What is Primary 6 Vocabulary | Examples, Non-Examples and Concept Boundaries for Precise Word Meaning

Primary 6 vocabulary concept boundaries are the invisible lines that separate a word’s correct uses from tempting near-misses. Families searching for Grade 6 vocabulary examples and non-examples, semantic features, concept definition, how to know what a word really means, near synonyms and word meaning boundaries are often confronting the same problem: a learner can repeat a definition but still apply the word too broadly.

A useful definition tells learners what a word means; examples and non-examples show where the meaning stops. Content-area vocabulary guidance explicitly recommends modelling non-examples because context and word parts do not always work mechanically. At Primary 6, this matters for pairs such as reluctant/unable, confident/arrogant, evidence/example, significant/large and efficient/effective, where overlapping features create attractive mistakes.

This guide builds a concept-boundary system for Grade 6 vocabulary using defining features, examples, near non-examples, semantic dimensions and contrast sets. It explains how to distinguish central cases from edge cases, how to test whether a synonym really fits, how to build learner-friendly definitions that exclude wrong uses, and how to use boundary work in comprehension and writing. The goal is not simply to know what a word points to, but to know when not to use it.

The 50-second router

1. State the central meaning.
2. Name one defining feature.
3. Give a clear example.
4. Give a tempting near non-example.
5. Explain the single feature that separates them.
6. Test the word in a fresh context.

Definitions need exclusion power

A definition is useful when it rules out wrong cases as well as including correct ones. “Reluctant means not wanting to do something” excludes inability, which is a different problem.

For the wider learning principle, use How Concept Boundaries Work and the Primary 6 Semantic Mapping owner. This child specialises the method for word meaning.

Near non-examples reveal the border

A wildly wrong example is easy to reject and teaches little. A near non-example forces the learner to identify the precise feature that controls the category.

For the wider learning principle, use How Concept Boundaries Work and the Primary 6 Semantic Mapping owner. This child specialises the method for word meaning.

Semantic features can be compared

Words can differ by intensity, duration, intention, certainty, evaluation, formality or cause. Naming the dimension turns a vague distinction into a usable rule.

For the wider learning principle, use How Concept Boundaries Work and the Primary 6 Semantic Mapping owner. This child specialises the method for word meaning.

Synonym sets are really contrast sets

Near-synonyms become educational when learners explain the difference rather than memorising them as replacements.

For the wider learning principle, use How Concept Boundaries Work and the Primary 6 Semantic Mapping owner. This child specialises the method for word meaning.

Antonyms reveal one axis of meaning

A good opposite clarifies the dimension being measured. The opposite of relevant is about connection to the topic, not general quality.

For the wider learning principle, use How Concept Boundaries Work and the Primary 6 Semantic Mapping owner. This child specialises the method for word meaning.

Multiple contexts test the boundary

A word that works in one memorised sentence may still be poorly understood. Change topic, subject and genre while preserving the semantic decision.

For the wider learning principle, use How Concept Boundaries Work and the Primary 6 Semantic Mapping owner. This child specialises the method for word meaning.

Concept boundaries improve comprehension

Readers can eliminate answer options that are broadly related but violate one crucial semantic feature.

For the wider learning principle, use How Concept Boundaries Work and the Primary 6 Semantic Mapping owner. This child specialises the method for word meaning.

Concept boundaries improve writing

Writers choose among near-neighbours more accurately when they understand what each word adds or excludes.

For the wider learning principle, use How Concept Boundaries Work and the Primary 6 Semantic Mapping owner. This child specialises the method for word meaning.

Edge cases are useful after the core is stable

Ambiguous or borderline examples can deepen understanding, but introducing them too early can blur a fragile concept.

For the wider learning principle, use How Concept Boundaries Work and the Primary 6 Semantic Mapping owner. This child specialises the method for word meaning.

Learners should verbalise the boundary

“This is X because…, but that is not X because…” forces comparison and exposes hidden misconceptions.

