What is Primary 6 Vocabulary | Abstract and Concrete Vocabulary — From Real Examples to Academic Concepts

Primary 6 abstract vocabulary is the language learners use for ideas, qualities, systems and relationships that cannot always be pointed to or pictured directly. Families searching for Grade 6 abstract words, concrete vs abstract vocabulary, academic vocabulary, abstract nouns, concept words and 6th grade academic language are dealing with a major transition in upper-primary learning: school language increasingly asks students to reason about concepts such as responsibility, significance, evidence, consequence, efficiency and probability rather than only naming visible objects and actions.

Concrete vocabulary refers readily to people, objects, actions or observable events, while abstract vocabulary packages relationships, qualities, categories and ideas. Strong Grade 6 vocabulary connects the two. A learner understands responsibility more securely when the abstract label is tied to observable choices; understands evidence by linking it to actual information that supports a claim; and understands efficiency by comparing processes that use different amounts of time or resources. Abstract language becomes teachable when it is anchored in examples and then generalised across contexts.

This guide builds a Primary 6 concrete-to-abstract vocabulary system. It explains how examples support concept formation, how abstract nouns organise school knowledge, why academic words travel across subjects, how to avoid empty definition memorisation, and how learners can move from one concrete example to a general principle without overgeneralising. The central goal is abstraction with evidence: the learner should be able to name an idea, show it in a real case and recognise it again when the surface details change.

The 50-second router

1. Start with a concrete case.
2. Name the abstract idea.
3. Identify the feature the examples share.
4. Add a contrasting non-example.
5. Move the concept into another subject or situation.
6. Retrieve the abstract word from the new example.

Concrete examples give abstract words somewhere to land

An abstract definition can remain verbal noise if the learner has no experience or example to attach to it. Observable cases provide the first semantic anchor.

For the wider concept system, use Vocabulary | Concepts and Categorisation and Primary 6 Vocabulary & Background Knowledge. This child owns the concrete-to-abstract transition.

Abstraction identifies what stays constant

The learner must notice the common relationship across different examples. Responsibility looks different at home, in a team and online, yet a core idea of obligation and accountable action can remain stable.

For the wider concept system, use Vocabulary | Concepts and Categorisation and Primary 6 Vocabulary & Background Knowledge. This child owns the concrete-to-abstract transition.

Academic vocabulary often names relationships

Words such as factor, consequence, evidence, significance, probability and criterion organise reasoning rather than merely naming things. Their usefulness comes from transfer across topics.

For the wider concept system, use Vocabulary | Concepts and Categorisation and Primary 6 Vocabulary & Background Knowledge. This child owns the concrete-to-abstract transition.

Abstract nouns compress complex ideas

A word such as evaluation can package an entire process into one noun. This supports dense academic language but can also make a text harder when the underlying action is unclear.

For the wider concept system, use Vocabulary | Concepts and Categorisation and Primary 6 Vocabulary & Background Knowledge. This child owns the concrete-to-abstract transition.

Examples and non-examples protect against empty labels

A learner who can repeat “evidence supports a claim” should also identify what counts as evidence and what is merely an opinion, detail or example.

For the wider concept system, use Vocabulary | Concepts and Categorisation and Primary 6 Vocabulary & Background Knowledge. This child owns the concrete-to-abstract transition.

Multiple contexts are necessary for genuine abstraction

One memorised example can make a concept context-bound. Changing topic forces the learner to recover the shared meaning rather than the surface story.

For the wider concept system, use Vocabulary | Concepts and Categorisation and Primary 6 Vocabulary & Background Knowledge. This child owns the concrete-to-abstract transition.

Concrete language still matters in advanced thinking

Good explanations move between abstract claims and concrete evidence. Abstract vocabulary should not replace examples; it should help organise them.

For the wider concept system, use Vocabulary | Concepts and Categorisation and Primary 6 Vocabulary & Background Knowledge. This child owns the concrete-to-abstract transition.

Visuals can support some abstract concepts indirectly

Timelines, diagrams, scales and comparison tables can make relationships such as sequence, proportion, cause or probability more inspectable even when the concept itself is not a visible object.

For the wider concept system, use Vocabulary | Concepts and Categorisation and Primary 6 Vocabulary & Background Knowledge. This child owns the concrete-to-abstract transition.

Abstract vocabulary supports cross-curricular learning

The same idea of evidence can appear in English comprehension, Science investigation, Mathematics justification and everyday decision making.

