The Dissertation

1. The Dissertation

2. Topics Covered • Structure • Length • Key Issues • How to Present Key Types of Research • Interviews • Surveys • Experimentation • Statistics

3. Dissertation Structure

4. Dissertation Overview • For all details related to dissertation layout, templates, deadlines, checklists etc. • http://www.comp.dit.ie/btierney/MScDissertations/index.html • Aim for 100 pages

5. Dissertation Structure • Title • Abstract • Table of Contents • Table of Figures • Table of Tables • Introduction (starts at page 1) • Literature Review (can be separate chapters) • Your Design • Your Findings • Your Evaluation • Conclusion and Future Work

6. Introduction • Aim is to introduce the reader to • The project • Its background • Justification that the project is viable • Your project aims • You project objectives • Your research approach • Any scope or limitations • Overview of the rest of the dissertation • 10-15 pages (approx. 10% of the dissertation)

7. Background/Literature Review • Aim is to provide the reader with your insight into the body of literature • Introduce key terms, definitions, ideas, thought leaders • Provide critical analysis of existing approaches, techniques etc. • Identify key ideas, themes, issues or directions that informed your approach • Set the scene for why you will be doing things the way you will do things for your project • 20-25 pages (approx. 20- 25% of the dissertation) • Can be split into multiple chapters

8. Your Project = 60% of the dissertation • Generally you need a chapter for each of the following: • Design/Formulation of proposed experimentation/implementation • Should be clear how the literature reviewed has influenced design • Should be clear why research approach is suitable • Experimentation/Implementation • Should align with proposed approach • Should discuss clearly any deviation/adjustments needed with justification • Analysis of your findings • Should honestly discuss the outcome of your experimentation • Should draw conclusions about your work

9. Conclusion and Future work • Approx. 10% of dissertation • Should mirror your introduction • Should address how well you have addressed the aim and objectives • Should assess where and how well your work aligns with existing research • Should discuss scope and limitations • Should provide detail about potential future work • To build on your experimentation • Alternates to your experimentation • Other avenues in which your work can be applied • Etc.

10. Interviews

11. The Interview Interviewer Interviewee Interview

12. Issues to be Discussed – Interview Design • Justification for use as a tool • Relate back to qualitative research • Relate to your project • State clearly • Interview Aims • Interview Objectives • Relationship to project • Choice of Interviewees (audience, sample) • Profile • Skills • Justification of suitability • Make transparent any constraints • Question design • Each question should address certain objectives • Outline clearly this relationship • Think clearly about the question wording • Is it suitable for your interviewees? • Is it suitable to elicit the knowledge you need?

13. Issues to be Discussed – Interview Execution • Who • Profile, how many etc. • When • Dates, times, duration • Where • Location, surroundings, anything that influenced • How • How long, one to one, recorded, over Skype etc. • What • Exactly what happened, any issues – hesitancy, lack of understanding of questions, additional questions, suggestions etc. • Why • For all the above why were things done in this way, why did certain things happen etc.

14. Issues to be Discussed – Interview Findings • Transcribe your interviews • You need to include the transcription • Not within the main dissertation but as an appendix • Can be included on a CD • Analyse your data • Summarise, organise and extract meaning from interview transcripts • Coding • Identify Major Themes • Align to aims and objectives • Of interview • Of project • To literature • Present summary statistics • Draw Conclusions • Determine key issues to be addressed • Identify recommendations • Be aware of bias • Make it transparent • Validate findings and conclusions • Expose to some interviewees • Look for independent verification – literature, other research tools used • Review and revise conclusions to ensure that they are reliable and valid

15. Bias What is bias? All views of reality are filtered. Bias only exists in relation to some reference point. Types of bias: Motivational bias Interviewee makes accommodations to please the interviewer or some other audience Observational bias Limitations on our ability to accurately observe the world Cognitive bias Mistakes in use of statistics, estimation, memory, etc. Notational bias Terms used to describe a problem may affect our understanding of it

16. Examples • Social pressure • response to verbal and non-verbal cues from interviewer • Group think • response to reactions of other experts • Impression management • response to imagined reactions of managers, clients,… • Wishful thinking • response to hopes or possible gains • Appropriation • selective interpretation to support current beliefs • Misrepresentation • expert cannot accurately fit a response into the requested response mode • Anchoring • contradictory data ignored once initial solution is available • Inconsistency • assumptions made earlier are forgotten • Availability • some data are easier to recall than others • Underestimation of uncertainty • tendency to underestimate by a factor of 2 or 3

17. Terminology • Theme • a topic that organizes a group of repeating ideas. • usually developed during focused coding, but may emerge during literature supported by interview findings • E.g. from analysis of interviewee responses, it emerged that that employees are reluctant to use the Wiki as they view the contents as out of date and stagnant. • Making conclusions/recommendation • a determination of what is working well and what needs to be improved based on repeating ideas and themes.  • Themes and repeating ideas should guide you in recommending or making improvements.   • E.g. in response to the view of the Wiki as stagnant and out of date, the project will introduce social media tools alongside the Wiki to encourage more informal knowledge sharing

18. Issues to be Discussed – Interview Findings • Report repeating ideas/issues • Repeated by a number of interviewees • Report meaningful responses • Those that most exemplify issues or support recommendations • Quantify these • How many people said this? • How many disagreed? • Why are they best situated to comment? • Include quotes • Present Graphically • Organise themes and conclusions into tables or trees • Demonstrate relationships

19. Interviews • Unstructured interview • Free flowing, used in early stages of elicitation/research, can produce basics of knowledge domain, basically broad chat • Semi-structured interview • Main technique • Pre-defined questions sent to expert prior to interview, supplementary questions asked at interview. Can be used as part of validation. • Structured interview • Pre-defined set of questions, can simply be filling in a questionnaire at the interview.