For the wider learning principle, use How Concept Boundaries Work and the Primary 6 Semantic Mapping owner. This child specialises the method for word meaning.

Word families can preserve or shift boundaries

Related forms often share a concept but differ in grammatical role and sometimes in conventional usage. Semantic family does not mean sentence-level interchangeability.

For the wider learning principle, use How Concept Boundaries Work and the Primary 6 Semantic Mapping owner. This child specialises the method for word meaning.

Boundary knowledge is a form of depth

Vocabulary depth includes knowing associations, contrasts, multiple senses and constraints. A learner who can reject a near-miss has richer knowledge than one who can only recite a definition.

For the wider learning principle, use How Concept Boundaries Work and the Primary 6 Semantic Mapping owner. This child specialises the method for word meaning.

The five-part boundary card

Meaning

One short learner-friendly definition.

Must-have feature

What must be true for the word to fit?

Example

A clear case.

Near non-example

A tempting case that fails one feature.

Decision sentence

Explain why one belongs and the other does not.

One hundred and fifteen concept-boundary laboratories

Boundary Lab 1: analyse — example versus near non-example

A learner who knows the base word but not the derived form is learning analyse in a narrative passage about environmental change. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 2: relevant — example versus near non-example

A learner who repairs spelling but misses a meaning error is learning relevant in a Mathematics word problem about friendship. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 3: classify — example versus near non-example

A learner who uses one memorised sentence only is learning classify in a continuous-writing paragraph about weather. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 4: precision — example versus near non-example

A learner who copies teacher correction without understanding it is learning precision in a school announcement about teamwork. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 5: similar — example versus near non-example

A learner who knows the base word but not the derived form is learning similar in a textbook section about sports. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 6: validity — example versus near non-example

A learner who repairs spelling but misses a meaning error is learning validity in a peer explanation about inventions. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 7: argument — example versus near non-example

A learner who uses one memorised sentence only is learning argument in a documentary extract about digital safety. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 8: context — example versus near non-example

A learner who copies teacher correction without understanding it is learning context in an informational passage about technology. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 9: inference — example versus near non-example

A learner who knows the base word but not the derived form is learning inference in an oral response about community service. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 10: retain — example versus near non-example

A learner who repairs spelling but misses a meaning error is learning retain in a listening task about healthy habits. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 11: justify — example versus near non-example

A learner who uses one memorised sentence only is learning justify in a graph explanation about biodiversity. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 12: observe — example versus near non-example

A learner who copies teacher correction without understanding it is learning observe in a digital article about media literacy. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 13: response — example versus near non-example

A learner who knows the base word but not the derived form is learning response in a Secondary 1 preview text about transport. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 14: construct — example versus near non-example

A learner who repairs spelling but misses a meaning error is learning construct in a class discussion about public spaces. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 15: efficiency — example versus near non-example

A learner who uses one memorised sentence only is learning efficiency in a Science explanation about energy. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 16: confident — example versus near non-example

A learner who copies teacher correction without understanding it is learning confident in a situational-writing email about water conservation. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 17: cause — example versus near non-example

A learner who knows the base word but not the derived form is learning cause in a news report about financial decisions. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 18: sequence — example versus near non-example

A learner who repairs spelling but misses a meaning error is learning sequence in a project reflection about learning habits. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 19: adapt — example versus near non-example

A learner who uses one memorised sentence only is learning adapt in a debate about school rules. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 20: evaluate — example versus near non-example

A learner who copies teacher correction without understanding it is learning evaluate in a revision task about food systems. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 21: comparison — example versus near non-example

A learner who knows the base word but not the derived form is learning comparison in a narrative passage about environmental change. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 22: explanation — example versus near non-example

A learner who repairs spelling but misses a meaning error is learning explanation in a Mathematics word problem about friendship. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 23: appropriate — example versus near non-example

A learner who uses one memorised sentence only is learning appropriate in a continuous-writing paragraph about weather. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 24: influential — example versus near non-example