For the wider concept system, use Vocabulary | Concepts and Categorisation and Primary 6 Vocabulary & Background Knowledge. This child owns the concrete-to-abstract transition.

Background knowledge affects abstraction

Learners generalise more effectively when they understand the situations from which the concept is being abstracted. Vocabulary and knowledge therefore grow together.

For the wider concept system, use Vocabulary | Concepts and Categorisation and Primary 6 Vocabulary & Background Knowledge. This child owns the concrete-to-abstract transition.

Overgeneralisation is the main danger

Once a learner discovers a broad idea, the word may be applied too widely. Concept boundaries and near non-examples are needed to show where the abstraction stops.

For the wider concept system, use Vocabulary | Concepts and Categorisation and Primary 6 Vocabulary & Background Knowledge. This child owns the concrete-to-abstract transition.

Secondary 1 increases abstraction density

Later texts contain more nominalisation, evaluative language and conceptual relationships. Primary 6 should make abstract vocabulary a familiar way of organising meaning rather than a sudden secondary-school shock.

For the wider concept system, use Vocabulary | Concepts and Categorisation and Primary 6 Vocabulary & Background Knowledge. This child owns the concrete-to-abstract transition.

A six-stage abstraction ladder

1. Case

Observe one concrete event, example or situation.

2. Label

Attach the relevant abstract word.

3. Feature

State what matters about the example.

4. Contrast

Compare a near non-example.

5. Generalise

State the concept in broader language.

6. Transfer

Recognise or use it in a new domain.

One hundred and eighteen abstraction laboratories

Abstraction Lab 1: justice from concrete case to abstract concept

A learner who knows concrete examples but struggles with abstract labels meets justice in a narrative passage about environmental change. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve justice without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 2: risk from concrete case to abstract concept

A learner who knows a scale but not which contexts permit each step meets risk in a situational-writing email about healthy habits. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve risk without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 3: confidence from concrete case to abstract concept

A learner who states every claim as certain meets confidence in a graph explanation about school rules. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve confidence without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 4: pattern from concrete case to abstract concept

A learner who confuses strong evidence with certain proof meets pattern in a peer explanation about technology. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve pattern without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 5: trend from concrete case to abstract concept

A learner who chooses a word that is too general meets trend in a narrative passage about financial decisions. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve trend without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 6: support from concrete case to abstract concept

A learner who writes vague nouns where a specific referent is needed meets support in a situational-writing email about inventions. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve support without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 7: importance from concrete case to abstract concept

A learner who uses very with every strong adjective meets importance in a graph explanation about energy. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve importance without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 8: major from concrete case to abstract concept

A learner who understands the idea but not the level of certainty meets major in a peer explanation about teamwork. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve major without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 9: likely from concrete case to abstract concept

A learner who avoids repetition by using inaccurate synonyms meets likely in a narrative passage about transport. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve likely without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 10: may from concrete case to abstract concept

A learner who knows many synonyms but cannot choose the best level of intensity meets may in a situational-writing email about friendship. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve may without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 11: slightly from concrete case to abstract concept

A learner who uses many different words but loses cohesion meets slightly in a graph explanation about biodiversity. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve slightly without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 12: almost from concrete case to abstract concept

A learner who uses abstract nouns without clear examples meets almost in a peer explanation about food systems. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve almost without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 13: movement from concrete case to abstract concept

A learner who confuses possible with probable meets movement in a narrative passage about community service. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve movement without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 14: stare from concrete case to abstract concept

A learner who hedges everything until the sentence becomes vague meets stare in a situational-writing email about learning habits. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve stare without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 15: object from concrete case to abstract concept

A learner who uses impressive vocabulary when a simple word is more precise meets object in a graph explanation about digital safety. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve object without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 16: evidence from concrete case to abstract concept

A learner who chooses a word that is unnecessarily specific meets evidence in a peer explanation about water conservation. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve evidence without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 17: probability from concrete case to abstract concept

A learner who uses overly specific details in a summary meets probability in a narrative passage about sports. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve probability without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 18: reluctance from concrete case to abstract concept

A learner who cannot rank near-synonyms by intensity meets reluctance in a situational-writing email about public spaces. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve reluctance without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 19: relationship from concrete case to abstract concept

A learner who can rank emotion words but not academic evaluative words meets relationship in a graph explanation about weather. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve relationship without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 20: claim from concrete case to abstract concept

