Writing built environment dissertations and projects : practical guidance and examples

Description

Title Page Copyright Page Contents Author biographies Preface About the companion website 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 1.5.1 The difference between non-technical and technical 1.6 Qualitative or quantitative analysis? 1.7 The student/supervisor relationship and time management 1.8 Ethical compliance and risk assessments 1.8.1 Physical or emotional harm; laboratory risk assessments 1.8.2 Confidentiality and anonymity 1.8.3 Generally 1.9 House style or style guide 1.10 Writing style 1.11 Proofreading 1.12 Extra support? 1.13 A research proposal 1.14 A viva or viva voce Summary References 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 Summary of this chapter References 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 3.8.1 Verbatim citations 3.8.2 Paraphrasing 3.8.3 Secondary citing 3.8.4 Who to cite in your narrative 3.8.5 Page numbers and emphasising the authority of the source 3.9 References or bibliography or both? 3.10 Common mistakes by students 3.11 Using software to help with references 3.12 Avoiding the charge of plagiarism Summary of this chapter References Chapter 4 Research goals and their measurement 4.1 Introduction 4.2 Aim 4.3 Research questions 4.4 Objectives 4.4.1 Objectives that ‘wobble’ 4.4.2 The literature review as an objective? 4.4.3 Objectives that do not match was has been done 4.5 Variables 4.6 A hypothesis with one variable 4.7 A hypothesis with two variables: independent and dependent 4.7.1 Which is the IV and which the DV? Variables ‘melting’ into each other 4.7.2 Manipulation or observation variables in research? 4.7.3 A relationship, not a cause: strength of relationships 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 of others 4.12.1 Variable values with high or low numbers as best? 4.12.2 Measurement scales of 0–10 and 0–100; multiple-item scales 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 4.17.1 Primary or secondary data 4.17.2 Objective or subjective data: hard or soft 4.17.3 Using subjective data since objective data is too difficult to secure 4.18 Money and CO2 as variables 4.19 Three objectives, each with an IV and DV: four variables to measure 4.20 Summarising research goals; variables and their definition Summary of this chapter References Chapter 5 The Methodology chapter; analysis, results and findings 5.1 Introduction 5.2 Approaches to collecting data 5.3 Data measuring and collection 5.3.1 Populations and samples 5.3.2 Single and multiple-item scales 5.3.3 How many response points on each Likert item? Words, numbers or both? Weighting 5.4 Issues mostly relevant to just questionnaires 5.4.1 Introduction 5.4.2 Administration 5.4.3 Piloting the questionnaire 5.4.4 Statements or questions 5.4.5 Alternating poles on statements and questions 5.4.6 Things to do and not to do in questionnaires 5.5 Ranking studies 5.6 Other analytical tools 5.7 Incorporating reliability and validity 5.8 Analysis, results and findings Summary of this chapter References 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) 6.7.1 Conclusions 6.7.2 Literature references and citations 6.7.3 Appendices 6.8 Health and safety in the laboratory; COSHH and risk assessments 6.8.1 Health and safety induction 6.8.2 Housekeeping 6.8.3 Health questionnaire for students 6.8.4 Example of risk assessment for laboratory work 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 6.12.1 Comparative performance of fibre reinforced polymer (FRP) and steel rebar 6.12.2 Equating steel and synthetic fibre concrete post crack performance to BS EN 14651:2005+A1:2007 6.12.3 Concrete with crushed, graded and washed recycled construction demolition waste as a coarse aggregate replacement 6.12.4 Surface coating of traditional construction materials using microbially induced calcite precipitation 6.12.5 Pull-out performance of chemical anchor bolts in fibre concrete Bibliography Chapter 7 Qualitative data analysis 7.1 Introduction 7.2 The process of qualitative data collection 7.3 Steps in the analytical process Summary of this chapter References Chapter 8 Quantitative data analysis; descriptive statistics 8.1 Introduction 8.2 Examples of the use of descriptive statistical tools 8.2.1 Calculation of the descriptive statistics without a spreadsheet and their definitions; missing and treated data 8.2.2 Calculation of the descriptive statistics with a spreadsheet 8.3 Ancillary variables 8.4 Illustration of relevant descriptive statistics in charts 8.5 Normal distributions; Z scores 8.5.1 Normal distributions 8.5.2 The Z score; standard score 8.6 A second variable for descriptive analysis; an IV and a DV Summary of this chapter References 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 9.2.1 The p value of ≤ 0.05 9.2.2 Setting the significance level of p; alternatives to 0.05 9.3 The chi-square test 9.3.1 Chi-square by Excel 9.3.2 The consequence of a different spread of numbers and sample size 9.3.3 More complex chi-square 9.3.4 More simple one row chi-square 9.4 Determining whether the dataset is parametric or non-parametric 9.4.1 How calculation procedures in parametric and non-parametric tests are different. 9.5 Difference in mean tests; the t-test 9.5.1 Unrelated or related data 9.6 Difference in means; the unrelated Mann–Whitney test 9.6.1 Mann–Whitney by Excel 9.6.2 Frequency histogram of mean scores 9.6.3 The consequence of larger sample size 9.7 Difference in means; the related Wilcoxon t-test 9.7.1 Wilcoxon test by Excel 9.7.2 Frequency histogram of mean scores 9.8 Difference in means; the parametric related t-test 9.9 Correlations 9.9.1 The scatter diagram 9.9.2 The correlation coefficient and its p value 9.9.3 Longhand calculation for Spearman’s rho 9.9.4 Correlation test by Excel 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 Summary of this chapter References 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 Summary of this chapter References List of appendices Appendix A: Glossary to demystify research terms Appendix B: Research ethics and health and safety examples Appendix C: An abstract, problem description and literature review Appendix D: Eight research proposals Appendix E: Raw data for a qualitative study Appendix F: Statistical tables Index EULA