A learner who copies teacher correction without understanding it is learning influential in a school announcement about teamwork. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 25: probable — example versus near non-example

A learner who knows the base word but not the derived form is learning probable in a textbook section about sports. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 26: process — example versus near non-example

A learner who repairs spelling but misses a meaning error is learning process in a peer explanation about inventions. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 27: relationship — example versus near non-example

A learner who uses one memorised sentence only is learning relationship in a documentary extract about digital safety. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 28: describe — example versus near non-example

A learner who copies teacher correction without understanding it is learning describe in an informational passage about technology. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 29: retrieval — example versus near non-example

A learner who knows the base word but not the derived form is learning retrieval in an oral response about community service. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 30: interpretation — example versus near non-example

A learner who repairs spelling but misses a meaning error is learning interpretation in a listening task about healthy habits. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 31: prediction — example versus near non-example

A learner who uses one memorised sentence only is learning prediction in a graph explanation about biodiversity. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 32: precise — example versus near non-example

A learner who copies teacher correction without understanding it is learning precise in a digital article about media literacy. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 33: difference — example versus near non-example

A learner who knows the base word but not the derived form is learning difference in a Secondary 1 preview text about transport. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 34: valid — example versus near non-example

A learner who repairs spelling but misses a meaning error is learning valid in a class discussion about public spaces. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 35: claim — example versus near non-example

A learner who uses one memorised sentence only is learning claim in a Science explanation about energy. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 36: source — example versus near non-example

A learner who copies teacher correction without understanding it is learning source in a situational-writing email about water conservation. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 37: infer — example versus near non-example

A learner who knows the base word but not the derived form is learning infer in a news report about financial decisions. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 38: resolution — example versus near non-example

A learner who repairs spelling but misses a meaning error is learning resolution in a project reflection about learning habits. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 39: significance — example versus near non-example

A learner who uses one memorised sentence only is learning significance in a debate about school rules. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 40: consequential — example versus near non-example

A learner who copies teacher correction without understanding it is learning consequential in a revision task about food systems. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 41: respond — example versus near non-example

A learner who knows the base word but not the derived form is learning respond in a narrative passage about environmental change. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 42: contribution — example versus near non-example

A learner who repairs spelling but misses a meaning error is learning contribution in a Mathematics word problem about friendship. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 43: efficient — example versus near non-example

A learner who uses one memorised sentence only is learning efficient in a continuous-writing paragraph about weather. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 44: reluctance — example versus near non-example

A learner who copies teacher correction without understanding it is learning reluctance in a school announcement about teamwork. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 45: result — example versus near non-example

A learner who knows the base word but not the derived form is learning result in a textbook section about sports. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 46: category — example versus near non-example

A learner who repairs spelling but misses a meaning error is learning category in a peer explanation about inventions. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 47: demonstration — example versus near non-example

A learner who uses one memorised sentence only is learning demonstration in a documentary extract about digital safety. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 48: analytical — example versus near non-example

A learner who copies teacher correction without understanding it is learning analytical in an informational passage about technology. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 49: compare — example versus near non-example

A learner who knows the base word but not the derived form is learning compare in an oral response about community service. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 50: explain — example versus near non-example

A learner who repairs spelling but misses a meaning error is learning explain in a listening task about healthy habits. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 51: logic — example versus near non-example

A learner who uses one memorised sentence only is learning logic in a graph explanation about biodiversity. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 52: influence — example versus near non-example

A learner who copies teacher correction without understanding it is learning influence in a digital article about media literacy. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 53: possibility — example versus near non-example

A learner who knows the base word but not the derived form is learning possibility in a Secondary 1 preview text about transport. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 54: factor — example versus near non-example

A learner who repairs spelling but misses a meaning error is learning factor in a class discussion about public spaces. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 55: pattern — example versus near non-example

A learner who uses one memorised sentence only is learning pattern in a Science explanation about energy. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 56: conclusion — example versus near non-example

A learner who copies teacher correction without understanding it is learning conclusion in a situational-writing email about water conservation. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 57: retrieve — example versus near non-example

