Notes Application

🧠 Data Collection and Sampling Methods in Qualitative Research

📌 Key terms

Term	Definition
Sampling	The process of selecting participants or cases to study from a population.
Purposive Sampling	Selecting participants based on specific characteristics or relevance to the research question.
Snowball Sampling	Existing participants recruit future participants through their social networks.
Convenience Sampling	Selecting participants based on availability and willingness.
Quota Sampling	Ensuring sample proportions match characteristics in the population (e.g., age, gender).
Theoretical Sampling	Sampling guided by emerging theory—used in grounded theory research.
Semi-Structured Interview	A flexible interview with open-ended questions based on a guiding schedule.
Unstructured Interview	Open conversation that explores topics freely with minimal guidance.
Focus Group	A group interview led by a facilitator, exploring collective perspectives.
Participant Observation	The researcher becomes part of the setting to observe behaviors and interactions.
Non-Participant Observation	The researcher observes without engaging with participants.
Naturalistic Observation	Observation of behavior in real-life contexts without manipulation.
Field Notes	Detailed written accounts of observed events, contexts, and reflections.
Reflexive Journal	A diary in which the researcher records personal thoughts and methodological decisions.

📌 Notes

Purpose of Qualitative Data Collection

Focuses on in-depth understanding of experiences and social interactions.
Seeks rich, descriptive data to interpret meanings rather than measure variables.
Methods are flexible and iterative—data collection and analysis often occur simultaneously.

📌 Comparison with Quantitative Research

Method	Description	Strengths	Limitations
Interviews (Semi-Structured/Unstructured)	Open-ended discussions exploring individual perspectives.	Deep insight into thoughts, flexible, builds rapport.	Time-consuming, interviewer bias possible.
Focus Groups	Group discussions guided by a moderator.	Generates diverse opinions, stimulates discussion.	Social desirability bias, group dynamics may suppress dissent.
Participant Observation	Researcher actively engages in setting to observe behavior.	High ecological validity, contextual detail.	Risk of researcher bias, ethical issues of consent.
Non-Participant Observation	Researcher observes from outside.	Reduces interference, useful in public settings.	Limited insight into motives.
Case Studies	In-depth study of one individual or group.	Provides comprehensive understanding.	Not generalizable; prone to researcher bias.
Document and Content Analysis	Systematic analysis of existing records, media, or text.	Non-intrusive, historical context possible.	Interpretation bias, lack of context.

Ensuring Credibility in Data Collection

Ensure ethical transparency—confidentiality, informed consent, and respect.
Use triangulation: multiple sources/methods.
Maintain reflexivity journals and field notes.
Conduct member checks to verify participants’ perspectives.

🔍Tok link

What counts as “truth” in qualitative findings if data are shaped by both participants and researchers?
This challenges the idea that knowledge can ever be entirely objective.

🌐 Real-World Connection

Qualitative sampling is key in cross-cultural studies, healthcare research, and education, where understanding context and participant experience is essential for effective intervention design.

❤️ CAS Link

Students can engage in local community interviews (e.g., on stress, motivation, or social belonging) and reflect on how purposive or snowball sampling ensures ethical inclusivity.

🧠 IA Guidance

Even though the IA uses quantitative data, students can improve design validity by borrowing qualitative practices such as clear sampling rationale and pilot testing of instruments.

🧠 Examiner Tips

Be specific: use correct terminology (e.g., “semi-structured interviews,” not “normal interviews”).
Always connect method + purpose + example study.
Be prepared to compare qualitative sampling (purposive, snowball) vs. quantitative sampling (random, stratified).