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.
Autorentext
Dr Peter Farrell, MSc, FRICS, FCIOB, FRSA, is Senior Lecturer in the Department of the Built Environment at the University of Bolton. He is the programme leader for the MSc in Construction Management and has taught research methods to undergraduate and postgraduate students for over ten years. He also delivers modules in construction management and commercial management. His industry training was in planning and quantity surveying, whilst most of his post-qualification work was as a contractor's site manager.
Zusammenfassung
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.
Inhalt
Author biography.
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 r…