MKB2705 Chap.3 Research Design and Evidence Choices
Research Design and Evidence Choices
Research design is the architecture connecting a question to evidence and a defensible claim. Exploratory design is useful when the problem, language or mechanisms are unclear. Interviews, observation, document review and small pilots can reveal dimensions worth testing, but their purpose is discovery and refinement rather than population estimation.
Descriptive design estimates characteristics, distributions or associations under a defined sampling and measurement system. Causal design requires a credible counterfactual, control of alternative explanations and attention to implementation. These families are not a quality ranking; the weakest design that can support the required decision claim is often the most proportionate choice. Time is part of the architecture.
Cross-sectional evidence describes one period and can identify associations, while longitudinal or repeated evidence can show sequence and change. Neither proves causation by itself. Primary evidence gives the study more control over measurement and recruitment but creates cost, access and ethics obligations.
Secondary evidence can establish context, benchmarks or prior patterns, yet it must be audited for original purpose, definitions, coverage, period, quality controls and permission. Availability is not evidence of fitness. The chapter stages an independent service-access project through exploratory interviews, a descriptive survey and a small intervention pilot. Each stage answers a different question.
Interviews clarify how users define access, the survey estimates the distribution of perceived access, and a pilot can test whether a specific operational change improves an outcome under stated conditions. Combining the stages strengthens the evidence only when their units, constructs and boundaries are compatible.
A design brief should record the decision, question, unit, population, period, source, comparison, planned analysis, main threats and strongest permissible verb. Red-team the brief by naming what it cannot establish. Selection bias, history, maturation, instrumentation, common-method error and nonresponse can each create an attractive but misleading pattern.
Triangulation is useful when methods contribute distinct evidence, not when several weak measures repeat the same assumption. Later-week detail in this chapter is standard research-methods canon aligned to the official sequence and assessment briefs. Scenarios and practice items are independently authored and do not reconstruct live questions or private teaching artifacts.
What this chapter covers
- 01
Decision focus
- 02
Evidence control
- 03
Error control
- 04
Claim boundary
- 05
Decision use
AskSia-authored practice weighting (not an official mark scheme): Original worked model: research design and evidence choices
- +1State the management or evidence question, population and decision use before naming a method.
- +1Choose and defend the relevant design, measure, sample or analysis, preserving the correct valid base.
- +1Report the result or planned output with magnitude, uncertainty and a precise evidence noun.
- +1State the main limitation and a conditional decision or follow-up that does not exceed the evidence.
Key terms
- exploratory design
- A key concept in Research Design and Evidence Choices: define it in the population, context and decision for this study rather than relying on a label alone.
- cross-sectional design
- A control term used to keep research design and evidence choices technically and conceptually traceable across the project.
- counterfactual
- A boundary or diagnostic that should appear beside the relevant result, not only in a generic limitations paragraph.
Research Design and Evidence Choices FAQ
How does research design and evidence choices support MKB2705 assessment?
It supplies a specific research decision, evidence control and claim boundary that can support the proposal, class-test reasoning, SPSS report or reflection. Apply it to your own project and current Moodle task rather than copying the worked model.
What is the most common research design and evidence choices mistake?
The common failure is letting a convenient method, software output or confident phrase replace the decision question and represented evidence. Keep population, construct, valid base and design visible.
Can AI complete this research design and evidence choices work?
No. Follow the current task-specific rule. Use only permitted support, verify every source and number, author submitted prose yourself and complete the required declaration. Quizzes say AI should not be used.
Assessment move
Make a three-column design sheet for exploratory, descriptive and causal evidence. For one original decision, state the uncertainty each design can reduce, the unit and period it observes, and the strongest verb it permits. Add primary and secondary source options, then audit each for purpose, definition, coverage, timing, quality and permission.
Draw the comparison or counterfactual explicitly; if it is missing, downgrade the claim. Red-team the chosen design with at least three threats such as selection, history, common-method error or nonresponse, and attach a control or claim response to each. Finally, compare the expected decision value with cost, burden and access.
Select the most proportionate architecture, not the most elaborate one, and confirm the active assessment brief before fixing any operational detail.
Working through Research Design and Evidence Choices in MKB2705? Sia is AskSia’s AI Marketing tutor — ask any MKB2705 Research Design and Evidence Choices question and get a clear, step-by-step explanation grounded in how MKB2705 is taught and assessed. Read this chapter free, then take your hardest questions to Sia.
