Session Kit: Module 05: Electron Microscopy and Image Basics
Everything needed to run Module 05 as a taught session: prep, timing, materials, misconceptions, rubric.
Generated from modules/module05.md. Edit the module page, not this file.
At a glance
| Duration | 4 hours |
| Capability target | Evaluate EM image patches for artifact risk and issue a justified pass/rework recommendation. |
| Learners leave with | Completed QA worksheet for all six patches |
Before you walk in
- You can state the capability target in one sentence without reading it.
- You have one worked example you will narrate, including where you are unsure.
- Data access works — accounts, viewer, notebook — verified today, not last week.
- The rubric is visible to learners before they start, not after.
- You have decided what “uncertain” earns, and you will say so out loud.
Learners should arrive having covered:
- Modules 01-04
Materials
Run of show
| Time | Segment | Your note |
|---|---|---|
| 00:00-08:00 | EM basics refresher | |
| 08:00-20:00 | Artifact recognition walkthrough | |
| 20:00-34:00 | Learner triage round | |
| 34:00-46:00 | QA threshold debate | |
| 46:00-56:00 | Decision logging practice | |
| 56:00-60:00 | Competency check |
The activity
Scenario: {: #studio-activity}
- Inspect image quality and artifact signatures.
- Classify severity and likely impact on segmentation.
- Decide pass/flag/rework with documented rationale.
- Log findings in a structured QA record for reproducibility.
What learners hand in
- Completed QA worksheet for all six patches
- Spatial artifact map (annotated sketch or diagram)
- One-page recommendation memo with summary table
Misconceptions to target
These are the errors this session exists to prevent. Surface them in the debrief rather than pre-empting them in the lecture — a misconception a learner has voiced is far easier to correct than one they are holding silently.
- They may believe: You can proofread your way out of a bad image.
- Surface it by asking: “What would have to be true for that to hold? What would change your mind?”
- They may believe: A noisy image is worse for segmentation than a clean image with faint membranes.
- Surface it by asking: “What would have to be true for that to hold? What would change your mind?”
- They may believe: Artifact severity can be judged from a count, when the spatial distribution matters more.
- Surface it by asking: “What would have to be true for that to hold? What would change your mind?”
- They may believe: Quality assessment is a clerical checkpoint rather than a scientific judgement that propagates through every downstream claim.
- Surface it by asking: “What would have to be true for that to hold? What would change your mind?”
Naming the norm
Every session is a chance to make one piece of the hidden curriculum explicit. Pick a moment where you would normally just do the professional thing, and say out loud why you are doing it — then ask whether anyone was taught that.
For this session, the candidate is whichever norm the activity most depends on: stating an assumption in the same sentence as the claim, recording the version a number came from, or saying “uncertain” and having it count as a real answer. See the hidden curriculum for the collected set and why naming them is a fairness intervention rather than etiquette.
Assessment
- Minimum (pass): Accurate identification of major artifacts across all patches, correct mapping to segmentation error type, and a defensible pass/flag/rework decision for each patch.
- Strong (merit): Clear articulation of cost tradeoffs, consistent severity thresholds across patches, spatially aware analysis, and a well-structured recommendation memo with specific conditions.
- Failure: Artifact labels assigned without reference to downstream segmentation implications, or QA decisions made without documented rationale.
Grade the reasoning, not the answer. A correct call with no evidence chain should not outscore a well-reasoned incorrect one — and saying so publicly changes behaviour within one session.
Exit prompt
Pick one artifact and explain how it could create a merge or split error later. Then estimate: if this artifact appears on 5% of sections, how many additional proofreading hours would it add to a 1000-section volume?
If this session goes wrong
- Nobody talks in the debrief. You asked “any questions?” Ask instead: “Which cue would you drop first if the data got worse?”
- Everyone finishes early. They are pattern-matching, not judging. Give an ambiguous case where the answer is “uncertain” and see what happens.
- Nobody finishes. The scaffolding came off too fast. Work the next case together rather than pressing on.
- A learner is silently lost. The most likely cause is unstated vocabulary. Point them at the dictionary and check back.