20. Kvale’s Seven Stages • Themazing • Designing • Interviewing • Transcribing • Analyzing • Verifying • Reporting

21. Interview Questions • Introductory Questions • Warm up questions • Followup Questions • Listen for “Red Lights” • Probing Questions • Unlimited scope question • Specifying Questions • Exact information • Direct Questions • Introducing a new topic • Indirect Questions • Projective questions • Structuring Questions • Transitioning to new topics • Interpreting Question • Clarifying questions • Silences

22. Questionnaires/Surveys A.N. Oppenheim, Questionnaire Design

23. Issues to be Discussed –Design • Justification for use as a tool • Relate back to qualitative research • Relate to your project • State clearly • Aims • Objectives • Relationship to project • Choice of audience • Profile • Skills • Justification of suitability • Size of sample • Explain distribution mechanism • Make transparent any constraints • Question design • Each question should address certain objectives • Outline clearly this relationship • Think clearly about the question wording • Is it suitable for your interviewees? • Is it suitable to elicit the knowledge you need? • Think clearly about the question design • Multi-choice, open text etc. • Justify • How long will it table to complete? • Check your grammar, twice (Rule of Thumb – two proofreads gets rid of 95% of errors).

24. Issues to be Discussed • Who • Profile, how many targeted, how many responses etc. • When • Dates, times, duration • Where • Geographic location • How • Email, paper etc. • What • Exactly what happened, any issues –omissions, lack of understanding of questions, additional questions, suggestions etc. • Why • For all the above why were things done in this way, why did certain things happen etc.

25. Issues to be Discussed – Survey Findings • Collate your findings • You need to include the collated responses • Not within the main dissertation but as an appendix • Can be included on a CD • Report summarised responses • Analyse your data • Summarise, organise and extract meaning from responses • Coding • Identify Major Themes • Align to aims and objectives • Of interview • Of project • To literature • Present summary statistics for survey overall • Draw Conclusions • Determine key issues to be addressed • Identify recommendations • Be aware of bias • Make it transparent • Validate findings and conclusions • Look for independent verification – literature, other research tools used • Review and revise conclusions to ensure that they are reliable and valid

26. Issues to be Discussed – Survey Findings • Present summary statistics for question responses (for key questions) • Report repeating ideas/issues • Report meaningful responses • Those that most exemplify issues or support recommendations • Quantify these • How many people said this? • How many disagreed? • Why are they best situated to comment? • Include quotes • Present Graphically • Present outcomes of key questions or question groupings as charts or diagrams • Organise themes and conclusions into tables or trees • Demonstrate relationships

27. Questionnaires • Keep questions short and simple • Avoid questions with “not” • Avoid questions with bias • Avoid sensitive questions (ask indirectly) • Do not ask compound questions, just ask one question at a time • e.g. "Do you know what services are available to you and how to find out?"

28. Questionnaires • Likert scales • Poor, Weak, O.K., Good, Excellent • Very Low, Low, O.K., High, Very High • 1, 2, 3, 4, 5

29. Descriptive and Inferential Statistics

30. Measure of Central Tendency • Central position of a frequency distribution for a group of data • Possible measures: mode, median, and mean. • Mean: The arithmetic average of a group of scores; the sum of the scores divided by the number of scores. • Median The middle score of a sequence of all the scores in a distribution arranged from lowest to highest. • Mode The value with the greatest frequency on the distribution

31. Examples

32. Measures of spread • Ways of summarizing a group of data by describing how spread out the results/findings • Normal Curve: A specific, mathematically defined, bell-shaped frequency distribution that is symmetrical and unimodal; • Normal Distribution: A frequency distribution following a normal curve. • Skewness: The extent to which the majority of cases in a frequency distribution fall to one side of the middle. • Inter-quartile range: The range of the middle 50 per cent of all scores in a distribution when arranged from lowest to highest. • Standard Deviation: A measure of the degree to which scores in a distribution vary from the mean. • Variance Another measure of the degree to which scores in a distribution vary from the mean (equal to the standard deviation squared).

33. Way to Present Data • Interval or Ratio Variables • Mean and Standard Deviation (if approximately normally distributed) • Median and Interquartile Range (if skewed and thus not normally distributed) • Histograms • Boxplots • Stem-and-Leaf Displays • Interval variable: A variable with actual values rather than categories e.g. salary • Ration variable: As with interval variable but with added characteristic that there is a true zero value e.g. age

34. Way to Present Data • Ordinal or Nominal • Mode and/or simple frequencies • Barcharts • Piecharts • Tables • Nominal variable: A variable that consists of two • or more categories. E.g. male or female • Ordinal variable: A variable that consists of categories that can be rank orderedin relation to being 'more' or 'less' of the concept in question. E.g. age ranges 16-20 etc.