Qualitative Research Method Flashcards
(12 cards)
What is qualitative research?
Qualitative research involves collecting and analyzing non-numerical data(eg text, video or audio) to understand concepts, opinions or experiences. It can be used to gather in-depth insights into a problem or generate new ideas for research.
What are some features of qualitative research?
● Qualitative research explores meanings, experiences, and social phenomena.
● Focuses on understanding rather than quantifying data.
● Used in business research to study customer behavior, organizational culture, leadership styles, etc.
● Key Characteristics:Subjective and interpretive. Uses open-ended questions. Data collected through interaction (interviews, focus groups, etc.)
What are the advantages of Qualitative research?
● Flexibility
The data collection and analysis process can be adapted as new ideas or patterns emerge. They are not rigidly decided beforehand.
● Natural settings
Data collection occurs in real-world contexts or in naturalistic ways.
● Meaningful insights
Detailed descriptions of people’s experiences, feelings and perceptions can be used in designing, testing or improving systems or products.
● Generation of new ideas
Open-ended responses mean that researchers can uncover novel problems or opportunities that they wouldn’t have thought of otherwise.
What are the disadvantages of qualitative research?
● Unreliability
The real world setting often makes qualitative research unreliable because of uncontrolled factors that affect the data.
● Subjectivity
Due to the researcher’s primary role in analyzing and interpreting data, qualitative research cannot be replicated. The researcher decides what is important and what is irrelevant in data analysis, so interpretations of the same data can vary greatly.
● Limited generalizability
Small samples are often used to gather detailed data about specific contexts. Despite rigorous analysis procedures, it is difficult to draw generalizable conclusions because the data maybe biased and unrepresentative of the wider population.
● Labor-intensive
Although software can be used to manage and record large amounts of text, data analysis often has to be checked or performed manually.
What are some qualitative research approaches?
- Grounded theory
- Ethnography
- Narrative research
- Historical research
- Case study research
What are the 3 steps involved in a qualitative data analysis?
- Data Reduction
- Data Display
- Data Coding
Explain data reduction?
Selecting, coding, and categorizing raw data to make it more manageable.
Helps focus on relevant information and remove unnecessary data.
*Example:
* Interview with 10 customers → Only responses about product
satisfaction are kept.
* Categorize responses into themes: “quality,” “price,” “customer
service.”
Explain data display?
Presenting data in an organized way (quotes, tables, charts, concept maps).
Makes it easier to interpret patterns and relationships.
*Examples:
* Quote Table: Displaying key customer feedback under different themes.
* Graph: Showing frequency of customer complaints by category.
* Matrix: Comparing responses from different demographics.
Explain data coding?
Reducing, rearranging, and integrating data to develop insights or theory.
Helps in identifying recurring patterns and themes.
*Example:
* Interview transcripts are labeled with keywords (e.g., “positive
experience,” “negative service”).
* Keywords are grouped into broader themes (e.g., “customer
satisfaction”).
* A theory about customer behavior is developed based on trends
What are the 5 steps usually used in a quantitative data analysis?
- Prepare and organize your data. This may mean transcribing interviews or typing up fieldnotes.
- Review and explore your data. Examine the data for patterns or repeated ideas that emerge.
- Develop a data coding system. Based on your initial ideas, establish a set of codes that you can apply to categorize your data.
- Assign codes to the data. For example, in qualitative survey analysis, this may mean going through each participant’s responses and tagging them with codes in a spreadsheet. As you go through your data, you can create new codes to add to your
system if necessary. - Identify recurring themes. Link codes together into cohesive, overarching themes.
What is content analysis?
It is a detailed,
systematic
examination of the
contents of a particular
material for identifying
patterns or themes.
What are some general steps in content analysis?
● Identify the specific body of material which
needs to be explored
● Define the characteristics or qualities to be
examined in precise terms
● Break into small and manageable segments
● Scrutinise and sort the materials