A learner who repeats the same word in every sentence meets claim in a peer explanation about media literacy. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve claim without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 21: source from concrete case to abstract concept

A learner who knows concrete examples but struggles with abstract labels meets source in a narrative passage about environmental change. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve source without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 22: severity from concrete case to abstract concept

A learner who knows a scale but not which contexts permit each step meets severity in a situational-writing email about healthy habits. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve severity without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 23: slight from concrete case to abstract concept

A learner who states every claim as certain meets slight in a graph explanation about school rules. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve slight without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 24: unlikely from concrete case to abstract concept

A learner who confuses strong evidence with certain proof meets unlikely in a peer explanation about technology. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve unlikely without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 25: might from concrete case to abstract concept

A learner who chooses a word that is too general meets might in a narrative passage about financial decisions. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve might without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 26: fairly from concrete case to abstract concept

A learner who writes vague nouns where a specific referent is needed meets fairly in a situational-writing email about inventions. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve fairly without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 27: partly from concrete case to abstract concept

A learner who uses very with every strong adjective meets partly in a graph explanation about energy. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve partly without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 28: walk from concrete case to abstract concept

A learner who understands the idea but not the level of certainty meets walk in a peer explanation about teamwork. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve walk without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 29: peer from concrete case to abstract concept

A learner who avoids repetition by using inaccurate synonyms meets peer in a narrative passage about transport. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve peer without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 30: item from concrete case to abstract concept

A learner who knows many synonyms but cannot choose the best level of intensity meets item in a situational-writing email about friendship. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve item without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 31: freedom from concrete case to abstract concept

A learner who uses many different words but loses cohesion meets freedom in a graph explanation about biodiversity. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve freedom without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 32: possibility from concrete case to abstract concept

A learner who uses abstract nouns without clear examples meets possibility in a peer explanation about food systems. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve possibility without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 33: influence from concrete case to abstract concept

A learner who confuses possible with probable meets influence in a narrative passage about community service. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve influence without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 34: category from concrete case to abstract concept

A learner who hedges everything until the sentence becomes vague meets category in a situational-writing email about learning habits. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve category without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 35: argument from concrete case to abstract concept

A learner who uses impressive vocabulary when a simple word is more precise meets argument in a graph explanation about digital safety. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve argument without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 36: context from concrete case to abstract concept

A learner who chooses a word that is unnecessarily specific meets context in a peer explanation about water conservation. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve context without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 37: frequency from concrete case to abstract concept

A learner who uses overly specific details in a summary meets frequency in a narrative passage about sports. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve frequency without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 38: substantial from concrete case to abstract concept

A learner who cannot rank near-synonyms by intensity meets substantial in a situational-writing email about public spaces. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve substantial without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 39: certain from concrete case to abstract concept

A learner who can rank emotion words but not academic evaluative words meets certain in a graph explanation about weather. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve certain without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 40: could from concrete case to abstract concept

A learner who repeats the same word in every sentence meets could in a peer explanation about media literacy. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve could without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 41: quite from concrete case to abstract concept

A learner who knows concrete examples but struggles with abstract labels meets quite in a narrative passage about environmental change. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve quite without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 42: completely from concrete case to abstract concept

A learner who knows a scale but not which contexts permit each step meets completely in a situational-writing email about healthy habits. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve completely without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 43: stroll from concrete case to abstract concept

A learner who states every claim as certain meets stroll in a graph explanation about school rules. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve stroll without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 44: gaze from concrete case to abstract concept

A learner who confuses strong evidence with certain proof meets gaze in a peer explanation about technology. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve gaze without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 45: device from concrete case to abstract concept

A learner who chooses a word that is too general meets device in a narrative passage about financial decisions. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve device without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 46: temperature from concrete case to abstract concept

A learner who writes vague nouns where a specific referent is needed meets temperature in a situational-writing email about inventions. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve temperature without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 47: certainty from concrete case to abstract concept

A learner who uses very with every strong adjective meets certainty in a graph explanation about energy. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve certainty without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 48: consequence from concrete case to abstract concept

A learner who understands the idea but not the level of certainty meets consequence in a peer explanation about teamwork. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve consequence without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 49: principle from concrete case to abstract concept

A learner who avoids repetition by using inaccurate synonyms meets principle in a narrative passage about transport. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve principle without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 50: reason from concrete case to abstract concept

