OpenCyber AcademyLesson map
Lesson 33 published. Map, example, EX097.
flowchart TD
N0["Learning outcomes"]
N1["33.1 Results"]
N2["33.2 Confounders"]
N3["33.3 Conclusion"]
N4["33.4 Ethics"]
N5["33.5 Next"]
N6["Reading the result"]
N7["Staff feedback"]
N0 --> N1 --> N2 --> N3 --> N4 --> N5 --> N6 --> N7
N7 --> EX["Worked example"]
EX --> Q["Exercise EX097"]
Logical drawing
flowchart LR
N0["Learning outcomes"]
N1["33.1 Results"]
N2["33.2 Confounders"]
N3["33.3 Conclusion"]
N4["33.4 Ethics"]
N5["33.5 Next"]
N6["Reading the result"]
N7["Staff feedback"]
N0 --> N1 --> N2 --> N3 --> N4 --> N5 --> N6 --> N7 --> Q["EX097"]
[Learning outcomes]
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[33.1 Results]
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[33.2 Confounders]
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[33.3 Conclusion]
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[33.4 Ethics]
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[33.5 Next]
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[Reading the result]
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[Staff feedback]
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[Worked example] --> [Exercise EX097]
Learning outcomes
You will (1) analyse the reminder study; (2) interpret results; (3) state limits.
33.1 Results
Share within 14 days rose from 26 of 45 to 33 of 45 after reminders.
The before months show 25 and 27 laptops within 14 days, an average of 26; the after months show 32 and 34, an average of 33. As shares of 45, that is a rise from about 58% to about 73%. The rise of seven laptops is larger than the five-laptop threshold Aisha set in advance, and it appears in both after months, not only in their average. Aisha reports the counts for each month in a small table, so readers can check the averages themselves.
33.2 Confounders
Forced restarts started the same month, so reminders cannot take all credit.
The forced restart after seven days' notice targets the same delay that reminders target: staff postponing restarts. Because both started in the same month, the study cannot separate their effects, and the before-after design has no control group to help. Aisha's diary also records new laptops and holidays during the four months, which she lists as further possible influences on the counts. She also checks that no laptops were added or removed in the four months in a way that changed the total of 45.
33.3 Conclusion
Reminders plus forced restarts are associated with improvement.
Aisha's wording follows Dr Grant's correction: improvement coincided with reminders and forced restarts, rather than "reminders worked". The conclusion rests on three facts: the threshold set in advance was met, the rise held in both months, and staff did not complain. It recommends keeping both changes and continuing to measure, which is a decision Bramley can act on without a stronger claim. Dr Grant suggests a longer comparison as future work, which would help separate the two changes.
33.4 Ethics
No individual is named.
All results are counts per month, such as 32 of 45, so no laptop owner can be identified from the dissertation. The staff survey is anonymous and reported as totals, including the three staff who asked for fewer emails. Raw update reports stay with Gareth inside IT, and Aisha's copies are deleted within a month of her capstone submission. The study's ethics approval is filed with the dissertation, together with the note sent to staff about the reminders.
33.5 Next
A future study could stagger changes.
Aisha suggests introducing reminders and forced restarts in different months, or to different groups of laptops, so each change can be measured on its own. A longer comparison, over a full year, would also show whether the rise lasts and how seasons affect it. She also proposes the test she noted earlier: if compliance falls after reminders stop, that supports their effect. A staggered design could also test whether combining reminders into one weekly message, as staff requested, changes the effect.
Reading the result
The reminder study compares two months before with two months after. Before, an average of 26 of 45 laptops were patched within 14 days; after, 33. The rise of seven exceeds the five-laptop threshold set in advance, so Aisha reports a likely improvement.
She is careful with the claim. The after period included the new forced restart policy, which may also have helped. With only two months on each side, chance variation is possible. She therefore says the reminders and restart policy together were associated with improvement, and recommends continuing both while monitoring.
Dr Grant praises the honest wording and suggests a longer comparison as future work.
Staff feedback
A short survey finds most staff found the reminders helpful and not annoying; three asked for fewer emails, so reminders are combined into one weekly message.
What would change the conclusion
If compliance fell back after reminders stopped, that would support their effect; Aisha notes this as a test.
Data
All data are aggregated counts.
Checking month by month
Looking at each month separately, the before months show 25 and 27 laptops patched within 14 days, and the after months show 32 and 34. The rise holds in both after months, which makes chance a less likely explanation, though not impossible.
Project log entry
Aisha also reports what she cannot conclude. She cannot say reminders alone caused the rise, nor that the effect will last. She can say that the result met the threshold set in advance, held in both months, and did not come with complaints from staff.
Worked example
Dr Grant asks Aisha to rewrite "reminders worked" as "improvement coincided with reminders and forced restarts".
Synthetic case. Synthetic.
Errors and limits
Simultaneous changes confound simple comparisons.
Exercises
- EX097 — Result. How did the share change?
Show marking criteria
Rubric: 3 = 26→33 of 45; 2 = partial; 1 = vague; 0 = none. - EX098 — Confounder. What confounds the result?
Show marking criteria
Rubric: 3 = forced restarts same month; 2 = partial; 1 = vague; 0 = none. - EX099 — Rewrite. How was the conclusion rewritten?
Show marking criteria
Rubric: 3 = coincided with both; 2 = partial; 1 = vague; 0 = none.
Synthesis
Name confounders honestly.
Continue studying — chapter 33 of 40
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