A well-formed research question can still be ruined by a poorly matched design. CES8150 is the course where students learn to choose — and defend — a research design capable of actually answering the question their theoretical framework generated.
Quantitative, qualitative, and mixed-methods designs
CES8150 covers the major design families in depth: quantitative designs (experimental, quasi-experimental, correlational, and survey), qualitative designs (phenomenology, grounded theory, case study, narrative inquiry, ethnography), and mixed-methods designs (convergent, explanatory sequential, exploratory sequential) that combine both. Students learn the specific strengths and limitations of each — for instance, phenomenology captures lived experience richly but cannot establish causal relationships, while an experimental design can establish causality but often at the cost of ecological validity.
Sampling, validity, and trustworthiness
The course covers sampling strategies appropriate to each design family — probability sampling for generalizable quantitative findings, purposive sampling for information-rich qualitative cases — and the corresponding standards for rigor: internal/external/construct validity for quantitative designs, and credibility/transferability/dependability/confirmability (Lincoln and Guba's trustworthiness criteria) for qualitative designs. Students practice justifying a sample size and sampling strategy as a defensible methodological choice, not an arbitrary convenience decision.
Key topics in CES8150
- Quantitative designs: experimental, quasi-experimental, correlational, and survey research
- Qualitative designs: phenomenology, grounded theory, case study, narrative inquiry, ethnography
- Mixed-methods designs: convergent, explanatory sequential, exploratory sequential
- Sampling strategies: probability sampling vs. purposive/theoretical sampling
- Quantitative rigor: internal, external, and construct validity; reliability
- Qualitative rigor: Lincoln and Guba's trustworthiness criteria (credibility, transferability, dependability, confirmability)
- Matching a research design to a research question and theoretical framework
Working on a research-design proposal or a methods-selection justification?
Our doctoral-level experts build CES8150 coursework with defensible, well-matched research designs.
Worked example: matching design to research question
- Research question: "How do first-generation doctoral counseling students experience imposter phenomenon during their program?"
- Design consideration: This question asks about lived experience and meaning-making, not measurable group differences
- Design selected: Interpretative Phenomenological Analysis (IPA), a qualitative design suited to rich, first-person accounts of a shared experience
- Sampling: Purposive sampling of 8-10 first-generation doctoral counseling students, selected for information richness, not statistical representativeness
- Rigor plan: Credibility established through member checking; dependability through an audit trail of coding decisions
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Research-design proposals and methods-selection assignments.
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Frequently asked questions
The choice should follow directly from the research question, not personal preference for a method. If the question asks about relationships between measurable variables, the effect of an intervention, or seeks generalizable findings across a population (e.g., "Does a specific supervision model reduce burnout scores more than standard supervision?"), a quantitative design is appropriate. If the question asks about lived experience, meaning-making, or a process that isn't yet well understood or measurable (e.g., "How do counselor educators experience the transition from clinician to academic?"), a qualitative design is appropriate. CES8150 teaches that a common error is selecting quantitative methods because they feel more "rigorous" even when the research question is fundamentally about experience and meaning — rigor in qualitative research comes from trustworthiness criteria specific to that paradigm, not from imitating quantitative validity standards that don't actually apply.
Lincoln and Guba proposed four criteria as the qualitative parallel to quantitative validity and reliability: credibility (do the findings accurately represent participants' experiences — established through techniques like member checking and prolonged engagement), transferability (can the findings inform understanding in other similar contexts — established through thick, detailed description rather than statistical generalization), dependability (would the findings be consistent if the study were repeated under similar conditions — established through an audit trail documenting methodological decisions), and confirmability (are the findings shaped by the data and participants rather than researcher bias — established through reflexivity and bracketing researcher assumptions). CES8150 teaches these as the standard a qualitative dissertation methodology chapter must explicitly address, since a committee will expect to see how each criterion was met, not just an assertion that the study is trustworthy.