Writing Built Environment Dissertations and Projects

Peter Farrell is a Reader in Construction Management at the University of Bolton, UK, and programme leader for the university�s MSc in Construction Project Management. Fred Sherratt is a Senior Lecturer in Construction Management at Anglia Ruskin University, UK. Alan Richardson is a Reader in Civil Engineering at Northumbria University, UK and programme leader for the BEng in Civil Engineering.

• Author biographies ixPreface xAbout the companion website xii1 Introduction 11.1 Introduction 11.2 Terminology; nomenclature 21.3 Document structure 31.4 Possible subject areas for your research 71.5 Professional bodies and the non]technical or technical dissertation or project 81.6 Qualitative or quantitative analysis? 101.7 The student/supervisor relationship and time management 141.8 Ethical compliance and risk assessments 171.9 House style or style guide 221.10 Writing style 231.11 Proofreading 271.12 Extra support? 291.13 A research proposal 291.14 A viva or viva voce 30Summary 31References 312 The introduction chapter to the dissertation or project 332.1 Introduction contents 332.2 Articulation or description of the problem and provisional objectives 35Summary of this chapter 37References 383 Review of theory and the literature 393.1 Introduction 393.2 Style and contents of a literature review 413.3 Judgements or opinions? 433.4 Sources of data 443.5 Methods of finding the literature 483.6 Embedding theory in dissertations and projects 493.7 Referencing as evidence of reading 533.8 Citing literature sources in the narrative of your work 543.9 References or bibliography or both? 583.10 Common mistakes by students 593.11 Using software to help with references 603.12 Avoiding the charge of plagiarism 62Summary of this chapter 64References 644 Research goals and their measurement 674.1 Introduction 684.2 Aim 704.3 Research questions 714.4 Objectives 714.5 Variables 744.6 A hypothesis with one variable 754.7 A hypothesis with two variables: independent and dependent 774.8 Writing the hypothesis: nulls and tails – a matter of semantics 814.9 ‘Lots’ of variables at large, intervening variables 834.10 Ancillary or subject variables 834.11 No relationship between the IV and the DV 884.12 Designing measurement instruments; use authoritative tools and adapt the work of others 894.13 Levels of measurement 934.14 Examples of categorical or nominal data in construction 954.15 Examples of ordinal data in construction 964.16 Examples of interval and ratio data in construction 974.17 Types of data 984.18 Money and CO2 as variables 1024.19 Three objectives, each with an IV and DV: four variables to measure 1034.20 Summarising research goals; variables and their definition 104Summary of this chapter 105References 1055 The Methodology chapter; analysis, results and findings 1075.1 Introduction 1075.2 Approaches to collecting data 1105.3 Data measuring and collection 1125.4 Issues mostly relevant to just questionnaires 1205.5 Ranking studies 1295.6 Other analytical tools 1315.7 Incorporating reliability and validity 1325.8 Analysis, results and findings 137Summary of this chapter 138References 1396 Laboratory experiments 1406.1 Introduction 1416.2 Test methodology 1426.3 Sourcing test materials 1436.4 Reliability and validity of findings 1436.5 Sample size 1456.6 Laboratory recording procedures 1456.7 Dissertation/project writing (introduction, methodology and results) 1466.8 Health and safety in the laboratory; COSHH and risk assessments 1496.9 Role of the supervisor 1516.10 Possible research topics for technical dissertations or projects, construction and civil engineering 1536.11 Examples of research proposals 1536.12 Research objectives and sample findings by the author 154Bibliography 1637 Qualitative data analysis 1657.1 Introduction 1657.2 The process of qualitative data collection 1667.3 Steps in the analytical process 168Summary of this chapter 175References 1768 Quantitative data analysis; descriptive statistics 1778.1 Introduction 1778.2 Examples of the use of descriptive statistical tools 1788.3 Ancillary variables 1868.4 Illustration of relevant descriptive statistics in charts 1908.5 Normal distributions; Z scores 1918.6 A second variable for descriptive analysis; an IV and a DV 197Summary of this chapter 201References 2029 Quantitative data analysis; inferential statistics 2039.1 Introduction 2049.2 Probability values and three key tests: chi]square, difference in means and correlation 2069.3 The chi]square test 2109.4 Determining whether the dataset is parametric or non]parametric 2209.5 Difference in mean tests; the t]test 2239.6 Difference in means; the unrelated Mann–Whitney test 2259.7 Difference in means; the related Wilcoxon t]test 2309.8 Difference in means; the parametric related t]test 2329.9 Correlations 2369.10 Using correlation coefficients to measure internal reliability and validity in questionnaires 2439.11 Which test? 2439.12 Confidence intervals 2479.13 Summarising results 250Summary of this chapter 250References 25010 Discussion, conclusions, recommendations and appendices 25110.1 Introduction 25110.2 Discussion 25210.3 Conclusions and recommendations 25310.4 Appendices 25510.5 The examiner’s perspective 25610.6 Summary of the dissertation or project process 258Summary of this chapter 259References 259List of appendices 260Appendix A: Glossary to demystify research terms 261Appendix B: Research ethics and health and safety examples 268Appendix C: An abstract, problem description and literature review 272Appendix D: Eight research proposals 279Appendix E: Raw data for a qualitative study 309Appendix F: Statistical tables 340Index 350