Section 253 of 440
Complete canonical tutorial. This reader section contains the same teaching body as PWR-070 · Visual search. Open the Power dossier.
PWR-070 · SELF GUIDED full tutorial
Scan a grid systematically and use a target-absent stopping rule
Search practice can sharpen a defined search, but rare things remain disproportionately easy to miss. Visual search requires finding a declared target among distractors and knowing when to stop on target-absent trials. The learner studies a template, uses one scan path, marks revisits and records hits, misses, false alarms and target-absent time on new grids. Rare targets remain easy to miss. A simple coverage map makes the scan path observable: skipped cells, immediate backtracking and end-of-row overshoot are marked, then one path correction is rehearsed on a fresh grid.
1 · Permission and limits
Know exactly what you may do
2 · Get ready
Gather what you need and check the starting conditions
What you need
- An exact grid recipe for a helper. Make each grid an 8×8 array of uppercase L characters in one 18-point monospaced font with 1 cm cells. A target-present grid replaces exactly one L with T; an absent grid contains only L. Fold this key: baseline A1 target row 2 column 6, A2 absent, A3 target row 7 column 3, A4 absent; practice B1 target row 4 column 8, B2 absent, B3 target row 1 column 2, B4 absent; delayed low-prevalence C1 target row 6 column 5 and C2–C6 absent. Present grids within each lettered set in a concealed shuffled order and retain the grid label for scoring.
- A target template shown before each grid.
- Pointer or erasable overlay for tracking the scan path.
- Timer and sheet for hits, misses, false alarms, revisits and stopping time.
Before you start
- Use a seated, low-stakes task; no medical images, baggage screening or hazards.
- Fix grid size, viewing distance, lighting and correction.
- Predeclare the scan path and target-absent stop rule.
- Do not add speed pressure until accuracy and false alarms are stable.
3 · The method
Follow these steps in order
- Study the exact template
Look at the target T and name how it differs from the L distractors.
Why: A precise template reduces searching for a vague shape.
Check: The learner identifies target and two distractors correctly.
- Choose a scan path
Select rows, columns or quadrants and state the order before revealing the grid.
Why: A systematic path reduces skipped regions and revisits.
Check: The path covers the full grid once.
- Start the timer and scan
Move through the declared path at a controllable pace, pointing or tracking each region.
Why: External tracking makes coverage visible.
Check: The scan follows the path rather than jumping to salient items.
- Commit target present
If a target is found, mark its location and stop before checking.
Why: A committed location distinguishes a hit from vague suspicion.
Check: One exact location is recorded.
- Apply the absent rule
If no target appears after one complete scan plus the predeclared verification pass, answer absent and stop.
Why: Endless searching inflates time without eliminating misses.
Check: Target-absent decisions use the same rule.
- Classify and mark revisits
Use the key to record hit, miss, false alarm or correct rejection and count repeated regions.
Why: Accuracy, bias and inefficient scanning are different errors.
Check: Every grid has outcome, time and revisit count.
- Retest rare novel targets
After practice, use new grids with the predeclared lower target prevalence and the same scan rule.
Why: Low prevalence can increase misses and must be tested directly.
Check: Prevalence and new-grid status are recorded.
- Draw a coverage trace
On a transparent overlay or duplicate grid, draw a light line through each inspected row or quadrant and put a dot where the eyes or pointer return to an earlier region. Keep this trace separate from the target answer.
Why: A coverage trace distinguishes a missed target from an unvisited region and shows where the declared path breaks down.
Check: Every sector has one pass mark, revisits have dots and the target answer remains unaltered by the trace.
4 · Worked example
See the whole method used once
Scenario
Eva searches four 8×8 T-among-L grids, two without a target.
Walkthrough
- Eva studies the T template and chooses a left-to-right row scan.
- She tracks rows with a pointer and marks one target location before checking.
- On an absent grid she completes one scan and one verification pass, then stops.
- The key shows one miss and no false alarms; she also records three revisits.
- On a delayed novel set with rarer targets, she keeps the same path and compares misses.
- Eva’s overlay reveals that she jumps from row four to row six and revisits row two; the next fresh grid uses a row-number card to correct only that transition.
Result
Eva reduces revisits and maintains accuracy on novel grids. This is grid-specific search learning, not competence in rare real-world hazard detection. Eva can link the miss to a broken row transition rather than simply trying to search faster.
