Map Outlines Quiz

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Map outlines are simplified silhouettes that show a place’s boundary without any labels. A geography outline quiz turns those silhouettes into quick recognition practice, like learning a face from a sketch. The goal is to build shape memory so names come to mind faster when you see a blank map.

You choose what region set you want to study and how long you want the session to be, then each question shows one outline and a small set of possible names. After each choice, the session moves forward and your final score summarizes how many you recognized. If you use a seed, the same sequence can be repeated later for practice or shared with others.

For example, you might run a 20 question round on world countries before a trivia night and discover you confuse similar coastline shapes. Repeating the same seeded round a week later helps you see whether the confusing pairs are improving. When a mistake repeats, it is a hint to learn one distinguishing feature such as a peninsula or a border angle.

Outline recognition is only one part of geographic knowledge, and a correct guess does not prove you know where the place sits on the map. Tiny islands and sprawling countries with lots of coastline can also look deceptively similar when reduced to a single silhouette. If you need to study capitals or locations, pair this with a labeled map exercise and use this quiz for quick recall checks.

To keep sessions comparable, use the same set, the same question count, and the same seed when you are tracking progress over time. Short rounds can swing from luck, so treat a small jump as a reason to repeat rather than a final verdict.

Technical Details:

The quiz measures outline recognition accuracy for a chosen pool of regions. Each question is a classification task where one outline corresponds to one correct name, and performance is tracked as counts and percentages.

Scoring is based on a simple tally of correct answers, then transformed into a whole number percentage for quick interpretation. Progress uses the same idea, showing how much of the session you have already answered.

Results do not come with built in grade bands, because outline difficulty varies by region and by how many questions you choose. A higher percentage usually means stronger recognition, but small sessions can be noisy, especially when a few tricky shapes cluster together.

To make comparisons fair, the app can use a seed that drives a deterministic pseudo random number generator (PRNG). With the same seed and the same map dataset, the question order and option order are repeatable.

Scoring formulas

P_{c} = round (100 \times \frac{S}{N})

P_{w} = 100 - P_{c}

P_{p} = round (100 \times \frac{A}{N})

Symbols used in quiz scoring and outline rendering
Symbol	Meaning	Unit or Datatype	Source
`N`	Total number of questions in the session	integer	Derived
`S`	Score counted as correct answers	integer	Derived
`P_c`	Correct percentage rounded to a whole number	percent	Derived
`P_w`	Wrong percentage computed from `100 − P_c`	percent	Derived
`A`	Answered count used for progress	integer	Derived
`P_p`	Progress percentage rounded to a whole number	percent	Derived
`W`	Outline frame width used for normalization	pixels	Constant
`H`	Outline frame height used for normalization	pixels	Constant
`pad`	Padding around the outline within the frame	pixels	Constant

Worked example

Assume a 20 question session with 14 correct answers, and you have just answered question 6.

N = 20, S = 14

P_{c} = round (100 \times \frac{14}{20}) = 70

P_{w} = 100 - 70 = 30

A = 6, P_{p} = round (100 \times \frac{6}{20}) = 30

Interpretation: 70 percent correct suggests strong recognition in this round, and 30 percent progress means you are about one third through the session.

Question generation pipeline

Load a fixed map dataset, then extract a pool of named regions.
Optionally filter the pool, for example to remove territories from a states only set.
Shuffle the pool with the seeded PRNG, then take the first N items without repeats.
For each chosen region, pick up to three distinct distractor names from the full pool.
Shuffle the four options and record the index of the correct answer.

Outline normalization and rendering

Each region outline is normalized into a consistent frame so shapes remain comparable even when source coordinates differ. The app computes a bounding box for all polygon points, applies a uniform scale to fit a 520 by 320 frame with padding, and then renders the result as an SVG data URI.

\begin{matrix} scale & = & min (\frac{W - 2 pad}{dx}, \frac{H - 2 pad}{dy}) \\ x′ & = & (x - minX) scale + offX \\ y′ & = & (maxY - y) scale + offY \end{matrix}

Parameters

User controlled parameters and their effects
Parameter	Meaning	Unit or Datatype	Typical Range	Sensitivity	Notes
Set	Which region family defines the pool	enum	States, states and territories, countries	High	Pool size and difficulty shift by set.
Question count	How many distinct regions appear in one session	integer	10 to 56	High	Only allowed values are offered and values are clamped to pool size.
Seed	Text used to drive deterministic shuffles	string	Optional	Medium	Same seed reproduces the same question and option order.
Options per question	Answer choices shown for one outline	count	4	Low	One correct option plus up to three distractors.

Key constants

Constants that affect rendering and downloads
Constant	Value	Unit	Source	Notes
Outline frame width (`W`)	520	px	Constant	Used for consistent outline sizing.
Outline frame height (`H`)	320	px	Constant	Used for consistent outline sizing.
Outline padding (`pad`)	18	px	Constant	Prevents outlines touching the frame border.
Chart export pixel ratio	2	multiplier	Constant	Improves image sharpness for downloads.

