03 · What You Need to Know
How the Scope and Purpose of a Research Aim Shape Qualitative Sampling
What Is the Research Aim in Qualitative Research?
The research aim expresses what the study seeks to understand, interpret, describe, or explain.
It defines the central phenomenon and helps establish the boundaries of the inquiry.
For example, a study might aim to understand how university teachers experience the transition from conventional examinations to performance-based assessment in online courses.
Another study might aim to compare how teachers across several institutions negotiate institutional expectations concerning assessment integrity.
Both are qualitative aims, but they require different forms of information and potentially different sampling strategies.
The research aim should therefore be established before selecting a participant number.
Why Does a Narrower Aim Often Support a Smaller Sample?
A narrowly focused aim limits the range of phenomena that the analysis must address.
Suppose a researcher investigates how experienced online mathematics instructors design authentic assessment tasks for one particular course type.
The participant population is specific, the phenomenon is bounded, and the intended analysis may concentrate on a relatively coherent set of professional experiences.
Such conditions may support a focused sample because participants can provide information directly relevant to the question.
However, the researcher must still evaluate whether the interviews offer sufficient detail and whether meaningful variation has been explored.
A narrow aim increases the possibility of focused recruitment; it does not establish a universally sufficient number.
Why Can a Broader Aim Require More Participants?
A broad aim may involve several phenomena, participant groups, institutional settings, or forms of experience.
For example, a study investigating teachers' experiences with educational AI across disciplines, career stages, and institutions introduces substantially more potential variation than a study focused on one assessment practice.
If the researcher intends to make analytical claims about those differences, the sample must provide information relevant to each comparison.
Recruiting more participants may help, but additional numbers alone do not guarantee coverage. The sampling strategy must deliberately identify participants who can illuminate the distinctions of interest.
In some cases, narrowing the research aim may be more methodologically defensible than attempting to address an excessively broad question with an unmanageable sample.
How Do Descriptive, Exploratory, and Explanatory Aims Differ?
Qualitative studies can pursue different forms of understanding, although these categories are not mutually exclusive.
| Research aim |
Typical analytical purpose |
Sampling implication |
| Focused descriptive aim |
Describe experiences or practices within a defined context. |
Recruit participants with direct relevant experience and sufficient variation for the description. |
| Broad exploratory aim |
Investigate a phenomenon with uncertain dimensions. |
Allow for broader recruitment and possible refinement as relevant perspectives emerge. |
| Interpretive aim |
Understand how participants construct meanings around experiences. |
Prioritize information richness and analytical depth consistent with the methodology. |
| Comparative aim |
Examine similarities and differences across groups or settings. |
Ensure sufficient relevant material within and across the intended comparison groups. |
| Theory-development aim |
Develop conceptual explanations or relationships. |
Consider iterative or theoretical sampling as analytical questions develop. |
These distinctions help clarify sampling requirements, but they do not correspond to fixed participant counts.
How Does the Research Aim Relate to Information Power?
Malterud, Siersma, and Guassora (2016) identify the study aim as one of five dimensions of information power.
Their framework proposes that a focused aim may support higher information power because the information needed is more clearly defined.
A broader aim may require more participants or more varied data because the study must address a wider range of experiences.
However, the aim interacts with sample specificity, established theory, dialogue quality, and analysis strategy.
The information power framework therefore supports a more nuanced justification than simply assuming that broad studies always need large samples.
How Does the Aim Determine Who Should Be Recruited?
The research aim should guide participant eligibility and purposive sampling criteria.
If the study examines how teachers design online performance-based assessments, participants should have direct experience of that activity.
If the study examines institutional policy implementation, relevant participants might include teachers, course designers, and others directly involved in interpreting or implementing the policy.
Recruiting participants who are readily available but have limited relevant experience may increase the participant count without improving the information available for analysis.
The specificity of the sample should therefore follow the phenomenon and perspective identified in the research aim.
Does a Narrow Aim Require a Homogeneous Sample?
Not necessarily. A focused research aim may still require meaningful variation among participants.
For example, a study examining teachers' decisions about AI-assisted feedback might recruit participants from different disciplines because disciplinary expectations influence feedback practices.
The sample can remain specific to the phenomenon while including relevant differences in experience.
Homogeneity may support intensive examination of shared experiences in some methodologies, but it can also restrict the range of perspectives available.
The researcher should distinguish variation that is necessary for answering the question from variation that would unnecessarily broaden the inquiry.
How Does a Comparative Aim Change Sampling Requirements?
A comparative qualitative study seeks to examine differences or similarities across defined groups, settings, or conditions.
For example, a researcher may compare how teachers in lecture-only courses and lecture-with-laboratory courses design performance-based assessments.
The sampling plan must provide sufficient information about both contexts to support the intended comparison.
A pooled sample of twenty participants may appear adequate overall but be uninformative if nineteen participants belong to one group and only one to the other.
However, qualitative comparison does not necessarily require equal group sizes. Adequacy depends on the analytical purpose and the richness of information within each group.
Researchers should not borrow numerical allocation rules from quantitative hypothesis testing unless a separate statistical objective requires them.
Does Every Subgroup Need Its Own Saturation Assessment?
Only when saturation is methodologically appropriate and the research objective requires meaningful conclusions about the subgroups.
For example, a coding-oriented study comparing teachers from different institutional settings may need to examine whether important experiences remain unexplored within each setting.
However, imposing identical saturation thresholds on every subgroup can be unnecessary or conceptually inappropriate.