A learner who knows many synonyms but cannot choose the best level of intensity meets reason in a situational-writing email about friendship. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve reason without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 51: criterion from concrete case to abstract concept

A learner who uses many different words but loses cohesion meets criterion in a graph explanation about biodiversity. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve criterion without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 52: likelihood from concrete case to abstract concept

A learner who uses abstract nouns without clear examples meets likelihood in a peer explanation about food systems. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve likelihood without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 53: significant from concrete case to abstract concept

A learner who confuses possible with probable meets significant in a narrative passage about community service. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve significant without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 54: suggests from concrete case to abstract concept

A learner who hedges everything until the sentence becomes vague meets suggests in a situational-writing email about learning habits. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve suggests without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 55: perhaps from concrete case to abstract concept

A learner who uses impressive vocabulary when a simple word is more precise meets perhaps in a graph explanation about digital safety. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve perhaps without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 56: very from concrete case to abstract concept

A learner who chooses a word that is unnecessarily specific meets very in a peer explanation about water conservation. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve very without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 57: vehicle from concrete case to abstract concept

A learner who uses overly specific details in a summary meets vehicle in a narrative passage about sports. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve vehicle without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 58: march from concrete case to abstract concept

A learner who cannot rank near-synonyms by intensity meets march in a situational-writing email about public spaces. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve march without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 59: problem from concrete case to abstract concept

A learner who can rank emotion words but not academic evaluative words meets problem in a graph explanation about weather. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve problem without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 60: tool from concrete case to abstract concept

A learner who repeats the same word in every sentence meets tool in a peer explanation about media literacy. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve tool without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 61: responsibility from concrete case to abstract concept

A learner who knows concrete examples but struggles with abstract labels meets responsibility in a narrative passage about environmental change. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve responsibility without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 62: relevance from concrete case to abstract concept

A learner who knows a scale but not which contexts permit each step meets relevance in a situational-writing email about healthy habits. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve relevance without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 63: process from concrete case to abstract concept

A learner who states every claim as certain meets process in a graph explanation about school rules. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve process without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 64: method from concrete case to abstract concept

A learner who confuses strong evidence with certain proof meets method in a peer explanation about technology. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve method without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 65: result from concrete case to abstract concept

A learner who chooses a word that is too general meets result in a narrative passage about financial decisions. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve result without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 66: sequence from concrete case to abstract concept

A learner who writes vague nouns where a specific referent is needed meets sequence in a situational-writing email about inventions. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve sequence without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 67: certainty from concrete case to abstract concept

A learner who uses very with every strong adjective meets certainty in a graph explanation about energy. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve certainty without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 68: extreme from concrete case to abstract concept

A learner who understands the idea but not the level of certainty meets extreme in a peer explanation about teamwork. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve extreme without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 69: indicates from concrete case to abstract concept

A learner who avoids repetition by using inaccurate synonyms meets indicates in a narrative passage about transport. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve indicates without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 70: probably from concrete case to abstract concept

A learner who knows many synonyms but cannot choose the best level of intensity meets probably in a situational-writing email about friendship. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve probably without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 71: extremely from concrete case to abstract concept

A learner who uses many different words but loses cohesion meets extremely in a graph explanation about biodiversity. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve extremely without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 72: transport from concrete case to abstract concept

A learner who uses abstract nouns without clear examples meets transport in a peer explanation about food systems. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve transport without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 73: sprint from concrete case to abstract concept

A learner who confuses possible with probable meets sprint in a narrative passage about community service. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve sprint without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 74: issue from concrete case to abstract concept

A learner who hedges everything until the sentence becomes vague meets issue in a situational-writing email about learning habits. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve issue without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 75: emotion from concrete case to abstract concept

A learner who uses impressive vocabulary when a simple word is more precise meets emotion in a graph explanation about digital safety. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve emotion without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 76: factor from concrete case to abstract concept

A learner who chooses a word that is unnecessarily specific meets factor in a peer explanation about water conservation. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve factor without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 77: efficiency from concrete case to abstract concept

A learner who uses overly specific details in a summary meets efficiency in a narrative passage about sports. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve efficiency without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 78: strategy from concrete case to abstract concept

A learner who cannot rank near-synonyms by intensity meets strategy in a situational-writing email about public spaces. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve strategy without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 79: resource from concrete case to abstract concept

A learner who can rank emotion words but not academic evaluative words meets resource in a graph explanation about weather. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve resource without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 80: cause from concrete case to abstract concept

