There is no absolute right or wrong in using convenience sampling and quota sampling. However, in rigorous educational research, they are often discouraged because they introduce systematic weaknesses that can undermine the credibility and defensibility of findings.
Here is the precise rationale:
1. Threat to Representativeness (External Validity)
- Convenience sampling selects participants based on ease of access (e.g., your own students).
- In action research, convenience sampling is usually the default because a teacher is studying the environment where he/she teaches already in. Thus, it is appropriate because action research is participatory. A teacher is the “insider” researcher, and the participants are the students or colleagues directly involved in the process one wants to improve.
- However, a teacher cum researcher who is using action research can move from selecting participants through convenience sampling to purposive sampling. So, it is more suitable because it is often seen as more “rigorous” in action research because it ensures the data comes from the people most affected by the issue.
- Example: A lecturer wants to explore his/her supervision in terms of its effectiveness and enhancing students’ learning experience. So, even though students who are under his/her supervision is convenience sample, yet the lecturer cum researcher can use criterion Sampling when he/she focuses only on specific criteria such as his/her research samples are students who do not have any background in education who are doing PhD in Education. In this regard, criterion sampling as a type of purposive sampling is chosen because the lecturer cum supervisor cum researcher selects participants because they meet a specific predetermined criterion and thus, it shows a more deliberate research design. It moves the study from “I just used who was there” to “I strategically chose these participants because they have the specific experience needed to solve the research problem.“
- Quota sampling ensures proportions (e.g., gender, age) but still relies on non-random selection. While the primary strength of quota sampling is its ability to mirror the population’s known distribution of certain characteristics (or controlled characteristics), ensuring these proportions (e.g., gender, age, location) are reflected in the sample, yet it may not be representative of the population for other uncontrolled characteristics (e.g., income, specific attitudes). Since selection within quotas is non-random, certain segments of a quota group might be systematically under- or over-represented.
The issue:
Neither method (convenience and quota sampling) gives every member of the population an equal chance of selection. This leads to sampling bias, meaning the sample may not reflect the actual population.
Consequence: Findings cannot be confidently generalised to the wider educational context.
Note: For action research, findings are not meant for generalisation and thus, using convenience sampling or purposive sampling suits with its nature. Action research, by its very nature, is a localized and context-specific form of inquiry aimed at solving immediate, practical problems and implementing improvements within a particular setting (such as a classroom, school, or organization). Consequently, the findings generated from an action research study are typically not intended or suitable for broad generalization to other populations or settings. Therefore, employing non-probability sampling techniques, such as convenience sampling or purposive sampling, is entirely consistent with the core principles and aims of action research.
2. High Risk of Systematic Bias
These methods are particularly vulnerable to:
- Selection bias (researcher chooses who is “available” or “fits”)
- Volunteer bias (participants who agree may differ systematically)
- Context bias (e.g., one class, one school culture)
Note: In education, this is critical because student performance, motivation, or behaviour can vary widely across contexts (schools, regions, SES).
3. Weak Alignment with Inferential Statistics
In quantitative studies, especially those aiming for hypothesis testing, prediction and generalisation, sampling design must support statistical assumptions. Thus, with convenience or quota sampling:
- You cannot justify probability-based inference
- Statistical conclusions become methodologically fragile
4. Limited Transferability (Qualitative Context)
Even in qualitative research, convenience sampling often produces shallow or homogeneous data and it may not capture information-rich cases. This weakens, the depth of analysis, conceptual development and credibility of interpretations
5. Methodological Inconsistency
Sampling must align with research intent:
- If your goal is theory generation -> you need purposeful/theoretical sampling
- If your goal is generalisation -> you need probability sampling
Using convenience or quota sampling often signals a mismatch between research design and sampling logic.
What is the exception of using convenience sampling?
1.Preliminary Research
Used to generate preliminary insights or hypotheses.
Example: A psychology lecturer in Malaysia surveying her own students to test whether a new questionnaire is understandable before wider use. This is in the stage of refining research instrument (developmental stage of a research instrument), prior to pilot study. This exploration phase, not the actual data collection and can be done in several cycles of research instrument refinement.
2. Pilot Studies / Feasibility Testing
Helps refine research tools, methods, or logistics before committing resources to a full-scale study.
Example: A research student is studying about digital usage among postgraduate university students and plan to conduct the data collection using online mode. The research student wants to test whether an online survey platform works smoothly by first distributing it to postgraduate classmates or fellow research colleagues.
3. Resource-Constrained Situations
When time, budget, or access limitations prevent random sampling.
Example: A small NGO collecting quick feedback from nearby communities due to limited funding about the effectiveness of their services which the communities receive and use.
4. Classroom or Informal Research
Used in teaching, training, or internal assessments where generalizability is not required.
Example: A statistics class at a university using classmates as a sample to practice survey analysis. It acknowledges the practical reality of being a practitioner-researcher.
What you must do (critical for assessment)
If you use convenience sampling, you must demonstrate methodological awareness:
1. Justify the choice
Explain clearly:
- Why this sample is accessible and relevant
- Why alternative sampling methods were not feasible
Example: “Convenience sampling was employed due to accessibility to a defined cohort within the institution, allowing timely data collection within the study period.”
2. Acknowledge limitations
Be explicit about:
- Limited representativeness
- Restricted generalisability
- Potential sampling bias
3. Align with research design
Ensure consistency:
- If quantitative research -> avoid strong claims of population generalisation
- If qualitative research -> emphasise contextual depth, not representativeness
