The Dissertation

Topics Covered Structure Length Key Issues How to Present Key Types of Research

Interviews Surveys Experimentation Statistics

Dissertation Structure

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

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

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)

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

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

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.

Interviews

The Interview

Interviewer Interviewee

Interview

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?

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.

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

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

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

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

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

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.

Kvale’s Seven Stages

1. Themazing2. Designing3. Interviewing4. Transcribing5. Analyzing6. Verifying7. Reporting

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

Questionnaires/SurveysA.N. Oppenheim, Questionnaire Design

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).

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.

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

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

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?"

Questionnaires Likert scales

Poor, Weak, O.K., Good, Excellent Very Low, Low, O.K., High, Very High 1, 2, 3, 4, 5

Descriptive and Inferential Statistics

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

Examples

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).

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

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 ordered in relation to being 'more' or 'less' of the concept in question. E.g. age ranges 16-20 etc.