A learner who repeats the same word in every sentence meets cause in a peer explanation about media literacy. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve cause without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 81: precision from concrete case to abstract concept

A learner who knows concrete examples but struggles with abstract labels meets precision in a narrative passage about environmental change. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve precision without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 82: minor from concrete case to abstract concept

A learner who knows a scale but not which contexts permit each step meets minor in a situational-writing email about healthy habits. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve minor without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 83: possible from concrete case to abstract concept

A learner who states every claim as certain meets possible in a graph explanation about school rules. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve possible without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 84: demonstrates from concrete case to abstract concept

A learner who confuses strong evidence with certain proof meets demonstrates in a peer explanation about technology. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve demonstrates without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 85: clearly from concrete case to abstract concept

A learner who chooses a word that is too general meets clearly in a narrative passage about financial decisions. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve clearly without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 86: absolutely from concrete case to abstract concept

A learner who writes vague nouns where a specific referent is needed meets absolutely in a situational-writing email about inventions. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve absolutely without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 87: bus from concrete case to abstract concept

A learner who uses very with every strong adjective meets bus in a graph explanation about energy. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve bus without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 88: look from concrete case to abstract concept

A learner who understands the idea but not the level of certainty meets look in a peer explanation about teamwork. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve look without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 89: challenge from concrete case to abstract concept

A learner who avoids repetition by using inaccurate synonyms meets challenge in a narrative passage about transport. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve challenge without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 90: feeling from concrete case to abstract concept

A learner who knows many synonyms but cannot choose the best level of intensity meets feeling in a situational-writing email about friendship. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve feeling without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 91: significance from concrete case to abstract concept

A learner who uses many different words but loses cohesion meets significance in a graph explanation about biodiversity. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve significance without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 92: effectiveness from concrete case to abstract concept

A learner who uses abstract nouns without clear examples meets effectiveness in a peer explanation about food systems. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve effectiveness without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 93: system from concrete case to abstract concept

A learner who confuses possible with probable meets system in a narrative passage about community service. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve system without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 94: capacity from concrete case to abstract concept

A learner who hedges everything until the sentence becomes vague meets capacity in a situational-writing email about learning habits. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve capacity without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 95: effect from concrete case to abstract concept

A learner who uses impressive vocabulary when a simple word is more precise meets effect in a graph explanation about digital safety. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve effect without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 96: accuracy from concrete case to abstract concept

A learner who chooses a word that is unnecessarily specific meets accuracy in a peer explanation about water conservation. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve accuracy without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 97: moderate from concrete case to abstract concept

A learner who uses overly specific details in a summary meets moderate in a narrative passage about sports. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve moderate without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 98: probable from concrete case to abstract concept

A learner who cannot rank near-synonyms by intensity meets probable in a situational-writing email about public spaces. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve probable without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 99: proves from concrete case to abstract concept

A learner who can rank emotion words but not academic evaluative words meets proves in a graph explanation about weather. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve proves without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 100: strongly from concrete case to abstract concept

A learner who repeats the same word in every sentence meets strongly in a peer explanation about media literacy. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve strongly without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 101: nearly from concrete case to abstract concept

A learner who knows concrete examples but struggles with abstract labels meets nearly in a narrative passage about environmental change. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve nearly without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 102: train from concrete case to abstract concept

A learner who knows a scale but not which contexts permit each step meets train in a situational-writing email about healthy habits. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve train without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 103: glance from concrete case to abstract concept

A learner who states every claim as certain meets glance in a graph explanation about school rules. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve glance without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 104: difficulty from concrete case to abstract concept

A learner who confuses strong evidence with certain proof meets difficulty in a peer explanation about technology. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve difficulty without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 105: justice from concrete case to abstract concept

A learner who chooses a word that is too general meets justice in a narrative passage about financial decisions. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve justice without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 106: risk from concrete case to abstract concept

A learner who writes vague nouns where a specific referent is needed meets risk in a situational-writing email about inventions. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve risk without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 107: confidence from concrete case to abstract concept

A learner who uses very with every strong adjective meets confidence in a graph explanation about energy. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve confidence without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 108: pattern from concrete case to abstract concept

A learner who understands the idea but not the level of certainty meets pattern in a peer explanation about teamwork. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve pattern without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 109: trend from concrete case to abstract concept

