Writing a Built Environment Dissertation : Practical Guidance and Examples

Preface.

1 Introduction.

1.1 Introduction.

1.2 Terminology; nomenclature.

1.3 Document structure.

1.4 Possible subject areas for your dissertation.

1.5 Qualitative or quantitative analysis?

1.6 The student/supervisor relationship and time management.

1.7 Ethical compliance.

1.8 House style or style guide.

1.9 Writing style.

1.10 Proofreading.

2 The introduction chapter to the dissertation.

2.1 Introduction contents.

2.2 Articulation or description of the problem and provisional objectives.

3 Review of theory and the literature.

3.1 Introduction.

3.2 Judgements or opinions?

3.3 Sources of data.

3.4 Methods of finding the literature.

3.5 Embedding theory in dissertations.

3.6 Referencing as evidence of reading.

3.7 Citing literature sources in the narrative of your work.

3.8 Secondary citing.

3.9 Who to cite in your narrative.

3.10 References or bibliography or both?

3.11 Common mistakes by students.

3.12 Using software to help with your references.

3.13 Avoiding the charge of plagiarism.

4 Research goals and their measurement.

4.1 Introduction.

4.2 Aim.

4.3 Research questions.

4.4 Objectives.

4.5 Objectives with only one variable.

4.6 Objectives with two variables.

4.7 Hypotheses.

4.8 Independent and dependent variables.

4.9 Lots of variables at large; intervening variables.

4.10 Subject variables.

4.11 No relationship between the IV and the DV.

4.12 Designing your own measurement scales.

4.13 Levels of measurement.

4.14 Examples of categorical data in construction.

4.15 Examples of ordinal data in construction.

4.16 Examples of interval and ratio data in construction.

4.17 Money as a variable.

5 Methodology.

5.1 Introduction.

5.2 Approaches to collecting data.

5.3 Types of data.

Primary or secondary data.

Objective or subjective data; hard or soft.

5.4 Questionnaires.

Piloting the questionnaire.

Coding questionnaires.

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

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

Other possible responses in ordinal closed-response scales.

Ranking studies.

5.5 Other analytical tools.

5.6 Incorporating reliability and validity.

5.7 Analysis, results and findings.

6 Qualitative data analysis.

6.1 Introduction and the process.

6.2 Steps in the analytical process.

7 Quantitative data analysis: descriptive statistics.

7.1 Introduction.

7.2 Glossary of symbols.

7.3 Calculations done manually or by using software.

7.4 Descriptive statistics.

Ranking.

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

Measures of spread: range, standard deviation, variance.

Standard score: the Z score.

Confidence intervals.

General use of descriptive statistics.

8 Quantitative data analysis: inferential statistics.

8.1 Introduction.

8.2 Probability values.

8.3 The chi-square test.

Assembling the raw data.

Transferring raw data to the contingency table: stage 1.

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

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

More complex or more simple chi-square.

8.4 Difference in mean tests: the 't'test.

Unrelated or related data.

Determining whether the data set is parametric.

Which difference in means test?

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

Assembling the raw data.

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

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

8.6 Difference in means: the related Wilcoxon test.

8.7 Difference in means: the parametric related t test.

8.8 Correlations.

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

Manual calculations for Spearman's Rho.

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

8.9 Difference in means, correlations or both?

8.10 Using correlation coefficients to measure internal reliability and validity.

8.11 Summarising results.

9 Discussion, conclusions, recommendations and appendices.

9.1 Introduction.

9.2 Discussion.

9.3 Conclusions and recommendations.

9.4 Appendices.

9.5 The examiner's perspective.

Initial overview.

Review of literature.

Design of study.

Presentation of results.

Discussion and conclusions.

Summative overview.

Summary of the dissertation process.

Summary of this chapter.

References.

Bibliography.

Appendices.

Appendix A: research ethics checklist.

Appendix B: narrative of a problem.

Appendix C: a review of theory and literature.

Introduction and the problem.

The literature.

Motivation.

Social class.

Appendix D: qualitative analysis.

File 1: research objectives.

File 2: interview questions and prompts.

File 3: verbatim transcripts of interviews first copy.

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

File 9: a new file, comprising tables.

File 10: the narrative.

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

Four charts.

Frequency histograms.

Line diagrams.

Pie charts.

Scatter diagrams.

Eleven descriptive tests.

The five inferential tests.

Pearson's chi-square test.

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

Pearson's product moment correlation test—two routes both giving the same answer.

Appendix F: the standard normal distribution table.

Appendix G: chi-square table.

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

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

Appendix J: Wilcoxon table.

Appendix K: related t test table.

Appendix L: Spearman's rho table.

Appendix M: Pearson's r table.

Appendix N: F distribution.

Index.

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