Skip to main content

Writing a Built Environment Dissertation: Practical Guidance and Examples

Writing a Built Environment Dissertation: Practical Guidance and Examples

Peter Farrell

ISBN: 978-1-444-32867-7

Jan 2011, Wiley-Blackwell

280 pages

Select type: E-Book



As a built environment student you are likely to be required to research, write and submit a dissertation as a core component of your degree studies. As a vocational profession, students of the built environment often have strong practical aspirations. Writing a Built Environment Dissertation provides practical guidance and will help to steer you into a position where you can develop a good dissertation by mixing your practical strengths with more theoretical tools.

The book is ordered around a common dissertation structure: that is, it starts with material that should be in the introduction and finishes with material that should be in the conclusion. Each chapter provides a commentary on the kind of information that you should put in each chapter of your dissertation, supported by a variety of examples using a range of methodological designs. The book has a strong focus on data collection, data analysis, reliability and validity – all areas where student dissertations are often weak. Material that will help you think about study skills and ethics is embedded throughout the book, and the chapters on qualitative and quantitative analysis will show you how to carry out a rigorous analysis while avoiding some of the complexity in statistical work.

If you are an under-graduate student in the final year of an honours degree programme in the built environment, or perhaps a student at masters or PhD level and have been away from academic study for some time, then this book will help you to write a more innovative and thorough dissertation.