A learner who avoids repetition by using inaccurate synonyms meets trend in a narrative passage about transport. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve trend without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 110: support from concrete case to abstract concept

A learner who knows many synonyms but cannot choose the best level of intensity meets support in a situational-writing email about friendship. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve support without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 111: importance from concrete case to abstract concept

A learner who uses many different words but loses cohesion meets importance in a graph explanation about biodiversity. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve importance without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 112: major from concrete case to abstract concept

A learner who uses abstract nouns without clear examples meets major in a peer explanation about food systems. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve major without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 113: likely from concrete case to abstract concept

A learner who confuses possible with probable meets likely in a narrative passage about community service. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve likely without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 114: may from concrete case to abstract concept

A learner who hedges everything until the sentence becomes vague meets may in a situational-writing email about learning habits. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve may without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 115: slightly from concrete case to abstract concept

A learner who uses impressive vocabulary when a simple word is more precise meets slightly in a graph explanation about digital safety. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve slightly without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 116: almost from concrete case to abstract concept

A learner who chooses a word that is unnecessarily specific meets almost in a peer explanation about water conservation. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve almost without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 117: movement from concrete case to abstract concept

A learner who uses overly specific details in a summary meets movement in a narrative passage about sports. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve movement without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

Abstraction Lab 118: stare from concrete case to abstract concept

A learner who cannot rank near-synonyms by intensity meets stare in a situational-writing email about public spaces. Begin with one concrete situation that clearly instantiates the target. Ask what happened and which feature makes the example relevant. Name the abstract concept only after the case is understood. Create a near non-example that looks similar but lacks one defining feature, then explain the difference. Move the concept into a different topic and ask the learner to retrieve stare without the original example. Finally, reverse the task: give the abstract word and require a fresh concrete example. The concept is becoming usable when the learner can travel both directions—case to abstraction and abstraction to case—without overgeneralising.

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 vocabulary 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 remains add-only. Each child owns one distinct search and teaching job, then routes into existing specialist pages instead of rewriting them.

Sources and further reading

• Reading Rockets — Vocabulary Instructional Guidelines and Classroom Examples.
• Reading Rockets — Content Area Vocabulary Learning.
• Cambridge Dictionary — Hedges.
• Cambridge Dictionary — Gradable Adjectives and Degree.
• Cambridge Dictionary — Intensifiers.
• Cambridge Dictionary — Degree Adverbs.
• Cambridge Core — Lexical Diversity and Language Proficiency (2026).
• IES — Word Knowledge Instruction and Grade 5 Writing.
• MOE Singapore — English Language Syllabus 2020 Primary.
• SEAB — 2026 PSLE English Language syllabus.

Extended Primary 6 application fieldbook

Fieldbook 1: justice in a narrative passage

A learner who knows concrete examples but struggles with abstract labels meets justice in a narrative passage about environmental change. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 2: category in a project reflection

A learner who chooses a word that is unnecessarily specific meets category in a project reflection about media literacy. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 3: certainty in a Science explanation

A learner who uses many different words but loses cohesion meets certainty in a Science explanation about weather. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 4: strongly in a digital article

A learner who writes vague nouns where a specific referent is needed meets strongly in a digital article about public spaces. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 5: peer in an oral response

A learner who knows concrete examples but struggles with abstract labels meets peer in an oral response about sports. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 6: relevance in a peer explanation

A learner who chooses a word that is unnecessarily specific meets relevance in a peer explanation about water conservation. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 7: effect in a continuous-writing paragraph

A learner who uses many different words but loses cohesion meets effect in a continuous-writing paragraph about digital safety. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 8: unlikely in a revision task

A learner who writes vague nouns where a specific referent is needed meets unlikely in a revision task about learning habits. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 9: vehicle in a news report

A learner who knows concrete examples but struggles with abstract labels meets vehicle in a news report about community service. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 10: feeling in a class discussion

A learner who chooses a word that is unnecessarily specific meets feeling in a class discussion about food systems. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 11: relationship in a graph explanation

A learner who uses many different words but loses cohesion meets relationship in a graph explanation about biodiversity. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 12: likelihood in an informational passage

A learner who writes vague nouns where a specific referent is needed meets likelihood in an informational passage about friendship. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 13: clearly in a textbook section

A learner who knows concrete examples but struggles with abstract labels meets clearly in a textbook section about transport. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 14: stare in a Mathematics word problem

A learner who chooses a word that is unnecessarily specific meets stare in a Mathematics word problem about teamwork. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 15: certainty in a debate