Researchers should first determine whether saturation fits their qualitative methodology.
Where it does, the assessment should reflect the intended analytical comparisons rather than a generic numerical requirement.
How Does the Aim Influence Interview Design?
A clearly defined research aim helps determine what interview questions should explore.
Focused aims allow researchers to develop prompts that elicit detailed accounts of specific experiences or decisions.
For example, asking teachers to describe how they revised an assessment after encountering AI-generated student work may produce information more directly relevant to assessment-design decisions than asking broadly whether AI is beneficial.
However, overly restrictive questions may prevent participants from introducing unexpected but important perspectives.
Good qualitative interviewing balances relevance to the aim with openness to participants' experiences.
The quality of interviews can influence how much useful information the sample provides.
Can a Broad Aim Be Addressed Through One Case Study?
Sometimes, provided the case is appropriately bounded and the claims remain consistent with the evidence.
For example, a researcher might investigate how an institution implements generative AI policies across teaching, assessment, and course design.
Although the topic is broad, the case boundaries may make the investigation manageable through a combination of interviews, documents, and observations.
However, one institution cannot automatically support conclusions about how all universities implement similar policies.
Sample adequacy in case study research concerns the sufficiency of evidence within the bounded case, not merely the number of interview participants.
How Does Theory Development Affect Sample Size?
When the research aim involves developing conceptual explanations, sampling may evolve as analysis progresses.
Grounded theory approaches, for example, may use theoretical sampling to investigate emerging categories and their relationships.
Early interviews may suggest that institutional trust influences teachers' willingness to adopt AI-assisted assessment practices.
The researcher may then recruit participants with contrasting experiences of institutional support to examine that developing category.
The final sample depends partly on the conceptual questions arising during analysis.
A fixed number established before data collection may therefore be insufficient as the sole recruitment criterion.
What If the Research Aim Changes During Data Collection?
Qualitative research may permit refinement of the research question as the researcher develops a better understanding of the phenomenon.
However, a material change in the aim can alter participant eligibility, recruitment requirements, interview questions, and analytical claims.
For example, shifting from teachers' assessment-design decisions to students' experiences of those assessments introduces a different participant population.
The researcher should reassess the sampling plan and consider whether amendments to ethics approval are necessary.
Changes should be documented rather than presented retrospectively as though the revised aim had guided the original recruitment.
Can Narrowing the Research Aim Reduce the Required Sample?
Potentially, but the reduction must be methodologically justified.
Narrowing a broad investigation to a more specific phenomenon can reduce the number of distinct experiences and contexts that must be examined.
For example, a study of teachers' overall AI adoption could be narrowed to teachers' decisions about AI-assisted formative feedback.
However, narrowing the aim solely because recruitment has failed may require reconsideration of the research contribution and the claims that can be supported.
A revised aim should remain scientifically meaningful and consistent with the collected data.
How Does the Research Aim Affect Analytical Depth?
Sample-size adequacy depends not only on the breadth of the question but also on the depth of interpretation required.
A focused phenomenological study may involve intensive analysis of a relatively small number of accounts.
A descriptive study seeking to map a broad range of practices may require more participants but less intensive interpretation of each individual case.
Neither design is inherently superior. They pursue different analytical purposes.
Researchers should ensure that the proposed sample and available resources support the intended level of analysis.
Can Too Many Research Questions Make Sample-Size Planning Difficult?
Yes. A proposal containing numerous loosely connected research questions may require substantially different forms of evidence.
For example, investigating teachers' attitudes, institutional policy implementation, student learning outcomes, and professional identity within one interview study may create an unmanageable scope.
Some questions may also require different methods. Student learning outcomes, for instance, may need quantitative or other direct evidence rather than teachers' perceptions alone.
Before increasing the sample, researchers should examine whether all questions belong within the same qualitative design.
A coherent and appropriately bounded aim often provides a stronger foundation for sampling than an expansive collection of loosely related objectives.
How Should the Aim Inform a Provisional Sample-Size Range?
Researchers can develop a provisional range by considering the scope of the aim, the required participant perspectives, and the analytical strategy.
Methodologically comparable studies may provide useful contextual evidence.
However, a range should not be justified solely because another thesis used similar numbers.
The researcher should explain what information the planned sample is expected to provide and how adequacy will be assessed.
Where iterative recruitment is appropriate, the plan should permit adjustment in response to emerging analytical needs.
The question of predetermining a qualitative sample-size range should be resolved in relation to the methodology and institutional requirements.
How Can Researchers Tell Whether the Aim Is Too Broad?
A research aim may be too broad when it requires more participant groups, contexts, or forms of evidence than the study can reasonably investigate.
Warning signs include research questions that span unrelated phenomena, comparisons unsupported by the proposed sample, or analytical claims that extend far beyond the available participant experiences.
Researchers can improve focus by identifying the central phenomenon, defining the context, clarifying whose perspectives matter, and specifying the intended analytical contribution.
These decisions should be guided by the research problem rather than made solely to reduce recruitment workload.
How Should the Relationship Between Aim and Sample Size Be Reported?
A qualitative methods section should explain how the research aim informed participant selection, sample diversity, and the initial recruitment target.
It should also identify the criterion used to evaluate the achieved sample.
For example, a focused interview study might explain that participants were selected for direct experience of the phenomenon and that recruitment was reviewed against the richness and variation of the material needed for the intended analysis.
If the aim was comparative, the report should explain how the sample supported the relevant comparisons.
The strongest justification connects the research question to the information obtained rather than treating the final participant number as self-explanatory.
