research methods Flashcards

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1
Q

what is an interview?

A

asking questions in real time and analysing answers after
- information gained directly from participants

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2
Q

define ‘researcher effect’

A

the influence of the interviewer directly on the respondent
- eg being rude

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3
Q

define ‘researcher bias’

A

interpretation of response by the interviewer

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4
Q

define ‘response bias’

A

the tendency of a participant to respond in a particular way

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5
Q

describe the characteristics of an interview

A
  • mostly open questions, generating qualitative data
  • smaller data sets lower generalisability
  • relevant questions are used and recorded/transcribed which increases reliability
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6
Q

describe a structured interview

A
  • standardised questions asked in same order
  • often used in job candidate screening
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7
Q

what are strengths of a structured interview?

A
  • high response rate
  • quick
  • comparable
  • high reliability
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8
Q

what are weaknesses of a structured interview?

A
  • less detail
  • can lack validity
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9
Q

what is a semi structured interview?

A

guide of topics but phrasing and timing is up to the interviewer
used in clinical interviews

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10
Q

what is a strength of a semi structured interview?

A
  • detailed
  • flexible
  • generates rich, easy to analyse data
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11
Q

what are weaknesses of semi structured interviews?

A
  • could have irrelevant data
  • lack reliability
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12
Q

what is an unstructured interview?

A

everyday conversation without pre determined questions

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13
Q

what are strengths of unstructured interviews?

A
  • deeper discussion
  • questions can be adapted and improvised to improve relevancy
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14
Q

what are weaknesses of unstructured interviews?

A
  • low reliability
  • time consuming
  • less objective
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15
Q

what is a questionnaire?

A

a self report technique which investigates beliefs and opinions through pre determined questions where respondents record their own answers

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16
Q

what is an open question?

A

no fixed response
generates qualitative data

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17
Q

what is a closed question?

A

fixed response
generates quantitative data

18
Q

what is a strength and weakness of qual data?

A
  • more detailed evaluation
  • hard to find averages
19
Q

what is a strength and weakness of quant data?

A
  • easy to analyse
  • extraneous variables not considered
20
Q

what is a ranked scale?

A
  • respondents assess views on 1-5 scale
  • objective
  • quantitative data
  • easy to draw conclusions
21
Q

what is a likert scale?

A
  • respondent rates how much they agree
  • quantitative data
  • allows for degrees of opinion or no opinion
22
Q

what are characteristics of a good questionnaire?

A
  • no leading / confusing questions
  • open and closed questions
  • avoid lists that are long or asking 2 diff things in one question = reduces fatigue
  • start with interesting questions
  • check / test to see if it works
23
Q

what are strengths of questionnaires?

A
  • large sample
  • flexible, quick and efficient
  • cost effective
  • anonymous = more valid response and reduces social desirability
  • standardised procedures = reliable
24
Q

what are weaknesses of questionnaires

A
  • risk of social desirability to appear favourable
  • poor response rate = unrepresentative
  • leading qs / researcher bias could flaw results
  • written at 11 year old level = age limited
25
Q

strength of quantitative data

A
  • quick and easy
  • large sample
  • high generalisability
  • objective and numerical
  • can be easily replicated
26
Q

weaknesses of quantitative data

A
  • gathered in questionnaires could be subjective so low validity
  • numerical data lacks detail which is unrepresentative of humans complex behaviour
  • reductionist - narrows down to one aspect
27
Q

what is thematic analysis?

A

A method that analyses qualitative data by finding patterns and themes within a data set.

28
Q

why is thematic analysis used?

A
  • It allows for flexibility in what the researcher wants to find with specification on any theory
  • Can be used to analyse transcripts, secondary data, media, etc
  • rich detailed data
29
Q

Define ‘data corpus’.

A

A large collection of qualitative data texts being analysed for research.

30
Q

Define ‘data set’.

A

A collection of related sets of qualitative data that is composed of separate elements but can be analysed as a whole.

31
Q

Give an example of a data set in social psychology.

A

All the answers to an open question in a single questionnaire about obedience.

32
Q

List the 6 stages of thematic analysis.

A

1) Familiarisation with the data
2) Coding
3) Searching for themes
4) Reviewing themes
5) Defining and naming themes
6) Producing the report

33
Q

describe ‘familiarisation with data’

A
  • Read through the data corpus
  • If it is audio data, transcribe it
  • Note any initial analytical observations
34
Q

describe ‘coding

A
  • Initial codes of labels using words or short phrases to identify important features of the data
  • It can be done manually or with a software program
  • Highlighting or post-it notes are a good way to indicate the origin of codes
  • Code as many potential themes as possible
  • All the data identified under the same code should be collated
35
Q

describe ‘searching for themes’

A
  • Sort all the codes into broader patterns of meaning of themes
  • Mind maps and tables are a good way to sort the codes
  • Some codes may form main themes or sub-themes, or even get discarded
36
Q

describe ‘reviewing themes’

A
  • Refining themes by combining or splitting or discarding on a mind map
  • The themes should have a relationship and form a coherent pattern, if it doesn’t then the issue may be with the theme itself or the arrangement of data
  • The themes should reflect the data corpus as a whole and the aim of the research
37
Q

describe ‘defining themes’

A
  • Each theme should be have a concise name and definition to immediately identify the ‘essence’ of each theme
  • The researcher should conduct a detailed analysis on each theme (e.g. how the theme fits with the data as a whole)
  • An overall narrative of the data will be formed with a final thematic map
38
Q

describe ‘finalising report’

A
  • Final analysis and writing the report
  • The audience must be considered to allow for coherent and appropriate language (e.g. writing for a scientific journal or a newspaper)
  • Evidence for each theme should be provided
39
Q

3 strengths of thematic analysis.

A
  • High inter-rater reliability - two researchers can both code the same data corpus to reach an agreement and remove subjectivity
  • High test-retest reliability - due to the standardised procedure of finding codes and collating them into themes it can be easily replicated for other data sets
  • High validity - qualitative data is rich and detailed that can provide insight into the respondent
40
Q

3 weaknesses of thematic analysis.

A
  • Low generalisability - it can get time consuming to replicate this procedure on every open question in a questionnaire and so the sample size may be low to account for this
  • Low validity - the different codes and themes may not fully reflect what the data was trying to get across and so is open to misinterpretation by the researcher
  • Low validity - the data corpus is qualitative and so open to interpretation when identifying codes and themes therefore has an element of researcher bias