5 · Right and wrong
Compare correct or safer execution with the common wrong version
| Moment | Right / safer | Wrong / riskier | Why it matters |
|---|---|---|---|
| Template | Study the exact target before each grid. | Search for “anything unusual”. | Vague search criteria increase misses and false alarms. |
| Path | Cover rows or sectors systematically. | Jump around toward visually interesting items. | Unstructured search skips regions and repeats others. |
| Absent decision | Stop after the declared coverage and verification pass. | Search indefinitely or quit when bored. | A stable rule makes time and errors comparable. |
| Score | Count misses, false alarms and revisits separately. | Use speed alone. | Fast search can conceal dangerous misses. |
| Rarity | Test low prevalence on novel grids. | Assume practice removes rare-target misses. | Rare targets remain disproportionately missed. |
| Coverage evidence | Use an overlay or pointer trace to show visited and revisited regions. | Assume the whole grid was scanned because the timer ran for long enough. | Elapsed time cannot reveal a skipped row or repeated quadrant. |
6 · Common mistakes
Spot the error and apply the correction
| Mistake | Fix |
|---|---|
| Search for “anything unusual”. | Study the exact target before each grid. |
| Jump around toward visually interesting items. | Cover rows or sectors systematically. |
| Search indefinitely or quit when bored. | Stop after the declared coverage and verification pass. |
| Use speed alone. | Count misses, false alarms and revisits separately. |
| Assume practice removes rare-target misses. | Test low prevalence on novel grids. |
| The pointer marks the target while searching, revealing likely answers during a later verification pass. | Use a separate coverage overlay and mark the final target location only after the search decision is committed. |
7 · Practice
Turn the steps into a usable skill
First session
- A helper builds and conceals A1–A4, B1–B4 and C1–C6 from the 8×8 recipe and folded coordinate key.
- Study the T template, choose a left-to-right row scan and state that absent means one full scan plus one verification pass.
- Run shuffled A1–A4, committing an exact row/column or absent answer before the key is opened for each grid.
- Trace one A grid on a clean overlay, mark the first skipped row or revisit and rehearse that path transition on shuffled B1–B4.
- After at least 48 hours, run shuffled C1–C6 without feedback first and compare the one-present/five-absent results with their declared prevalence.
Repeat plan
Use four to eight new grids once or twice weekly. Progress only after accuracy and false alarms are stable; vary prevalence or clutter one at a time.
Progress when
- Misses and revisits decline on novel grids.
- False alarms do not rise.
- The absent stopping rule is followed consistently.
Do not progress when
- Speed pressure increases misses.
- The target template or grid size changes without being recorded.
- The learner transfers the score to a safety-critical search.
8 · Check the result
Measure what changed
Sensitivity, miss and false-alarm rates on rare unfamiliar targets
How: On target-present grids, a hit requires the exact keyed row and column; an absent answer or wrong coordinate is a miss/localisation error. On absent grids, any marked location is a false alarm and absent is a correct rejection. Report hits divided by present grids and false alarms divided by absent grids, plus stopping time, revisits, skipped rows, first path break, prevalence and grid configuration.
Good result: Two novel sets show fewer misses or revisits without increased false alarms, using the same stopping rule.
This does not prove: Predeclare target class, prevalence, sensitivity, false alarms, response time and unfamiliar-scene transfer; keep speed–accuracy trade-offs visible.
Self-check
- Can you demonstrate “Choose a scan path”? The path covers the full grid once.
- Can you demonstrate “Commit target present”? One exact location is recorded.
- Can you demonstrate “Retest rare novel targets”? Prevalence and new-grid status are recorded.
- Can your coverage trace show the difference between a target miss in a visited cell and a target located in a skipped cell?
9 · Stop, adapt or get help
Keep the safety boundary practical
Stop and get help
- Stop for headache, eye strain, nausea or visual disturbance.
- Seek professional assessment for new everyday search failure, field loss or neglect symptoms.
- Do not use the fixture as clearance for radiology, security, driving or other consequential search.
Accessibility and adaptations
- Use larger grids with the same target/distractor relation as a labelled configuration.
- Use pointer, row guide, speech or switch response without adding a motor-speed requirement.
- Reduce visual clutter for instruction, then measure any clutter change separately.
10 · Evidence and limits
Why these instructions are here
- primary research
Primary research demonstrates a low-prevalence effect in visual search, supporting explicit miss and prevalence tracking.
Cognitive psychology: rare items often missed in visual searches - primary research
Primary research distinguishes contextual and perceptual learning in visual search, limiting broad transfer claims.
Dissociating electrophysiological correlates of contextual and perceptual learning in a visual search task
Limits
- Predeclare target class, prevalence, sensitivity, false alarms, response time and unfamiliar-scene transfer; keep speed–accuracy trade-offs visible.
- Unsupported claim: Photographic scanning.
- Unsupported claim: Never miss an anomaly.
- Unsupported claim: One game trains every search job.
- Grid improvement does not establish safe rare-target search in professional, medical or mobility settings.
Open the complete canonical research register
- Primary empirical supportLimiting / contraryCognitive psychology: rare items often missed in visual searches
J. M. Wolfe; T. S. Horowitz; N. M. Kenner · 2005 · Primary research
- Limiting / contraryRehabilitation of visuospatial neglect by prism adaptation: effects of a mild treatment regime. A randomised controlled trial
N. Vaes; G. Nys; C. Lafosse; L. Dereymaeker; K. Oostra; D. Hemelsoet; G. Vingerhoets · 2018 · Primary research
- Primary empirical supportLimiting / contraryTwo-stage perceptual learning to break visual crowding
Z. Zhu; Z. Fan; F. Fang · 2016 · Primary research
- Primary empirical supportLimiting / contraryDissociating electrophysiological correlates of contextual and perceptual learning in a visual search task
C. C. Le Dantec; A. R. Seitz · 2020 · Primary research
- Limiting / contraryOfficial boundary contextAeronautical Information Manual, Chapter 8: Medical Facts for Pilots
Federal Aviation Administration · 2026 · Official guidance
- Limiting / contraryAcute neglect rehabilitation using repetitive prism adaptation: a randomized placebo-controlled trial
G. M. Nys; E. H. de Haan; A. Kunneman; P. L. de Kort; H. C. Dijkerman · 2008 · Primary research
Read the complete evidence interpretation on the Power dossier.
Tutorial delivery controls
Learn, adapt, troubleshoot and resume
Progress is saved only in this browser on this device.
Step-by-step learner mode
Each activity includes its success check, a nearby accessible alternative and an “I’m stuck” correction path. Alternatives preserve the target where possible; when they change the task, Titan labels them as related rather than equivalent.
Study the exact template
Look at the target T and name how it differs from the L distractors.
A precise template reduces searching for a vague shape.
The learner identifies target and two distractors correctly.
I’m stuck on this step
Reset: Re-read this authored instruction — “Look at the target T and name how it differs from the L distractors.” — and its success check, then attempt only this step.
Possible snag: Search for “anything unusual”.
Correction: Study the exact target before each grid.
Stop / get help: Stop for headache, eye strain, nausea or visual disturbance.
Choose a scan path
Select rows, columns or quadrants and state the order before revealing the grid.
A systematic path reduces skipped regions and revisits.
The path covers the full grid once.
I’m stuck on this step
Reset: Re-read this authored instruction — “Select rows, columns or quadrants and state the order before revealing the grid.” — and its success check, then attempt only this step.
Possible snag: Jump around toward visually interesting items.
Correction: Cover rows or sectors systematically.
Stop / get help: Stop for headache, eye strain, nausea or visual disturbance.
Start the timer and scan
Move through the declared path at a controllable pace, pointing or tracking each region.
External tracking makes coverage visible.
The scan follows the path rather than jumping to salient items.
I’m stuck on this step
Reset: Re-read this authored instruction — “Move through the declared path at a controllable pace, pointing or tracking each region.” — and its success check, then attempt only this step.
Possible snag: The result from “Move through the declared path at a controllable pace, pointing or tracking each region.” does not yet meet this declared check: The scan follows the path rather than jumping to salient items.
Correction: Return to the start of “Start the timer and scan”, reduce complexity or pace, and repeat only the part needed to satisfy: “The scan follows the path rather than jumping to salient items.”
Stop / get help: Stop for headache, eye strain, nausea or visual disturbance.
Commit target present
If a target is found, mark its location and stop before checking.
A committed location distinguishes a hit from vague suspicion.
One exact location is recorded.
I’m stuck on this step
Reset: Re-read this authored instruction — “If a target is found, mark its location and stop before checking.” — and its success check, then attempt only this step.
Possible snag: The result from “If a target is found, mark its location and stop before checking.” does not yet meet this declared check: One exact location is recorded.
Correction: Return to the start of “Commit target present”, reduce complexity or pace, and repeat only the part needed to satisfy: “One exact location is recorded.”
Stop / get help: Stop for headache, eye strain, nausea or visual disturbance.
Apply the absent rule
If no target appears after one complete scan plus the predeclared verification pass, answer absent and stop.
Endless searching inflates time without eliminating misses.
Target-absent decisions use the same rule.
I’m stuck on this step
Reset: Re-read this authored instruction — “If no target appears after one complete scan plus the predeclared verification pass, answer absent and stop.” — and its success check, then attempt only this step.
Possible snag: Search indefinitely or quit when bored.
Correction: Stop after the declared coverage and verification pass.
Stop / get help: Stop for headache, eye strain, nausea or visual disturbance.
Classify and mark revisits
Use the key to record hit, miss, false alarm or correct rejection and count repeated regions.
Accuracy, bias and inefficient scanning are different errors.
Every grid has outcome, time and revisit count.
I’m stuck on this step
Reset: Re-read this authored instruction — “Use the key to record hit, miss, false alarm or correct rejection and count repeated regions.” — and its success check, then attempt only this step.
Possible snag: Use speed alone.
Correction: Count misses, false alarms and revisits separately.
Stop / get help: Stop for headache, eye strain, nausea or visual disturbance.
Retest rare novel targets
After practice, use new grids with the predeclared lower target prevalence and the same scan rule.
Low prevalence can increase misses and must be tested directly.
Prevalence and new-grid status are recorded.
I’m stuck on this step
Reset: Re-read this authored instruction — “After practice, use new grids with the predeclared lower target prevalence and the same scan rule.” — and its success check, then attempt only this step.
Possible snag: Assume practice removes rare-target misses.
Correction: Test low prevalence on novel grids.
Stop / get help: Stop for headache, eye strain, nausea or visual disturbance.
Draw a coverage trace
On a transparent overlay or duplicate grid, draw a light line through each inspected row or quadrant and put a dot where the eyes or pointer return to an earlier region. Keep this trace separate from the target answer.
A coverage trace distinguishes a missed target from an unvisited region and shows where the declared path breaks down.
Every sector has one pass mark, revisits have dots and the target answer remains unaltered by the trace.
I’m stuck on this step
Reset: Re-read this authored instruction — “On a transparent overlay or duplicate grid, draw a light line through each inspected row or quadrant and put a dot where the eyes or pointer return to an earlier region. Keep this trace separate from the target answer.” — and its success check, then attempt only this step.
Possible snag: The pointer marks the target while searching, revealing likely answers during a later verification pass.
Correction: Use a separate coverage overlay and mark the final target location only after the search decision is committed.
Stop / get help: Stop for headache, eye strain, nausea or visual disturbance.
Correct versus incorrect execution
These accessible process diagrams are built from the tutorial’s own right/wrong teaching. They are not anatomical illustrations and do not add technique beyond the canonical tutorial.
Study the exact target before each grid.
Search for “anything unusual”.
Cover rows or sectors systematically.
Jump around toward visually interesting items.
Stop after the declared coverage and verification pass.
Search indefinitely or quit when bored.
Count misses, false alarms and revisits separately.
Use speed alone.
Test low prevalence on novel grids.
Assume practice removes rare-target misses.
Use an overlay or pointer trace to show visited and revisited regions.
Assume the whole grid was scanned because the timer ran for long enough.
Method-structure checklist
10 of 10 structural checks present
- Ordered, Power-specific instructions — present
- Every activity has a success check — present
- Materials or supplied records are declared — present
- Measurement or assessment rule is present — present
- Tutorial-specific troubleshooting is present — present
- Stopping or escalation boundary is present — present
- Every activity has an adjacent alternative — present
- Correct-versus-incorrect comparison is present — present
- Evidence context is bound to the Power record — present
- Planning metadata is present — present
The method-readiness band and presence checklist assess tutorial presentation and are separate from evidence quality for the underlying Power. They are automated editorial aids, not human approval.
Manual editorial sign-off: Pending. This tutorial must not display a human-approved state until an identified editor signs the exact content hash.