysis -- Conclusion -- 4 The sampling frame -- Introduction -- State provision -- Fee-paying schools as an established market -- Explanations for the size of the fee-paying sector -- Conclusions -- Part Two: Researching the established market -- 5 Outline methodology -- Introduction -- The pilot study -- The sample -- The questionnaires -- The analysis of the results -- The quality of the survey -- Thicker" data -- Conclusion -- 6 The schools and their users -- Introduction -- The seven types of schools -- The focus schools themselves -- The market and the right image -- The respondents and their schools -- Families and types of schools -- Conclusion -- 7 The choice criteria -- Introduction -- The process of choice -- Ratings of the reasons for choice -- Relationships between the reasons for choice -- Seven factors underlying the reasons for choice -- Conclusion -- Part Three: The process of choice -- 8 Family influences on choice -- Introduction -- The reflection effect -- The domino effect -- Conclusion -- 9 The three step model -- Introduction -- Different roles in the choice process -- Three steps to choosing a school

"Research design is of critical importance in social research, despite its relative neglect in many methods resources. Early consideration of design in relation to research questions leads to the elimination or diminution of threats to eventual research claims, by encouraging internal validity and substantially reducing the number of alternative explanations for any finite number of research 'observations'. This new book: discusses the nature of design; gives an introduction to design notation; offers a flexible approach to new designs; looks at a range of standard design models; and presents craft tips for real-life problems and compromises. Most importantly, it provides the rationale for preferring one design over another within any given context. Each section is illustrated with case studies of real work and concludes with suggested readings and topics for discussion in seminars and workshops, making it an ideal textbook for postgraduate research methods courses. Based on the author's teaching on the ESRC Doctoral Training Centre "Masters in Research Methods" at the University of Birmingham, and his ongoing work for the ESRC Researcher Development Initiative, this is an essential text for postgraduate researchers and academics. There is no book like Research Design on the market that addresses all of these issues in an easy to comprehend style, for those who want to design research and make critical judgements about the designs of others."--Publisher's website.

Based on the views of teenagers across Europe and in the Far East, this book argues that we need to reconsider how we judge schools and what they are for. It shows that the treatment of pupils in schools makes more difference to teenagers' views on society, and on what it means to be fair, than it does to differences in attainment

This paper is a discussion of the challenges to equity faced by the education and training systems of the 28 EU countries (at time of writing), based on secondary sources and official reports by individual countries. The data are descriptive and simply summarised for this paper. The systems of all countries are fairly similar, modelled on those set up to deal with challenges of early industrialisation, and all now face several similar problems and opportunities. There is a clear correlation between family background, average attainment, and subsequent participation in education and training. All 28 countries show some signs of progress over time, both in terms of the absolute level of attainment, and in terms of reduced gaps between social and economic groups. These trends are historical, and thus hard to link to specific policies. However, looking at the common characteristics of countries with similar levels of equity can produce a tentative guide to its determinants. Some of the main suggestions are: More countries to set up monitoring systems for school intakes and outcomes; more robust evaluations of policy interventions; fair funding and opportunities for all students; extra funding for students facing challenges; no selection by ability or anything else; all taught in mainstream settings; no tracking or grade retention; more recognition of prior experience and learning; respectful interaction with all students; and use of context when allocating places in higher education, or simply more open access.

This paper is a brief reply to two responses to a paper I published previously in this journal. In that first paper I presented a summary of part of the long-standing literature critical of the use of significance testing in real-life research, and reported again on how significance testing is abused, leading to invalid and therefore potentially damaging research outcomes. I illustrated and explained the inverse logic error that is routinely used in significance testing, and argued that all of this should now cease. Although clearly disagreeing with me, neither of the responses to my paper addressed these issues head on. One focussed mainly on arguing with things I had not said (such as that there are no other problems in social science). The other tried to argue either that the inverse logic error is not prevalent, or that there is some other unspecified way of presenting the results of significance testing that does not involve this error. This reply paper summarises my original points, deals with each response paper in turn, and then turns to an examination of how the responders use significance testing in practice in their own studies. All of them use significance testing exactly as I described in the original paper – with non-random cases, and using the probability of the observed data erroneously as though it were the probability of the hypothesis assumed in order to calculate the probability of the observed data.

This paper reminds readers of the absurdity of statistical significance testing, despite its continued widespread use as a supposed method for analysing numeric data. There have been complaints about the poor quality of research employing significance tests for a hundred years, and repeated calls for researchers to stop using and reporting them. There have even been attempted bans. Many thousands of papers have now been written, in all areas of research, explaining why significance tests do not work. There are too many for all to be cited here. This paper summarises the logical problems as described in over 100 of these prior pieces. It then presents a series of demonstrations showing that significance tests do not work in practice. In fact, they are more likely to produce the wrong answer than a right one. The confused use of significance testing has practical and damaging consequences for people's lives. Ending the use of significance tests is a pressing ethical issue for research. Anyone knowing the problems, as described over one hundred years, who continues to teach, use or publish significance tests is acting unethically, and knowingly risking the damage that ensues.