Writing Built Environment Dissertations and Projects: practical guidance and examples

Writing Built Environment Dissertations and Projects will help you to write a good dissertation or project by giving you a good understanding of what should be included, and showing you how to use data collection and analysis tools in the course of your research. Addresses prominent weaknesses in under–graduate dissertations including weak data collection; superficial analysis and poor reliability and validity Includes many more in–depth examples making it easy to understand and assimilate the concepts presented Issues around study skills and ethics are embedded throughout the book and the many examples encourage you to consider the concepts of reliability and validity Second edition includes a new chapter on laboratory based research projects Supporting website with sample statistical calculations and additional examples from a wider range of built environment subjects  INDICE: Chapter 1: Introduction .1.1 Introduction .1.2 Terminology; nomenclature .1.3 Document structure .1.4 Possible subject areas for your research .1.5 Professional bodies and the non–technical or technical dissertation or project .1.6 Qualitative or quantitative analysis? .1.7 The student / supervisor relationship and time management .1.8 Ethical compliance and risk assessments .1.9 House style or style guide .1.10 Writing style .1.11 Proof–reading .1.12 Extra support? .1.13 A research proposal .Chapter 2: The introduction chapter to the dissertation or project .2.1 Introduction contents .2.2 Articulation or description of the problem and provisional objectives .Chapter 3: Review of theory and the literature .3.1 Introduction .3.2 Style and contents of a literature review .3.3 Judgements or opinions? .3.4 Sources of data .3.5 Methods of finding the literature .3.6 Embedding theory in dissertations and projects .3.7 Referencing as evidence of reading .3.8 Citing literature sources in the narrative of your work; cite in text .3.9 References or bibliography or both? .3.10 Common mistakes by students .3.11 Using software to help with your references .3.13 Avoiding the charge of plagiarism .Chapter 4: Research goals and their measurement .4.1 Introduction .4.2 Aim .4.3 Research questions .4.4 Objectives .4.5 Variables .4.6 A hypothesis with one variable .4.7 A hypothesis with two variables; independent and dependent variables (IVs and DVs) .4.8 Writing the hypothesis; nulls and tails.  A matter of semantics .4.9 Lots of variables at large, intervening variables .4.10 Ancillary or subject variables .4.11 No relationship between the IV and the DV .4.12 Designing measurement instruments; use authoritative tools and adapt the work or others .4.13 Levels of measurement .4.14 Examples of categorical or nominal data in construction .4.15 Examples of ordinal data in construction .4.16 Examples of interval and ratio data in construction .4.17 Types of data .4.18 Money as a variable .4.19 Three objectives, each with an IV and DV; four variables to measure .4.20 Summarising research goals; variables and their definition .Chapter 5: The Methodology chapter; analysis, results and findings .5.1 Introduction .5.2 Approaches to collecting data .5.3 Data measuring and collection .5.4 Issues mostly relevant to just questionnaires .5.5 Ranking studies .5.6 Other analytical tools .5.7 Incorporating reliability and validity .5.8 Analysis, results and findings .Chapter 6: Laboratory experiments .6.1 Introduction .6.2 Test methodology .6.3 Sourcing test materials .6.4 Reliability and validity of findings .6.5 Sample size .6.6 Laboratory recording procedures .6.7 Dissertation/project writing (Introduction, methodology and results) .6.8 Health and safety in the laboratory; COSHH and risk assessments .6.9 Role of the supervisor .6.10 Possible research topics for technical dissertations or projects, construction and civil engineering .6.11 Examples of research proposals .6.12 Research objectives and sample findings by the author .Chapter 7: Qualitative data analysis .7.1 Introduction .7.2 The process of qualitative data collection .7.3 Steps in the analytical process .Chapter 8: Quantitative data analysis; descriptive statistics .8.1 Introduction .8.2 Examples of use of descriptive statistical tools .8.3 Ancillary variables .8.4 Illustration of relevant descriptive statistics in charts .8.5 Normal distributions; Z scores .8.6 A second variable for descriptive analysis; an IV and a DV .Chapter 9: Quantitative data analysis; inferential statistics .9.1 Introduction .9.2 Probability values and three key tests: chi–square, difference in means and correlation .9.3 The chi–square test .9.4 Determining whether the data set is non–parametric or parametric .9.5 Difference in mean tests; the t test .9.6 Difference in means; the unrelated Mann–Whitney test .9.7 Difference in means; the related Wilcoxon t test .9.8 Difference in means; the parametric related t test .9.9 Correlations .9.10 Using correlation coefficients to measure internal reliability and validity in questionnaires .9.11 Which test? .9.12 Confidence intervals .9.13 Summarising results .Chapter 10: Discussion, conclusions, recommendations and appendices .10.1 Introduction .10.2 Discussion .10.3 Conclusions and recommendations .10.4 Appendices .10.5 The examiner s perspective .10.6 Summary of the dissertation or project process .Appendices

• ISBN: 978-1-118-92192-0
• Editorial: Wiley–Blackwell
• Encuadernacion: Rústica
• Páginas: 320
• Fecha Publicación: 03/06/2016
• Nº Volúmenes: 1
• Idioma: Inglés