Dissertation Studies

1. Dissertation Studies Data Collection Methods

2. Outline • Choosing your participants • Qualitative collection methods • Interviews • Focus groups • Quantitative collection methods • questionnaires

3. Choosing your Participants • relevance or convenience methods • usually associated with qualitative methods but can be applied to surveys or evaluations of programmes • probability methods • usually associated with experimental and survey methods

4. Choosing your Participants-relevance methods • It is the relevance to the research topic rather than their representativeness which determines the way in which the people/subjects are chosen • convenience (haphazard) • get any participants in any manner that is convenient • person on the street interviews of media

5. Choosing your Participants-relevance methods • quota • get a pre-set number of participants in each of several pre-determined categories that will reflect the diversity of the population. • snowball • get cases using referrals form one or a few participants, and then referrals from those people…and so on • extreme/deviant case • get participants that substantially differ from the dominant pattern

6. Choosing your Participants-relevance methods • theoretical • (sometimes called purposive sampling) • Get participants that will help reveal features that are theoretically important about a particular setting / topic • establish criteria for selection of participants • certain knowledge • certain experiences

7. Choosing your Participants-relevance methods • Number of participants? • depends on: • research purpose • type of data analysis • on population characteristics • number is far less important than sampling method • saturation sampling • keep selecting / interviewing data/ participants until no new information occurs

8. Choosing your Participants-probability sampling • Everyone in your population has an equal chance of being selected • simple random • create a sample frame for all cases, then select cases using a purely random process • pull names out of a hat • allocate random numbers to cases • sample frame is a list of all possible participants

9. Choosing your Participants-probability sampling • stratified • you may wish to ensure a balance of particular traits (gender or age etc.) • divide (stratify) your sampling frame into groups according to your traits • draw a random sample from each of the subgroups then combine the samples

10. John • Peter • Toni • Rebecca • Amanda • Vicky • Andrew • Robert • Bart

11. John Male Peter Peter Toni Andrew Rebecca Robert Amanda Bart Vicky Females Andrew Toni Robert Rebecca Bart Amanda Vicky

12. John Male Peter Peter Toni Andrew RebeccaRobert AmandaBart Vicky Females Andrew Toni Robert Rebecca Bart Amanda Vicky 2 Males randomly 2 Females 4 Random

13. Choosing your Participants-probability sampling • systematic • create a sampling frame • specify the total number of cases required. • divide the sampling frame by the no. of cases • choose a random starting place, select every Xth case

14. 1. a programme has 100 students • 2. you wish to select 10% e.g. 10 • 3. select every 10th student

15. Choosing your Participants-probability sampling • Cluster • identify sub groups (clusters) of your population (usually geographical) • create a list (a sampling frame) of the clusters • randomly select an agreed number of clusters • create a sampling frame for each selected cluster • select a random sample from within each cluster

17. 1 2 3 4

18. suppose you were undertaking a satisfaction survey for a university library • you need to cluster your sampling • time of day • day of week • quota for each sample period

19. Mon Tues Wed Thurs Fri Sat Sun 7-9 9-12 12-2 2-5 5-7 7-10

20. Sample Size • depends on: • research purpose • type of data analysis • on population characteristics • size is far less important than sampling method. • the larger the population the smaller sampling ratio is required (95% confidence)

21. Sampling

22. response rate • 0-20% Your project has not succeeded - unless representativeness doesn’t matter or somehow it is so homogeneous that a tiny sample is still representative • 20-40%Too low - unless there are reasons. You must account for the low rate - it may represent too strong a bias • 40-60%Bearable - but again you must account • 60-80%You can relax. As a formality: account for the non response • 80-100%Good …but still account for non responses

24. Questionnaires • A questionnaire is a set of standardised questions for gathering the same information from a group of individuals • Aim • To make comments about the group • To generalise from the group to a wider population • You can administer questionnaires by: • Mail • Telephone • Face-to-face interviews • Hand-outs • Electronically (e-mail or through Web-based questionnaires).

25. Purpose & types • Advantages • researcher doesn’t need to be present (low cost) • structured, often numerical data • relatively straightforward to analyse • Disadvantages • time consuming to develop, pilot and refine (high cost) • limited scope of data (no visual cues) • elicits inflexible responses (Wilson and McLean, 1994 in Cohen, Manion and Morrison, 2000)

26. Purpose & types • Descriptive • The descriptive survey is designed to find out the extent of a particular phenomena within a population • Typically descriptive surveys seek to determine 'how many' participate in a certain behaviour or hold a particular opinion • Need to ensure the sample and sample size are representative • Analytical • The analytic relational survey is set up specifically to explore associations between particular concepts • It is less orientated towards representativeness and more towards finding associations and explanations • It is more than often used in theory-building/testing research therefore statistically staple sample sizes are more important (Oppenheim, 2000)

27. Levels of measurement • we classify information from questions using numbers and we can do this with varying amounts of precision. This process is called level of measurement and partly determines what statistical processes can be carried out • nominal type questions (lowest) • ordinal type questions • interval type questions • ratio type questions (highest)

28. Basic statistical approaches • Category / Discrete • nominal • Ordered • ordinal • Continuous • interval • ratio description of a particular phenomena associations of particular behaviours and conditions differences between certain sub-groups or conditions relationships between variables prediction of variables modelling of relationships

29. Levels of measurement • in nominal measurement the numerical values just "name" the attribute uniquely. No ordering of the cases is implied. • Jersey numbers in basketball are measures at the nominal level. A player with number 30 is not more of anything than a player with number 15, and is certainly not twice whatever number 15 is. • Subject specialism of teachers in a secondary school, no implication of value of one subject over another is made.

