2026-04-27 20:41:39lisa:
Data Collection Methods: add Check Your Understanding section
Five MCQs covering: primary vs secondary, triangulation, common
plan-mix risks, qual/quant typing rule, and matching method to
SRS section. Each answer in OtterWiki spoiler block (>!) with a
one-sentence rationale.
sd/C02/Data Collection Methods.md ..
@@ 188,6 188,37 @@
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## Check Your Understanding
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Answer in your head first, then click the spoiler to check.
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**1.** Which of these is a **secondary** data collection method?
>! **(d) literature review.** Secondary methods reuse data someone else already collected. Interviews, surveys, and observations are all *primary* — you collect the data first-hand.
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**2.** You want to know whether your survey finding *"most students prefer dark mode"* is real or just a fluke. Which method would best **triangulate** that claim?
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*(a) another survey with the same question · (b) an interview asking why · (c) observation of students using the system in their usual environment · (d) a report on UI trends*
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>! **(c) observation.** Triangulation = checking the claim against a *different* type of evidence. Re-asking in another survey reproduces the same self-report bias. Observation tests whether stated preference matches actual behaviour — the strongest cross-check.
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**3.** A classmate's data collection plan is: *"three interviews with my client"*. According to this page, what's the biggest risk?
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*(a) too few people for breadth · (b) interviewer bias · (c) qualitative-only data · (d) all of the above*
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>! **(d) all of the above.** Three interviews with one stakeholder gives no breadth (only one person's perspective), introduces interviewer bias unchecked, and produces only qualitative data. The rubric explicitly looks for a *justified mix*; this caps at 6–7 on C2-1.
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**4.** You collect 50 survey responses to the question *"how often do you forget to bring your laptop?"* with options *Never / Rarely / Sometimes / Often / Always*. What kind of data is this?
>! **(b) quantitative.** Even though the *topic* feels qualitative ("how often" is a subjective judgement), the *data type* is quantitative — closed-ended responses you can count and compare. Data type is determined by what you do with it, not what it's about.
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**5.** For your project's **technical environment** section of the SRS, which method is usually most efficient?
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*(a) interview the IT coordinator · (b) survey students about their devices · (c) observation in the computer lab · (d) request the school's existing IT device list (a report)*
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>! **(d) request the school's IT device list.** That data already exists — your IT staff maintain it. Surveying or interviewing recreates work that's already done. (a) is a useful follow-up if the list is unclear, but the report is your starting point.
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## See also
- [Essential Terms](Essential%20Terms.md) — definitions of *qualitative*, *quantitative*, *open-ended*, *close-ended*, and the four method names