A learner who knows the base word but not the derived form is learning retrieve in a news report about financial decisions. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 58: interpret — example versus near non-example

A learner who repairs spelling but misses a meaning error is learning interpret in a project reflection about learning habits. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 59: predict — example versus near non-example

A learner who uses one memorised sentence only is learning predict in a debate about school rules. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 60: accuracy — example versus near non-example

A learner who copies teacher correction without understanding it is learning accuracy in a revision task about food systems. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 61: differentiate — example versus near non-example

A learner who knows the base word but not the derived form is learning differentiate in a narrative passage about environmental change. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 62: reliability — example versus near non-example

A learner who repairs spelling but misses a meaning error is learning reliability in a Mathematics word problem about friendship. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 63: evidence — example versus near non-example

A learner who uses one memorised sentence only is learning evidence in a continuous-writing paragraph about weather. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 64: support — example versus near non-example

A learner who copies teacher correction without understanding it is learning support in a school announcement about teamwork. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 65: general — example versus near non-example

A learner who knows the base word but not the derived form is learning general in a textbook section about sports. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 66: resolve — example versus near non-example

A learner who repairs spelling but misses a meaning error is learning resolve in a peer explanation about inventions. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 67: significant — example versus near non-example

A learner who uses one memorised sentence only is learning significant in a documentary extract about digital safety. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 68: consequence — example versus near non-example

A learner who copies teacher correction without understanding it is learning consequence in an informational passage about technology. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 69: decision — example versus near non-example

A learner who knows the base word but not the derived form is learning decision in an oral response about community service. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 70: contribute — example versus near non-example

A learner who repairs spelling but misses a meaning error is learning contribute in a listening task about healthy habits. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 71: effectiveness — example versus near non-example

A learner who uses one memorised sentence only is learning effectiveness in a graph explanation about biodiversity. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 72: reluctant — example versus near non-example

A learner who copies teacher correction without understanding it is learning reluctant in a digital article about media literacy. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 73: strategy — example versus near non-example

A learner who knows the base word but not the derived form is learning strategy in a Secondary 1 preview text about transport. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 74: function — example versus near non-example

A learner who repairs spelling but misses a meaning error is learning function in a class discussion about public spaces. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 75: demonstrate — example versus near non-example

A learner who uses one memorised sentence only is learning demonstrate in a Science explanation about energy. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 76: analysis — example versus near non-example

A learner who copies teacher correction without understanding it is learning analysis in a situational-writing email about water conservation. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 77: relevance — example versus near non-example

A learner who knows the base word but not the derived form is learning relevance in a news report about financial decisions. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 78: classification — example versus near non-example

A learner who repairs spelling but misses a meaning error is learning classification in a project reflection about learning habits. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 79: logical — example versus near non-example

A learner who uses one memorised sentence only is learning logical in a debate about school rules. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 80: similarity — example versus near non-example

A learner who copies teacher correction without understanding it is learning similarity in a revision task about food systems. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 81: possible — example versus near non-example

A learner who knows the base word but not the derived form is learning possible in a narrative passage about environmental change. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 82: reason — example versus near non-example

A learner who repairs spelling but misses a meaning error is learning reason in a Mathematics word problem about friendship. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 83: criterion — example versus near non-example

A learner who uses one memorised sentence only is learning criterion in a continuous-writing paragraph about weather. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 84: conclude — example versus near non-example

A learner who copies teacher correction without understanding it is learning conclude in a school announcement about teamwork. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 85: retention — example versus near non-example

A learner who knows the base word but not the derived form is learning retention in a textbook section about sports. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 86: justification — example versus near non-example

A learner who repairs spelling but misses a meaning error is learning justification in a peer explanation about inventions. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 87: observation — example versus near non-example

A learner who uses one memorised sentence only is learning observation in a documentary extract about digital safety. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 88: accurate — example versus near non-example

A learner who copies teacher correction without understanding it is learning accurate in an informational passage about technology. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 89: construction — example versus near non-example