A learner who uses many different words but loses cohesion meets certainty in a debate about energy. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 16: cause in a situational-writing email

A learner who writes vague nouns where a specific referent is needed meets cause in a situational-writing email about inventions. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 17: likely in a Secondary 1 preview text

A learner who knows concrete examples but struggles with abstract labels meets likely in a Secondary 1 preview text about financial decisions. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 18: completely in a listening task

A learner who chooses a word that is unnecessarily specific meets completely in a listening task about technology. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 19: emotion in a documentary extract

A learner who uses many different words but loses cohesion meets emotion in a documentary extract about school rules. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 20: pattern in a school announcement

A learner who writes vague nouns where a specific referent is needed meets pattern in a school announcement about healthy habits. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 21: frequency in a narrative passage

A learner who knows concrete examples but struggles with abstract labels meets frequency in a narrative passage about environmental change. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 22: probably in a project reflection

A learner who chooses a word that is unnecessarily specific meets probably in a project reflection about media literacy. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 23: glance in a Science explanation

A learner who uses many different words but loses cohesion meets glance in a Science explanation about weather. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 24: possibility in a digital article

A learner who writes vague nouns where a specific referent is needed meets possibility in a digital article about public spaces. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 25: result in an oral response

A learner who knows concrete examples but struggles with abstract labels meets result in an oral response about sports. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 26: probable in a peer explanation

A learner who chooses a word that is unnecessarily specific meets probable in a peer explanation about water conservation. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 27: partly in a continuous-writing paragraph

A learner who uses many different words but loses cohesion meets partly in a continuous-writing paragraph about digital safety. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 28: tool in a revision task

A learner who writes vague nouns where a specific referent is needed meets tool in a revision task about learning habits. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 29: system in a news report

A learner who knows concrete examples but struggles with abstract labels meets system in a news report about community service. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 30: severity in a class discussion

A learner who chooses a word that is unnecessarily specific meets severity in a class discussion about food systems. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 31: perhaps in a graph explanation

A learner who uses many different words but loses cohesion meets perhaps in a graph explanation about biodiversity. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 32: look in an informational passage

A learner who writes vague nouns where a specific referent is needed meets look in an informational passage about friendship. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 33: probability in a textbook section

A learner who knows concrete examples but struggles with abstract labels meets probability in a textbook section about transport. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 34: reason in a Mathematics word problem

A learner who chooses a word that is unnecessarily specific meets reason in a Mathematics word problem about teamwork. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 35: possible in a debate

A learner who uses many different words but loses cohesion meets possible in a debate about energy. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 36: almost in a situational-writing email

A learner who writes vague nouns where a specific referent is needed meets almost in a situational-writing email about inventions. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 37: device in a Secondary 1 preview text

A learner who knows concrete examples but struggles with abstract labels meets device in a Secondary 1 preview text about financial decisions. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 38: strategy in a listening task

A learner who chooses a word that is unnecessarily specific meets strategy in a listening task about technology. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 39: importance in a documentary extract

A learner who uses many different words but loses cohesion meets importance in a documentary extract about school rules. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 40: could in a school announcement

A learner who writes vague nouns where a specific referent is needed meets could in a school announcement about healthy habits. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 41: sprint in a narrative passage

A learner who knows concrete examples but struggles with abstract labels meets sprint in a narrative passage about environmental change. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 42: risk in a project reflection

A learner who chooses a word that is unnecessarily specific meets risk in a project reflection about media literacy. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 43: argument in a Science explanation

A learner who uses many different words but loses cohesion meets argument in a Science explanation about weather. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 44: extreme in a digital article

A learner who writes vague nouns where a specific referent is needed meets extreme in a digital article about public spaces. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 45: nearly in an oral response

A learner who knows concrete examples but struggles with abstract labels meets nearly in an oral response about sports. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 46: item in a peer explanation

A learner who chooses a word that is unnecessarily specific meets item in a peer explanation about water conservation. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 47: process in a continuous-writing paragraph

A learner who uses many different words but loses cohesion meets process in a continuous-writing paragraph about digital safety. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 48: accuracy in a revision task

A learner who writes vague nouns where a specific referent is needed meets accuracy in a revision task about learning habits. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 49: might in a news report

A learner who knows concrete examples but struggles with abstract labels meets might in a news report about community service. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 50: march in a class discussion

