research methods + data analysis (w9) Flashcards

1
Q

does qualitative approach use inductive or deductive reasoning, how/why

A

inductive (data –> theory) (specific –> general)
starts with specific examples, analyses to generate theory

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2
Q

does quantitative approach use inductive or deductive reasoning, how/why

A

deductive (theory –> data) (general –> specific)
starts with a theory, tests via specific examples to prove or disprove theory

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3
Q

what things constitute quality in qualitative research

A

validity, reliability, trustworthiness - dependability, confirmability, credibility, transferability

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4
Q

what does dependability mean

A

showing that the findings are consistent and could be repeated

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5
Q

what does confirmability mean

A

a degree of neutrality or the extent to which the findings of a study are shaped by the respondents and not researcher bias, motivation or interest

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6
Q

what does credibility mean

A

confidence in the truth of the findings

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7
Q

what does transferability mean

A

showing that the findings have applicability in other contexts

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8
Q

types of qualitative research approaches

A

phenomenology, ethnography, grounded theory

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9
Q

what is the research purpose for phenomenology and its disciplinary origin

A

describe one or more individuals’ experiences of a phenomenon, philosophy

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10
Q

what is the research purpose for ethnography and its disciplinary origin

A

describe cultural characteristics of a group of people, anthropology

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11
Q

what is the research purpose for grounded theory and its disciplinary origin

A

inductively generate a grounded theory describing and explaining a phenomenon, sociology

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12
Q

what is the primary data collection method for phenomenology

A

in depth interviews

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13
Q

what is the primary data collection method for ethnography

A

participant observation over an extended period of time, interviews with informants

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14
Q

what is the primary data collection method for grounded theory

A

interviews, observations

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15
Q

what is data analysis like for phenomenology

A

list significant statements, determine meaning of statements and identify essence of the phenomenon

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16
Q

what is data analysis like for ethnography

A

holistic description and search for cultural themes in the data

17
Q

what is data analysis like for grounded theory

A

begin with open coding, then axial coding and end with selective coding

18
Q

what is the report like for phenomenology

A

rich description of the essential characteristics of the experience

19
Q

what is the report like for ethnography

A

rich description of context and cultural themes

20
Q

what is the report like for grounded theory

A

description of topic and people studied, presentation of the theory

21
Q

types of interview

A

individual, group, structured, semi structured, unstructured, open Qs, closed Qs, biographical, clinical, ethnographical, face to face, telephone, computer assisted

22
Q

strengths of interviewing

A

extensive personalisation/interaction, extensive opportunities to ask Qs, possible to ‘probe’, good ‘rate of return’, flexible

23
Q

limitations of interviewing

A

labour intensive, costly, not extensive, subjectivities in interpretation and analysis (?), limited reliability, memory decay (?)

24
Q

what to think about when designing interview guide

A

what are you asking people Qs, why are you asking these people, what do you want to ask (identify key Qs), how do you plan to ask them (open, closed, scales)

25
questions to avoid in interviews
double Qs, long complex Qs, Qs involving technical terms, leading/biased Qs, ambiguous Qs, invasion of privacy
26
what must a good interviewer do
have listening skills, make Qs straightforward, clear, non-threatening, non-verbal communication, eliminate cues that lead them to respond in a certain way, don't look bored
27
stages of qualitative analysis
data reduction: coding, discarding irrelevant data, on going throughout research data display draw conclusions from mass of data conclusion drawing/verifications validity examined through references to your existing field notes and critical discussions with tutors
28
ways of analysing qualitative data
ethnographic analysis, structured analysis, content analysis, axial coding and constant comparison, inductive and deductive analytical procedures, post-structuralism approach, feminist approach
29
what is data structure
words, phrases, paragraphs, connections, patterns, sequences
30
what is coding for qualitative data
the organisation of raw data in conceptual categories, each code is effectively a category - first stage of providing some form of logical structure to data
31
what are codes for qualitative data
tags or label for assigning units of meaning to descriptive information compiled during a study, codes are attached to chunks of words or phrases, sentences or whole paragraphs
32
stages of data coding
statements relating to research Q identified and assigned a code - category reread transcripts - search for statement that fit into categories further codes might be developed - axial coding more analytical - look for patterns and explanations
33
questions to consider
to what extent does my sample allow generalisation, what did I do that produced these findings, what was left out, why, what/who doesn't fit, what's missing, what's surprising
34
what's the hierarchy of themes
transcripts > raw data themes > lower order themes > main themes > dimensions
35
aspects of data trustworthiness
confirmability (objectivity) : link with raw data themes-list of emerged themes dependability (reliability) : triangulation of transcripts and themes credibility (internal validity) : pilot study, member checking transferability (external validity) : demographic characteristics, specific settings