A learner who knows the base word but not the derived form is learning construction in an oral response about community service. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 90: reliable — example versus near non-example

A learner who repairs spelling but misses a meaning error is learning reliable in a listening task about healthy habits. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 91: confidence — example versus near non-example

A learner who uses one memorised sentence only is learning confidence in a graph explanation about biodiversity. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 92: effect — example versus near non-example

A learner who copies teacher correction without understanding it is learning effect in a digital article about media literacy. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 93: specific — example versus near non-example

A learner who knows the base word but not the derived form is learning specific in a Secondary 1 preview text about transport. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 94: adaptation — example versus near non-example

A learner who repairs spelling but misses a meaning error is learning adaptation in a class discussion about public spaces. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 95: evaluation — example versus near non-example

A learner who uses one memorised sentence only is learning evaluation in a Science explanation about energy. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 96: contrast — example versus near non-example

A learner who copies teacher correction without understanding it is learning contrast in a situational-writing email about water conservation. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 97: decide — example versus near non-example

A learner who knows the base word but not the derived form is learning decide in a news report about financial decisions. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 98: appropriateness — example versus near non-example

A learner who repairs spelling but misses a meaning error is learning appropriateness in a project reflection about learning habits. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 99: effective — example versus near non-example

A learner who uses one memorised sentence only is learning effective in a debate about school rules. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 100: probability — example versus near non-example

A learner who copies teacher correction without understanding it is learning probability in a revision task about food systems. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 101: method — example versus near non-example

A learner who knows the base word but not the derived form is learning method in a narrative passage about environmental change. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 102: structure — example versus near non-example

A learner who repairs spelling but misses a meaning error is learning structure in a Mathematics word problem about friendship. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 103: description — example versus near non-example

A learner who uses one memorised sentence only is learning description in a continuous-writing paragraph about weather. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 104: analyse — example versus near non-example

A learner who copies teacher correction without understanding it is learning analyse in a school announcement about teamwork. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 105: relevant — example versus near non-example

A learner who knows the base word but not the derived form is learning relevant in a textbook section about sports. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 106: classify — example versus near non-example

A learner who repairs spelling but misses a meaning error is learning classify in a peer explanation about inventions. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 107: precision — example versus near non-example

A learner who uses one memorised sentence only is learning precision in a documentary extract about digital safety. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 108: similar — example versus near non-example

A learner who copies teacher correction without understanding it is learning similar in an informational passage about technology. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 109: validity — example versus near non-example

A learner who knows the base word but not the derived form is learning validity in an oral response about community service. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 110: argument — example versus near non-example

A learner who repairs spelling but misses a meaning error is learning argument in a listening task about healthy habits. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 111: context — example versus near non-example

A learner who uses one memorised sentence only is learning context in a graph explanation about biodiversity. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 112: inference — example versus near non-example

A learner who copies teacher correction without understanding it is learning inference in a digital article about media literacy. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 113: retain — example versus near non-example

A learner who knows the base word but not the derived form is learning retain in a Secondary 1 preview text about transport. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 114: justify — example versus near non-example

A learner who repairs spelling but misses a meaning error is learning justify in a class discussion about public spaces. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Boundary Lab 115: observe — example versus near non-example

A learner who uses one memorised sentence only is learning observe in a Science explanation about energy. Give a short learner-friendly meaning, then identify one semantic feature that must be present. Create a clear example and a near non-example that differs by only one important feature. Ask the learner to decide which is valid and explain why. Add a near-synonym and compare intensity, intention, certainty, register or scope where relevant. Then move the word into a new topic and repeat the decision without the original examples. Finish by asking the learner to invent a new near non-example. The word is becoming precise when the learner can defend rejection as confidently as acceptance.

Where this fits in the eduKate Primary 6 vocabulary architecture

This article is a specialist child of the Primary 6 vocabulary apex. It does not replace the Top 100 Primary 6 high-utility word-bank owner or the Primary 6 vocabulary practice owner. The master Vocabulary router and Vocabulary Learning Hub remain the wider routes across vocabulary levels and problems.

