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IB Psychology Research Methods Review
Terms in this set (17)
Numerical, Objective, Deductive data
Rich, thick, textural data. More subjective than quantitative data. Inductive.
Strengths of Qualitative data
Real life setting, not created in a laboratory. It can help to generate new ideas and theories and is more effective for exploring sensitive issues. Explains phenomena in a great amount of detail not available with quantitative research.
Limitations of Qualitative Data
It creates a large amount of data, meaning it is time consuming and possibly expensive to analyse. There is also the possibility of this data being too subjective, although this can be overcome using techniques such as reflexivity and triangulation.
Generalising in Qualitative Research.
It is often not possible to generalise all of this data as the sample can be too small (e.g. in a case study). The aim of qualitative data is not always to generalise, this is more the aim of quantitative research. The aim in to explore one particular phenomena in detail.
Sampling in qualitative research
Purposive Sampling: Based on a particular criteria the researcher has in mind.
Snowball Sampling: The researcher will use already gathered participants to find other possible candidates for the research.
Convenience Sampling: They use whoever they can get. (this type of sampling has the most limitations associated with it)
The participants create an idea or an 'expectation' of what they think the research will be about and then alter their behaviour. REACTIVITY and SOCIAL DESIRABILITY fit under this umbrella.
The researcher influencing the results of the research with their own motivations, beliefs etc. either intentionally or unintentionally.
Types of reflexivity
Personal: 'Personal Reflection', personal reflexivity involves the researcher reflecting on how their own views and values have influenced the research, and how the research also has influenced them.
Epistemological: Reflecting on how the data and knowledge has been collected, and then the implications of said collected data.
Types of Triangulation
Researcher Triangulation: Using different researchers to collect the data, in order to reduce the bias due to misinterpretation of the research.
Types of interviews.
Semi-Structured: A guide is used, including themes to be explored. However, the researcher can ask for more detail and clarification about a question if need be. This type of interview is useful in socially sensitive issues, however it can cause issues if not enough time is allocated to a specific theme.
Focus Group: A group of around 6-10 people, lead by a facilitator who asks questions and leads discussion (with prepared prompts).
Narrative: An interviewer does not prompt questions but instead the interviewee tells a story or 'narrative'. It is an interpretation of a particular situation by a particular person, and the end result is a mixture of facts and interpretations.
Considerations before an interview
Selection of data collection method and creation of an interview guide.
Choosing the right interviewer and training them.
Sampling method; Purposive, snowball, convenience?
Data recording method: (S&L: note-taking? Filming?)
Transcription or recorded data: Verbatim (word-by-word) or Post-Modern (includes body language and laughter, etc.)
Considerations during an interview
Active, neutral listening (No making concerned/happy gestures at particular responses)
Professional approach (allowing participant to leave etc.)
Considerations after an interview
Credibility check (checking interpretations of data inc. analysis)
Making sure there is consent to use ALL data.
Process of Inductive Content Analysis
CREDIBILITY CHECKS MUST OCCUR THE ENTIRE WAY THROUGH THE INDUCTIVE CONTENT ANALYSIS PROCESS
1. Interview is transcribed
2. Interview is read/reread and annotated
3. High-order and low-order themes are obtained and recorded.
4. Summary table including evidence is created.
5. Interpretation and conclusion is drawn.
Participants do not know they are being observed.
Participants know they are being observed.
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