Other Qualitative approaches Flashcards
What are the other approaches to qualitative research?
other qualitative approaches include: Interpretative phenomenological analysis content analysis discourse analysis grounded theory
What does IPA stand for?
IPA stands for interpretative phenomenological analysis, it is a qualitative approach that focuses on understanding a person’s experiences and perceptions. Interpretative phenomenological analysis has a inductive idiographic approach as it focuses on individuals experiences and perceptions.
What type of approach does Interpretative phenomenological analysis have?
IPA or interpretative phenomenological analysis has a inductive idiographic approach as it focuses on understanding a person’s experiences and perceptions.
What does Interpretative phenomenological analysis focus on?
Interpretative phenomenological analysis focuses on understanding individuals experiences and perceptions because it has an inductive idiographic approach.
What is IPA interested in?
IPA or interpretative phenomenological analysis is interested in how an individual makes sense or understands an event or experience in a given context.
What does IPA try to find?
Interpretative phenomenological analysis tries to find common features in an event among different interviews.
How would you describe IPA?
Interpretative phenomenological analysis is subjective as it focuses on individuals experiences and perceptions.
What is the sample like in IPA?
The sample in Interpretative phenomenological analysis is a small sample size and it contains homogeneous individuals to understand an experience that means the sample includes similar individuals.
What is the data like in IPA?
The data in interpretative phenomenological analysis includes interviews or observations. probes are used for participants to elaborate. In interpretative phenomenological analysis an analytical method is used which means we go and back and forward with the data. IPA provides detailed account of a person’s experiences and perceptions
What does IPA provide?
interpretative phenomenological analysis is a qualitative approach that provides a detailed account of a person’s lived experiences. IPA is an inductive idiographic approach and tries to identify common features in an event. IPA tries to understand how a person makes sense or understand an experience in a given context.
Definition of content analysis.
content analysis places importance to the number of occurrences of things or themes.
What are the types of content analysis?
there are two types of content analysis including qualitative content analysis and quantitative content analysis.
quantitative content analysis = apply categories and count number of times they are used in a text. Frequencies are applied. Quantitative content analysis is not open to interpretation.
qualitative content analysis = comes up with a coding scheme.
What does quantitative content analysis use?
quantitative content analysis uses frequencies. Quantitative content analysis works by applying categories and counting number of times they occur in a text. Then frequencies are applied. quantitative content analysis is not as open to interpretation.
How do you do quantitative content analysis?
quantitative content analysis uses frequencies. It works by applying categories and counting number of times they occur in a text. Then frequencies are applied. Quantitative content analysis is not open to interpretation.
What does qualitative content analysis use?
qualitative content analysis uses a coding scheme.
How do you do qualitative content analysis?
Qualitative content analysis comes up with a coding scheme.
What is the difference between qualitative content analysis and quantitative content analysis?
The difference between quantitative content analysis and qualitative content analysis is that quantitative content analysis is not open to interpretation but qualitative content analysis is open to interpretation.
Why is content analysis useful?
content analysis is useful because it gives us a broad understanding of a topic. It is also useful for a large amount of data.
What is the sample like in content analysis?
The sample size in content analysis is big. so content analysis is useful for analysing large amount of data.
What is the data like in content analysis?
you can use content analysis for survey, newspaper, text and image.
How do you analyse content analysis?
Content analysis is analysed by coding for qualitative research. It is important data is coded by two different people. Also, coding must be consistent between and within coders.
What is important when coding in content analysis?
When coding in content analysis it is important for two different people to code the data. Also, coding must remain consistent between and within coders.
Definition of discourse analysis.
Discourse analysis believe that language and words are meaningless but we give them meaning.
What does discourse analysis believe?
Discourse analysis believe that words and language and meaningless but we give them meaning.
Also, discourse analysis believes that individuals use language to present themselves.
What is the research question about in discourse analysis?
Research question in discourse analysis is about how our identity, knowledge and meaning is constructed through our use of language.
What is the sample like in discourse analysis?
sample size can vary in discourse analysis but the sample uses different types of people to understand variation across people and context.
What type of people are used in discourse analysis sample?
In discourse analysis, the sample size varies but different types of people are used in each sample to understand variation.
What type of data is used in discourse analysis?
Discourse analysis believe that words and language are meaningless but we give them meaning. It believes that individuals use language to present themselves. The sample size may vary but different types of people are used in the sample to understand variation. Research question in discourse analysis is about how our identity, knowledge and meaning is constructed through the use of language. in discourse analysis, we do coding but the coding is focused on language. The type of data in discourse analysis include interviews, observations, analysis of text.
What does discourse analysis believe in terms of language?
Discourse analysis believe that language is meaningless and that we give it meaning. Research question in discourse analysis is about how our identity, knowledge and meaning is constructed through the use of language. In the sample, the sample size may vary but different types of people may be used each sample to understand variation. Discourse analysis believe that people use language to present themselves. Coding is used in discourse analysis but the coding is focused on language. The type of data that is used in discourse analysis include interviews, observations and analysis of text.
Definition of grounded theory.
Grounded theory is based in sociological roots. Grounded theory is about how we as social beings, interact and behave.
what is grounded theory based on?
Grounded theory is based in sociological roots - it is about how we as social beings interact and behaviour.
What is the aim of the grounded theory?
The aim of grounded theory is to generate a theory.
What are the 6 c’s of social processes?
The 6 c’s of social processes include:
- cause
- context
- consequence
- condition
- contingencies
- covariance
What do you observe in grounded theory?
In grounded theory, you observe speech patterns and behaviour.
How does grounded theory work?
Grounded theory is an inductive process so data driven. Firstly, look at each individual case then identify patterns in the data in order to generate a theory.
What should the data be like for grounded theory?
In grounded theory, data is rich and thick so we collect a lot of information from participants.
What is the sample like in grounded theory?
In grounded theory, we use theoretical sampling which is a way of reviewing data to find gaps in the data and including new needed information by adding new participants or modifying interview.
Definition of theoretical sampling.
Theoretical sampling is reviewing the data and finding gaps in the data to include new needed information by recruiting new participants or modifying interview.
What does grounded theory use?
Grounded theory uses theoretical sampling and saturation. Theoretical sampling is a way of reviewing data to find gaps in the data and including new needed information by modifying interview or adding new information. Also, grounded theory uses saturation which is when you keep analysing information until you find nothing new. This means that grounded theory generates a lot of data. Grounded theory does constant comparision which means identifying patterns in data by checking for similarities and differences in the data and constantly comparing through the data. In grounded theory, the researcher constantly checks and rechecks for consistency.
Definition of saturation.
Saturation means you keep analysing until you find nothing new. the aim of grounded theory is to reach saturation so grounded theory generates a lot of data and it can be time consuming.
How much data does grounded theory generate?
The aim of grounded theory is to reach saturation which means you keep analysing until you don’t find anything new so grounded theory generates a lot of data and this can be very time consuming.
What is coding like in grounded theory?
coding in grounded theory is based on sociology.
What do you do when you carry out grounded theory?
In grounded theory, you do constant comparison which helps to identify patterns in data, by looking for similarities and differences in data and constantly comparing throughout data. also, research constantly checks and rechecks data for consistency.
What is the research question in grounded theory?
The research question in grounded theory is about how social processes and social structures are achieved by social interactions. In the research question, we have to think of the 6 c’s of social processes including context, cause, condition, consequence, contingencies, covariance.