The lane stays add-only. Each child owns one teaching and search intent, links to existing specialist owners where they are deeper, and avoids rewriting protected pages.

Sources and further reading

• IES — Project DIMES: Diagnostic Instrument for Morphology of Elementary Students.
• IES — Word Knowledge Instruction and Grade 5 Writing.
• IES PRISMS — Vocabulary and Morphology for Grades 6–8.
• IES — Evaluating, Revising and Editing Writing.
• IES What Works Clearinghouse — Teaching Elementary School Students to Be Effective Writers.
• Reading Rockets — Content Area Vocabulary Learning.
• Reading Rockets — Vocabulary Instructional Guidelines and Classroom Examples.
• Reading Rockets — Vocabulary in Practice.
• MOE Singapore — English Language Syllabus 2020 Primary.
• SEAB — 2026 PSLE English Language syllabus.

Extended Primary 6 application fieldbook

Fieldbook 1: analyse in a narrative passage

A learner who knows the base word but not the derived form studies analyse in a narrative passage about environmental change. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 2: classification in a project reflection

A learner who repairs spelling but misses a meaning error studies classification in a project reflection about media literacy. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 3: influence in a Science explanation

A learner who uses one memorised sentence only studies influence in a Science explanation about weather. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 4: process in a digital article

A learner who copies teacher correction without understanding it studies process in a digital article about public spaces. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 5: description in an oral response

A learner who knows the base word but not the derived form studies description in an oral response about sports. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 6: relevance in a peer explanation

A learner who repairs spelling but misses a meaning error studies relevance in a peer explanation about water conservation. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 7: logic in a continuous-writing paragraph

A learner who uses one memorised sentence only studies logic in a continuous-writing paragraph about digital safety. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 8: probable in a revision task

A learner who copies teacher correction without understanding it studies probable in a revision task about learning habits. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 9: structure in a news report

A learner who knows the base word but not the derived form studies structure in a news report about community service. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 10: analysis in a class discussion

A learner who repairs spelling but misses a meaning error studies analysis in a class discussion about food systems. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 11: explain in a graph explanation

A learner who uses one memorised sentence only studies explain in a graph explanation about biodiversity. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 12: influential in an informational passage

A learner who copies teacher correction without understanding it studies influential in an informational passage about friendship. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 13: method in a textbook section

A learner who knows the base word but not the derived form studies method in a textbook section about transport. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 14: demonstrate in a Mathematics word problem

A learner who repairs spelling but misses a meaning error studies demonstrate in a Mathematics word problem about teamwork. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 15: compare in a debate

A learner who uses one memorised sentence only studies compare in a debate about energy. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 16: appropriate in a situational-writing email

A learner who copies teacher correction without understanding it studies appropriate in a situational-writing email about inventions. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 17: probability in a Secondary 1 preview text

A learner who knows the base word but not the derived form studies probability in a Secondary 1 preview text about financial decisions. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 18: function in a listening task

A learner who repairs spelling but misses a meaning error studies function in a listening task about technology. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 19: analytical in a documentary extract

A learner who uses one memorised sentence only studies analytical in a documentary extract about school rules. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 20: explanation in a school announcement

A learner who copies teacher correction without understanding it studies explanation in a school announcement about healthy habits. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 21: effective in a narrative passage

A learner who knows the base word but not the derived form studies effective in a narrative passage about environmental change. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 22: strategy in a project reflection

A learner who repairs spelling but misses a meaning error studies strategy in a project reflection about media literacy. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 23: demonstration in a Science explanation

A learner who uses one memorised sentence only studies demonstration in a Science explanation about weather. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 24: comparison in a digital article

A learner who copies teacher correction without understanding it studies comparison in a digital article about public spaces. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 25: appropriateness in an oral response

A learner who knows the base word but not the derived form studies appropriateness in an oral response about sports. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 26: reluctant in a peer explanation