Units, precision, and rounding

Progress and correctness percentages are rounded to the nearest whole percent.
Outline path coordinates are formatted to two decimal places, then trailing zeros are removed.
The chart summary CSV formats the correctness percentage with two decimal places.

Validation and bounds

Input validation and error surfaces
Field	Type	Min	Max	Step or Pattern	Error Text
Set	enum	—	—	Must match a supported set id	Unknown map data source.
Question count	integer	1	Pool size	Allowed list varies by set	Clamped to the nearest allowed value
Seed	string	—	—	Any text, optional	—

Inputs and outputs

Accepted inputs and available outputs
Input	Accepted Families	Output	Encoding or Precision	Rounding
Quiz configuration	Set id, question count, optional seed	Deterministic question and option order	UTF 16 strings internally	Question count rounded to an integer
Answers	One selection per question	Score, correct percent, wrong percent	Whole number percent display	Nearest integer percent
Results table	Per question row data	CSV download and copy	Comma separated text with header row	No rounding beyond displayed values
Session summary	Set, source info, seed, rows	JSON download and copy	Pretty printed with two space indentation	Correct percent is a whole number
Study report	Results rows and summary lines	DOCX download	Title, subtitle, and a table of results	Percent shown as whole number
Answer breakdown	Correct and incorrect counts	Pie chart plus image and CSV downloads	PNG, WebP, JPEG, and a small metrics CSV	Chart CSV percent to two decimals

Randomness, seeds, and reproducibility

When a seed is provided, the PRNG produces the same sequence of random numbers each time. That sequence drives a Fisher Yates shuffle used for both question order and option order, which makes the session reproducible for comparisons.

Question selection is without replacement, so a region appears at most once per session.
Distractors aim to be distinct names sampled from the full pool.
When the seed is blank, a time based seed is created from the current clock and random noise.
The PRNG is designed for repeatable shuffles, not for cryptographic security.

Networking and storage behavior

The browser fetches one of two fixed map datasets and prefers cached responses when available.
Outlines are converted into in memory features, then individual SVG data URIs are cached per region code.
No answers are sent to a server by this script, and the session resets when the page is reloaded.

Performance and complexity

Building the question list is linear in pool size for the shuffle, plus linear in question count.
Rendering an outline is linear in the number of polygon points, then cached for later reuse.
Chart rendering is constant time relative to question count because it only uses totals.

Security considerations

Map datasets are external inputs, so treat names and geometry as untrusted data in custom forks.
SVG strings are URI encoded before display, reducing injection risk in the image source.
JSON is rendered as highlighted HTML, so escaping must remain correct in the highlighter.
Seeds should not include sensitive text if you plan to share them widely.

Assumptions and limitations

Scores reflect recognition of silhouettes, not knowledge of capitals, locations, or borders on a labeled map.
Difficulty varies by region, and coastlines and islands can make shapes ambiguous.
Short sessions can fluctuate, especially when only a few mistakes change the percentage.
Reproducibility assumes the same map dataset and naming remain available and unchanged.
Question selection avoids repeats within one session, but a new session may revisit the same regions.
The PRNG is suitable for practice shuffles, not for security or gambling use.
Heads-up Very small pools can reduce choice variety, and building distractors expects multiple distinct names.
Chart exports summarize correct versus incorrect only, and they do not show per region difficulty.

Edge cases and error sources

Network failures can prevent map datasets from loading, producing a load error and an empty pool.
Unexpected dataset structure can stop parsing if the expected object name is missing.
Features without an id are skipped and will never appear as questions.
Features with missing names fall back to the id string or the label Unknown.
Non finite coordinate points are ignored when computing the bounding box.
Polygons with fewer than two points are skipped and may render as a blank outline.
Closed rings that repeat the first point at the end are trimmed to avoid duplicate segments.
Multi polygon shapes are flattened into multiple rings and rely on even odd fill for holes.
If a pool ever had only two distinct names, distractor selection could stall while seeking new unique picks.
Downloaded chart image conversion to WebP or JPEG can fail in environments without support.
Percentage rounding can hide small changes, for example 69.6 and 70.4 both display as 70.
Cached map data can become stale or be cleared, changing what is available between sessions.

Scientific and standards backing

Geometry concepts follow GeoJSON as defined in RFC 7946, and outlines are rendered using the SVG specification. Randomization uses the Fisher Yates shuffle pattern with a deterministic PRNG for repeatable draws.

Privacy and compliance

Map datasets are fetched directly by the browser from public CDNs while answers stay local and exports are generated on device, and outcomes are purely random and have no monetary value.

Step by Step Guide:

Map outline practice works best when you run a focused round, review what you missed, and then repeat with a consistent setup.