30. Levels of measurement • in ordinal measurement the attributes can be rank-ordered. Here, distances between attributes do not have any meaning. • for example, on a survey you might code highest level of educational attainment using the national qualifications framework: • level 1 (5+ GCSE passes), 2 (5+GCSE A*-C), 3 (A-level/IB), 4 (HND, foundation degree), 5 (degree) • In this measure, higher numbers mean more education. But is distance from 1 to 2 same as 4 to 5? The interval between values is not interpretable in an ordinal measure.

31. Levels of measurement • in interval measurement the difference between the attributes have meaning on a numerical scale and are equal, but zero is not an absence of that attribute. • for example in the Celsius (centigrade) temperature scale we know that the change from 5 to 10 C is the same as a change from 15 to 20 C. But 20 C is not twice as hot as 10 C.

32. Levels of measurement • in ratio measurement there is always an absolute zero that is meaningful. This means that you can construct a meaningful fraction (or ratio) with a ratio variable. Weight is a ratio variable. • In applied social research most "count" variables are ratio, for example, the number of clients in past six months. It is possible to have zero clients and it is meaningful to say that "...we had twice as many clients in the past six months as we did in the previous six months."

33. Basic statistical approaches • Category / Discrete • nominal • Ordered • ordinal • Continuous • interval • ratio description of a particular phenomena associations of particular behaviours and conditions differences between certain sub-groups or conditions relationships between variables prediction of variables modelling of relationships

34. Question formats • Open question [write whatever you want] Please use the space below to tell us about your peanut butter experiences.

35. Question formats • Open question [write what one wants] What brand of peanut butter do you use? _________________

36. Question formats • Nominal-type Questions • forced choice Do you like peanut butter? o Yes o No

37. Question formats • Nominal-type Questions • inventory Which brands of peanut butter do you like? Kraft o Sunbeamo Daffodil o Nature’s Owno Tesco’s finesto

38. Question formats • Ordinal-type Questions • ranking Please rank the following brands of peanut butter Kraft o Sunbeamo Daffodil o Nature’s Owno Tesco’s finesto

39. Question formats • Interval-type Questions • (scales) To me peanut butter is the best food in the world strongly agree agree disagree strongly disagree I think I would die if I didn’t have peanut butter Agree 1 2 3 4 5 disagree

40. Question formats • Ratio-type Questions • (behaviour/frequency) • Please indict how times a week you would have a peanut butter sandwich _______________ • How many times a day do you dream of peanut butter ____________________

41. Response formats- Likert Scale To me peanut butter is the best food in the world strongly-agree agree disagree strongly-disagree I think I would die if I didn’t have peanut butter disagree 1 2 3 4 5 agree

42. Response format- Likert Scale • respondents indicate the extent of their agreement or disagreement with a statement • usually 5 / 7 / 9 options provided Problems • too many options confuse the respondent • what does the middle position represent • response set • Which direction? (increasing/decreasing?) • General rule of thumb… 5 or 7 options

43. Single or multiple Questions To what extent are you satisfied with peanut butter Very Unsatisfied Very Satisfied 1 2 3 4 5 To what extent are you satisfied with the following aspects of peanut butter Satisfaction with the colour 1 2 3 4 5 Satisfaction with taste 1 2 3 4 5 Satisfaction with the texture 1 2 3 4 5 Satisfaction with the aroma 1 2 3 4 5 Satisfaction with packaging 1 2 3 4 5

44. Pre-published questionnaires? • Advantages • Less time • Proven set of items • Reliability / Validity tested • Clarity of directions • Potential for benchmark comparisons • Prior data analysis framework • Disadvantages • Cost • Items may not fit your research question (s) • Inappropriate norms for your group (e.g. US vs. UK)

45. Develop my own questionnaire? • Advantages • Relevant set of items • Involvement of stakeholders • Low(er) Cost • Data analysis control • Control over report format • Disadvantages • Time consuming- development of items, formatting, printing, check reliability & validity, etc.) • Unknown reliability/validity • Have to consider length of questionnaire carefully • Greater risk of poorly worded items

46. Tips • Length • Keep questions short < 25 words • Phone questionnaires should be no longer than 10 minutes • Face to face questionnaires < 30 minutes • Self-administered questionnaires < 4 - A4 • Web-based questionnaires shouldn't require participants to have to take multiple steps to answer each question.

47. Tips • Language • Use simple everyday language ( accessible, readability, validation process) • What particular aspects of the current positivistic debate would you like to see reflected in the developmental psychology course • Avoid irritating questions • Have you ever attended an in-service course of any kind during your entire teaching career?

48. Tips • Language • Avoid loaded questions that suggests to the respondent there is only one acceptable answer • Do you prefer abstract, academic courses or down-to earth practical courses useful to your day-to-day life? • Avoid double-barrelled questions • Vocational education is only available to the lower ability students but it should be open to every student

49. Tips • Order • No hard and fast rules • Be logical in the sequence • Avoid developing a ‘response-set’ • Start with easy, move to harder questions • Early questions may inform later questions • Put least important questions last • Be sensitive to fatigue