A learner who repairs spelling but misses a meaning error studies reluctant in a peer explanation about water conservation. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 27: category in a continuous-writing paragraph

A learner who uses one memorised sentence only studies category in a continuous-writing paragraph about digital safety. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 28: evaluate in a revision task

A learner who copies teacher correction without understanding it studies evaluate in a revision task about learning habits. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 29: decide in a news report

A learner who knows the base word but not the derived form studies decide in a news report about community service. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 30: effectiveness in a class discussion

A learner who repairs spelling but misses a meaning error studies effectiveness in a class discussion about food systems. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 31: result in a graph explanation

A learner who uses one memorised sentence only studies result in a graph explanation about biodiversity. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 32: adapt in an informational passage

A learner who copies teacher correction without understanding it studies adapt in an informational passage about friendship. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 33: contrast in a textbook section

A learner who knows the base word but not the derived form studies contrast in a textbook section about transport. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 34: contribute in a Mathematics word problem

A learner who repairs spelling but misses a meaning error studies contribute in a Mathematics word problem about teamwork. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 35: reluctance in a debate

A learner who uses one memorised sentence only studies reluctance in a debate about energy. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 36: sequence in a situational-writing email

A learner who copies teacher correction without understanding it studies sequence in a situational-writing email about inventions. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 37: evaluation in a Secondary 1 preview text

A learner who knows the base word but not the derived form studies evaluation in a Secondary 1 preview text about financial decisions. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 38: decision in a listening task

A learner who repairs spelling but misses a meaning error studies decision in a listening task about technology. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 39: efficient in a documentary extract

A learner who uses one memorised sentence only studies efficient in a documentary extract about school rules. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 40: cause in a school announcement

A learner who copies teacher correction without understanding it studies cause in a school announcement about healthy habits. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 41: adaptation in a narrative passage

A learner who knows the base word but not the derived form studies adaptation in a narrative passage about environmental change. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 42: consequence in a project reflection

A learner who repairs spelling but misses a meaning error studies consequence in a project reflection about media literacy. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 43: contribution in a Science explanation

A learner who uses one memorised sentence only studies contribution in a Science explanation about weather. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 44: confident in a digital article

A learner who copies teacher correction without understanding it studies confident in a digital article about public spaces. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 45: specific in an oral response

A learner who knows the base word but not the derived form studies specific in an oral response about sports. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 46: significant in a peer explanation

A learner who repairs spelling but misses a meaning error studies significant in a peer explanation about water conservation. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 47: respond in a continuous-writing paragraph

A learner who uses one memorised sentence only studies respond in a continuous-writing paragraph about digital safety. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 48: efficiency in a revision task

A learner who copies teacher correction without understanding it studies efficiency in a revision task about learning habits. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 49: effect in a news report

A learner who knows the base word but not the derived form studies effect in a news report about community service. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 50: resolve in a class discussion

A learner who repairs spelling but misses a meaning error studies resolve in a class discussion about food systems. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 51: consequential in a graph explanation

A learner who uses one memorised sentence only studies consequential in a graph explanation about biodiversity. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 52: construct in an informational passage

A learner who copies teacher correction without understanding it studies construct in an informational passage about friendship. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 53: confidence in a textbook section

A learner who knows the base word but not the derived form studies confidence in a textbook section about transport. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 54: general in a Mathematics word problem

A learner who repairs spelling but misses a meaning error studies general in a Mathematics word problem about teamwork. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 55: significance in a debate

A learner who uses one memorised sentence only studies significance in a debate about energy. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 56: response in a situational-writing email

A learner who copies teacher correction without understanding it studies response in a situational-writing email about inventions. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 57: reliable in a Secondary 1 preview text

A learner who knows the base word but not the derived form studies reliable in a Secondary 1 preview text about financial decisions. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 58: support in a listening task

A learner who repairs spelling but misses a meaning error studies support in a listening task about technology. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 59: resolution in a documentary extract

