Video Summary - Sampling in qualitative research

Main ideas and lessons

Sampling meaning (general definition): Sampling is when researchers study a portion of a larger group of potential participants and use results to make statements about the broader population.
Key difference for qualitative research: Qualitative sampling is nonprobability sampling (no random selection). Sampling choices are driven by:
- ongoing analysis
- the needs of the research as data collection proceeds
Why qualitative sampling differs in size: Qualitative studies usually use smaller samples because data collection goes in depth, making it impractical to recruit large numbers as in quantitative research.
Goal of qualitative findings: Instead of “generalizability” in the statistical sense (common in quantitative research), qualitative sampling aims for transferability—findings that can be applied to other contexts or similar settings.
When to stop sampling: Sampling continues until:
- data saturation is reached (no new meaningful data emerges)
- alternatively, some discuss information power for guiding sample size in qualitative research

Qualitative research commonly uses three nonprobability sampling types:

How participants are selected: Choose participants based on easy access/availability.
Core idea: Recruit whoever is readily reachable for the study.
Example given: Interview university students about views on assessment feedback because they are at the university and accessible.

How participants are selected: Select participants on purpose to capture specific experiences relevant to the research question.
Core idea: Recruit people who have knowledge/experience that will produce relevant data.
Selection strategy example given: To study views on assessment feedback across experiences, include:
- mature students
- students who came directly from school/college
- students with a previous degree
- a mix of male and female participants
Why this matters: Ensures the dataset reflects a wide range of backgrounds/experiences through intentional selection.

How participants are selected: Identify initial participants, then use their networks to reach others who meet inclusion criteria.
Core idea: Useful for hard-to-identify groups.
Process described:
- Recruit one participant with relevant experience and inclusion criteria
- Ask them to connect you with other relevant individuals
- Repeat (network expands “like a snowball”)
Example given: Studying students with bad experiences of assessment feedback—such students may not volunteer at first, but someone with a difficult experience may connect you to friends who share similar experiences.