Pick a Quiz set that matches what you want to learn.
Select a Number of questions that fits your time.
Optionally enter a Random seed to make the shuffle repeatable.
Answer each outline by choosing the name that matches the silhouette.
Review your score, scan the per question results, and retake with the same or a new seed.

Example

Choose world countries, set 20 questions, and use the seed geo-quiz-2026. If you score 14 correct, your result is 70 percent correct and 30 percent wrong.

Use the same seed when you want to measure improvement on the same material.

Switch to a new seed when you want broader coverage and fewer repeats across sessions.

After a miss, look for one distinctive feature and say it out loud before the next round.

Pro tip: keep a short list of your top five confusing outlines and revisit them every few sessions with a fresh seed.

Features:

Multiple region pools, including United States states and world countries.
Optional seeded shuffles for repeatable question order and answer options.
One session, one score, with both correct and wrong percentages.
Per question review so you can spot repeated confusions.
A simple answer breakdown chart for quick summaries.
Downloadable results and a portable study report for later review.

FAQ:

Is my data stored?

Your answers are kept in memory for the current session and are not submitted by this script. The browser does fetch map datasets, then everything else is generated locally. Reloading the page resets the session.

How accurate is scoring?

Scoring is exact for what you selected, each correct choice adds one point and the percentage is rounded to a whole number. What it does not measure is deeper geographic knowledge like capitals or locations. Treat the score as a practice signal, not a formal grade.

What can I download?

You can copy or download a results table, download a JSON session summary, export a DOCX study report, and download the answer breakdown chart as an image or as a small metrics CSV. Downloads are created from your current session data.

Can I use it offline?

The quiz needs to load a map dataset first, so an initial connection is required. After that, your browser may be able to reuse cached map data depending on its cache settings. If the dataset cannot be loaded, the pool size will be zero and the quiz cannot start.

Is there a license?

This package does not display licensing terms in the interface or metadata beyond its name and tags. If you need redistribution rights or commercial terms, confirm them with the site or repository that ships this tool.

How do I repeat a quiz?

Use the same seed, the same set, and the same question count. The seeded PRNG drives both the question shuffle and the option shuffle, so matching inputs produce the same session structure. This is useful for before and after practice checks.

What is a borderline score?

There are no built in thresholds, so borderline is about your goal and the number of questions. If you are near your personal target, run another round with the same setup to reduce luck effects. For four options per question, repeated results near 25 percent suggest guessing rather than recognition.

Troubleshooting:

If the pool size is zero, change the set or check your connection and reload.
If outlines appear blank, try a different question, some shapes may fail to render when geometry is missing.
If you cannot start, ensure map data has finished loading and no load error is shown.
If the percentage feels off, remember it is rounded to a whole number for display.
If your repeated seed does not match a friend’s session, confirm you chose the same set and question count.
If chart downloads fail, try a different image format or download the chart CSV instead.

Blocking issue: map data will not load

If you see a map data load error, the quiz cannot build a pool of regions. Reload the page, allow the browser to fetch external datasets, and try again.

Advanced Tips:

Tip Use one fixed seed as your weekly benchmark for a stable comparison.
Tip Increase question count when you want the percentage to be less sensitive to luck.
Tip Track your most common confusions and study them as pairs rather than alone.
Tip Alternate between a repeatable seed for measurement and a fresh seed for coverage.
Tip When you miss, describe one feature in plain words before moving on.
Tip Use exports as a study log, then revisit only the missed items next time.

Glossary:

Outline: A silhouette of a region boundary without labels.
Pool: The full list of regions available for questions.
Seed: Text that makes shuffles repeatable across sessions.
PRNG: Pseudo random number generator used for deterministic shuffles.
Distractor: An incorrect option designed to be plausible.
Correct percent: Rounded percentage of questions answered correctly.
TopoJSON: A compact topology based map format used as input.
SVG data URI: An encoded SVG image string used to display outlines.

Map Outlines Quiz

Your Score

{{ questionHeading }}

Technical Details:

Scoring formulas

Question generation pipeline

Outline normalization and rendering

Parameters

Key constants

Units, precision, and rounding

Validation and bounds

Inputs and outputs

Randomness, seeds, and reproducibility

Networking and storage behavior

Performance and complexity

Security considerations

Assumptions and limitations

Edge cases and error sources

Scientific and standards backing

Privacy and compliance

Step by Step Guide:

Features:

FAQ:

Troubleshooting:

Advanced Tips:

Glossary:

Map Outlines Quiz

Your Score

{{ questionHeading }}

Introduction:

Technical Details:

Scoring formulas

Question generation pipeline

Outline normalization and rendering

Parameters

Key constants

Units, precision, and rounding

Validation and bounds

Inputs and outputs

Randomness, seeds, and reproducibility

Networking and storage behavior

Performance and complexity

Security considerations

Assumptions and limitations

Edge cases and error sources

Scientific and standards backing

Privacy and compliance

Step by Step Guide:

Features:

FAQ:

Troubleshooting:

Advanced Tips:

Glossary: