Lesson map
Lesson 23 published. Map, example, EX067.
flowchart TD
N0["Learning outcomes"]
N1["23.1 Survey analysis"]
N2["Lab — Counting reported barriers"]
N3["23.2 Coding interviews"]
N4["23.3 Combining findings"]
N5["Synthesis"]
N0 --> N1 --> N2 --> N3 --> N4 --> N5
N5 --> EX["Worked example"]
EX --> Q["Exercise EX067"]
Logical drawing
flowchart LR
N0["Learning outcomes"]
N1["23.1 Survey analysis"]
N2["Lab — Counting reported barriers"]
N3["23.2 Coding interviews"]
N4["23.3 Combining findings"]
N5["Synthesis"]
N0 --> N1 --> N2 --> N3 --> N4 --> N5 --> Q["EX067"]
[Learning outcomes]
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v
[23.1 Survey analysis]
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[Lab — Counting reported barriers]
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v
[23.2 Coding interviews]
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v
[23.3 Combining findings]
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v
[Synthesis]
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v
[Worked example] --> [Exercise EX067]
Learning outcomes
You will (1) analyse survey data on reporting barriers; (2) code interview responses into themes; (3) combine both into findings.
23.1 Survey analysis
Nadia's anonymous survey received 84 responses from 120 staff. She asked which barriers made reporting less likely, allowing several answers. The lab counts how often each barrier was chosen. The most common barrier is uncertainty about whether an email is suspicious enough, followed by not knowing how to report and worry about looking foolish. She reports counts and percentages, and notes that respondents may differ from non-respondents, perhaps being more engaged, so the results describe those who answered rather than all staff. She shares the counts with staff.
Lab — Counting reported barriers
# Barrier counts from 84 synthetic survey responses (multiple choice).
b = {"unsure if suspicious enough": 45, "don't know how to report": 28, "worry about looking foolish": 19, "too busy": 17, "never hear back": 12}
for k, v in sorted(b.items(), key=lambda x: -x[1]): print(f"{k}: {v}/84 = {v / 84:.0%}")
Run with python3 lab_barriers.py. Verified output:
unsure if suspicious enough: 45/84 = 54%
don't know how to report: 28/84 = 33%
worry about looking foolish: 19/84 = 23%
too busy: 17/84 = 20%
never hear back: 12/84 = 14%
23.2 Coding interviews
Nadia interviews eight counter staff for about twenty minutes each, taking notes without names. She reads the notes several times and labels passages with codes such as unsure, busy, no reply and embarrassed. She groups codes into themes: uncertainty, time pressure, lack of feedback and social risk. A second student codes two interviews independently and they compare, discussing disagreements to refine the code definitions. This simple check improves consistency and makes the coding less dependent on one person's interpretation. They agree on most codes.
23.3 Combining findings
Nadia combines survey and interviews. The survey shows uncertainty is the most common barrier; interviews explain it: staff fear wasting IT's time and have never been told that unsure reports are welcome. Lack of feedback appears in interviews though not in the top survey choices, suggesting it matters more than the survey captured. Her findings are that Ashcombe should tell staff explicitly to report when unsure, make reporting quicker and reply to every report. Each finding is linked to its evidence.
Worked example
Nadia counts barriers from 84 survey responses, codes interviews into themes with a second coder and combines the methods into findings.
Synthetic case. Data are synthetic.
Errors and limits
Survey response bias. Coding remains interpretive.
Exercises
- EX067 — Response rate. What was the survey response rate?
Show marking criteria
Rubric: 3 = 70%;; 2 = 84 of 120;; 1 = 84%;; 0 = none. - EX068 — Top barrier. What was the top barrier and its share?
Show marking criteria
Rubric: 3 = unsure if suspicious enough, 45 of 84 or 54%;; 2 = uncertainty;; 1 = vague;; 0 = none. - EX069 — Second coder. Why did a second student code interviews?
Show marking criteria
Rubric: 3 = to check consistency of codes;; 2 = consistency;; 1 = vague;; 0 = none.
Synthesis
Surveys show how common barriers are and interviews explain why they matter.
Continue studying — chapter 23 of 40
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