Related Resources


Contact your Rep for all inquiries

Author biography xi

Preface xiii

1 Introduction 1

1.1 Introduction 1

1.2 Terminology; nomenclature 2

1.3 Document structure 2

1.4 Possible subject areas for your dissertation 5

1.5 Qualitative or quantitative analysis? 6

1.6 The student/supervisor relationship and time management 9

1.7 Ethical compliance 11

1.8 House style or style guide 14

1.9 Writing style 15

1.10 Proofreading 18

Summary of this chapter 19

2 The introduction chapter to the dissertation 20

2.1 Introduction contents 20

2.2 Articulation or description of the problem and provisional objectives 21

Summary of this chapter 23

3 Review of theory and the literature 24

3.1 Introduction 24

3.2 Judgements or opinions? 27

3.3 Sources of data 28

3.4 Methods of finding the literature 29

3.5 Embedding theory in dissertations 30

3.6 Referencing as evidence of reading 34

3.7 Citing literature sources in the narrative of your work 35

3.8 Secondary citing 36

3.9 Who to cite in your narrative 37

3.10 References or bibliography or both? 38

3.11 Common mistakes by students 39

3.12 Using software to help with your references 40

3.13 Avoiding the charge of plagiarism 42

Summary of this chapter 45

4 Research goals and their measurement 46

4.1 Introduction 46

4.2 Aim 47

4.3 Research questions 48

4.4 Objectives 48

4.5 Objectives with only one variable 51

4.6 Objectives with two variables 51

4.7 Hypotheses 52

4.8 Independent and dependent variables 54

4.9 Lots of variables at large; intervening variables 57

4.10 Subject variables 59

Example 1 59

Example 2 61

4.11 No relationship between the IV and the DV 63

4.12 Designing your own measurement scales 63

4.13 Levels of measurement 67

4.14 Examples of categorical data in construction 68

4.15 Examples of ordinal data in construction 69

4.16 Examples of interval and ratio data in construction 71

4.17 Money as a variable 72

Summary of this chapter 74

5 Methodology 75

5.1 Introduction 75

5.2 Approaches to collecting data 77

5.3 Types of data 79

Primary or secondary data 79

Objective or subjective data; hard or soft 79

5.4 Questionnaires 82

Piloting the questionnaire 83

Coding questionnaires 84

A basket of questions to measure variables or multiple item scales 86

Using a basket of questions in ordinal closed-response scales 90

Other possible responses in ordinal closed-response scales 93

Ranking studies 93

5.5 Other analytical tools 95

5.6 Incorporating reliability and validity 96

5.7 Analysis, results and findings 99

Summary of this chapter 100

6 Qualitative data analysis 101

6.1 Introduction and the process 101

6.2 Steps in the analytical process 104

Summary of this chapter 111

7 Quantitative data analysis: descriptive statistics 112

7.1 Introduction 112

7.2 Glossary of symbols 113

7.3 Calculations done manually or by using software 114

7.4 Descriptive statistics 115

Ranking 121

Normal distributions: measures of central tendency (mean, median and mode) 121

Measures of spread: range, standard deviation, variance 124

Standard score: the Z score 127

Confidence intervals 128

General use of descriptive statistics 129

Summary of this chapter 131

8 Quantitative data analysis: inferential statistics 133

8.1 Introduction 133

8.2 Probability values 134

The p value of _ 0.05 135

Setting the significance level of p; alternatives to 0.05 136

8.3 The chi-square test 137

Assembling the raw data 139

Transferring raw data to the contingency table: stage 1 139

Are differences due to chance? manual calculations: p values and degrees of freedom 140

The consequence of larger sample size and different spread of numbers 143

More complex or more simple chi-square 144

8.4 Difference in mean tests: the ‘t’ test 146

Unrelated or related data 147

Determining whether the data set is parametric 148

Which difference in means test? 154

8.5 Difference in means: the unrelated Mann–Whitney test 157

Assembling the raw data 157

Are differences due to chance? Manual calculations: p values and degrees of freedom 159

The consequence of larger sample size and different spread of numbers 162

8.6 Difference in means: the related Wilcoxon test 162

8.7 Difference in means: the parametric related t test 165

8.8 Correlations 165

Are differences due to chance?; and the correlation coefficient 168

Manual calculations for Spearman’s Rho 169

The consequence of larger sample size and a wider spread of data 173

8.9 Difference in means, correlations or both? 176

8.10 Using correlation coefficients to measure internal reliability and validity 177

8.11 Summarising results 182

Summary of this chapter 182

9 Discussion, conclusions, recommendations and appendices 183

9.1 Introduction 183

9.2 Discussion 184

9.3 Conclusions and recommendations 185

9.4 Appendices 188

9.5 The examiner’s perspective 189

Initial overview 189

Review of literature 189

Design of study 189

Presentation of results 190

Discussion and conclusions 190

Summative overview 190

Summary of the dissertation process 190

Summary of this chapter 191

References 192

Bibliography 195

Appendices 196

Appendix A: research ethics checklist 197

Appendix B: narrative of a problem 198

Appendix C: a review of theory and literature 200

Introduction and the problem 200

The literature 201

Motivation 201

Social class 202

Appendix D: qualitative analysis 207

File 1: research objectives 207

File 2: interview questions and prompts 207

File 3: verbatim transcripts of interviews first copy 208

File 7: verbatim transcripts of interviews third copy; originating from file 4, person A only 224

File 9: a new file, comprising tables 231

File 10: the narrative 237

Appendix E: using Excel for charts, descriptive tests and inferential tests 240

Four charts 240

Frequency histograms 240

Line diagrams 240

Pie charts 241

Scatter diagrams 241

Eleven descriptive tests 243

The five inferential tests 245

Pearson’s chi-square test 245

Wilcoxon test, unrelated t-test and Mann–Whitney test 245

Pearson’s product moment correlation test—two routes both giving the same answer 247

Appendix F: the standard normal distribution table 249

Appendix G: chi-square table 250

Appendix H: Mann–Whitney table, p = 0.05 251

Appendix I: Mann–Whitney table, p = 0.01 252

Appendix J: Wilcoxon table 253

Appendix K: related t test table 254

Appendix L: Spearman’s rho table 255

Appendix M: Pearson’s r table 256

Appendix N: F distribution 257

Index 259

"Although there are significant differences between the UK and US educational models, students at the university level in either system can benefit from Farrell's suggestions and examples for dissertation writing." (Book News, 1 March 2011)


  • Addresses three prominent weaknesses in under-graduate dissertations: poor data collection; analysis that is superficial and lacking rigour; poor reliability and validity
  • Supported by a variety of in-depth examples so that the student can easily understand and assimilate the concepts presented
  • Draws on research methods used in other disciplines and applies them to built environment research so that students can be more innovative and rigorous in their work