A learner who uses one memorised sentence only studies resolution in a documentary extract about school rules. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 60: observe in a school announcement

A learner who copies teacher correction without understanding it studies observe in a school announcement about healthy habits. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 61: construction in a narrative passage

A learner who knows the base word but not the derived form studies construction in a narrative passage about environmental change. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 62: evidence in a project reflection

A learner who repairs spelling but misses a meaning error studies evidence in a project reflection about media literacy. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 63: infer in a Science explanation

A learner who uses one memorised sentence only studies infer in a Science explanation about weather. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 64: justify in a digital article

A learner who copies teacher correction without understanding it studies justify in a digital article about public spaces. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 65: accurate in an oral response

A learner who knows the base word but not the derived form studies accurate in an oral response about sports. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 66: reliability in a peer explanation

A learner who repairs spelling but misses a meaning error studies reliability in a peer explanation about water conservation. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 67: source in a continuous-writing paragraph

A learner who uses one memorised sentence only studies source in a continuous-writing paragraph about digital safety. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 68: retain in a revision task

A learner who copies teacher correction without understanding it studies retain in a revision task about learning habits. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 69: observation in a news report

A learner who knows the base word but not the derived form studies observation in a news report about community service. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 70: differentiate in a class discussion

A learner who repairs spelling but misses a meaning error studies differentiate in a class discussion about food systems. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 71: claim in a graph explanation

A learner who uses one memorised sentence only studies claim in a graph explanation about biodiversity. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 72: inference in an informational passage

A learner who copies teacher correction without understanding it studies inference in an informational passage about friendship. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 73: justification in a textbook section

A learner who knows the base word but not the derived form studies justification in a textbook section about transport. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 74: accuracy in a Mathematics word problem

A learner who repairs spelling but misses a meaning error studies accuracy in a Mathematics word problem about teamwork. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 75: valid in a debate

A learner who uses one memorised sentence only studies valid in a debate about energy. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 76: context in a situational-writing email

A learner who copies teacher correction without understanding it studies context in a situational-writing email about inventions. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 77: retention in a Secondary 1 preview text

A learner who knows the base word but not the derived form studies retention in a Secondary 1 preview text about financial decisions. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 78: predict in a listening task

A learner who repairs spelling but misses a meaning error studies predict in a listening task about technology. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 79: difference in a documentary extract

A learner who uses one memorised sentence only studies difference in a documentary extract about school rules. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 80: argument in a school announcement

A learner who copies teacher correction without understanding it studies argument in a school announcement about healthy habits. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 81: conclude in a narrative passage

A learner who knows the base word but not the derived form studies conclude in a narrative passage about environmental change. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 82: interpret in a project reflection

A learner who repairs spelling but misses a meaning error studies interpret in a project reflection about media literacy. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 83: precise in a Science explanation

A learner who uses one memorised sentence only studies precise in a Science explanation about weather. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 84: validity in a digital article

A learner who copies teacher correction without understanding it studies validity in a digital article about public spaces. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 85: criterion in an oral response

A learner who knows the base word but not the derived form studies criterion in an oral response about sports. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 86: retrieve in a peer explanation

A learner who repairs spelling but misses a meaning error studies retrieve in a peer explanation about water conservation. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 87: prediction in a continuous-writing paragraph

A learner who uses one memorised sentence only studies prediction in a continuous-writing paragraph about digital safety. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 88: similar in a revision task

A learner who copies teacher correction without understanding it studies similar in a revision task about learning habits. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 89: reason in a news report

A learner who knows the base word but not the derived form studies reason in a news report about community service. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.

Fieldbook 90: conclusion in a class discussion

A learner who repairs spelling but misses a meaning error studies conclusion in a class discussion about food systems. Give a short meaning and name one must-have semantic feature. Create a clear example and a near non-example that differs by one important property. Require the learner to explain the boundary, then compare one near-synonym or opposite. Change the topic and test whether the same decision rule still works. The target is precise acceptance and rejection, not definition recital.