A learner who chooses a word that is unnecessarily specific meets march in a class discussion about food systems. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 51: significance in a graph explanation

A learner who uses many different words but loses cohesion meets significance in a graph explanation about biodiversity. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 52: claim in an informational passage

A learner who writes vague nouns where a specific referent is needed meets claim in an informational passage about friendship. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 53: significant in a textbook section

A learner who knows concrete examples but struggles with abstract labels meets significant in a textbook section about transport. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 54: absolutely in a Mathematics word problem

A learner who chooses a word that is unnecessarily specific meets absolutely in a Mathematics word problem about teamwork. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 55: object in a debate

A learner who uses many different words but loses cohesion meets object in a debate about energy. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 56: consequence in a situational-writing email

A learner who writes vague nouns where a specific referent is needed meets consequence in a situational-writing email about inventions. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 57: precision in a Secondary 1 preview text

A learner who knows concrete examples but struggles with abstract labels meets precision in a Secondary 1 preview text about financial decisions. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 58: may in a listening task

A learner who chooses a word that is unnecessarily specific meets may in a listening task about technology. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 59: stroll in a documentary extract

A learner who uses many different words but loses cohesion meets stroll in a documentary extract about school rules. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 60: factor in a school announcement

A learner who writes vague nouns where a specific referent is needed meets factor in a school announcement about healthy habits. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 61: trend in a narrative passage

A learner who knows concrete examples but struggles with abstract labels meets trend in a narrative passage about environmental change. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 62: substantial in a project reflection

A learner who chooses a word that is unnecessarily specific meets substantial in a project reflection about media literacy. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 63: extremely in a Science explanation

A learner who uses many different words but loses cohesion meets extremely in a Science explanation about weather. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 64: difficulty in a digital article

A learner who writes vague nouns where a specific referent is needed meets difficulty in a digital article about public spaces. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 65: influence in an oral response

A learner who knows concrete examples but struggles with abstract labels meets influence in an oral response about sports. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 66: sequence in a peer explanation

A learner who chooses a word that is unnecessarily specific meets sequence in a peer explanation about water conservation. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 67: proves in a continuous-writing paragraph

A learner who uses many different words but loses cohesion meets proves in a continuous-writing paragraph about digital safety. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 68: walk in a revision task

A learner who writes vague nouns where a specific referent is needed meets walk in a revision task about learning habits. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 69: responsibility in a news report

A learner who knows concrete examples but struggles with abstract labels meets responsibility in a news report about community service. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 70: capacity in a class discussion

A learner who chooses a word that is unnecessarily specific meets capacity in a class discussion about food systems. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 71: slight in a graph explanation

A learner who uses many different words but loses cohesion meets slight in a graph explanation about biodiversity. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 72: very in an informational passage

A learner who writes vague nouns where a specific referent is needed meets very in an informational passage about friendship. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 73: challenge in a textbook section

A learner who knows concrete examples but struggles with abstract labels meets challenge in a textbook section about transport. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 74: reluctance in a Mathematics word problem

A learner who chooses a word that is unnecessarily specific meets reluctance in a Mathematics word problem about teamwork. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 75: criterion in a debate

A learner who uses many different words but loses cohesion meets criterion in a debate about energy. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 76: demonstrates in a situational-writing email

A learner who writes vague nouns where a specific referent is needed meets demonstrates in a situational-writing email about inventions. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 77: movement in a Secondary 1 preview text

A learner who knows concrete examples but struggles with abstract labels meets movement in a Secondary 1 preview text about financial decisions. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 78: temperature in a listening task

A learner who chooses a word that is unnecessarily specific meets temperature in a listening task about technology. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 79: resource in a documentary extract

A learner who uses many different words but loses cohesion meets resource in a documentary extract about school rules. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 80: major in a school announcement

A learner who writes vague nouns where a specific referent is needed meets major in a school announcement about healthy habits. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 81: quite in a narrative passage

A learner who knows concrete examples but struggles with abstract labels meets quite in a narrative passage about environmental change. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 82: issue in a project reflection

A learner who chooses a word that is unnecessarily specific meets issue in a project reflection about media literacy. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 83: confidence in a Science explanation

A learner who uses many different words but loses cohesion meets confidence in a Science explanation about weather. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 84: context in a digital article

A learner who writes vague nouns where a specific referent is needed meets context in a digital article about public spaces. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 85: indicates in an oral response

A learner who knows concrete examples but struggles with abstract labels meets indicates in an oral response about sports. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 86: train in a peer explanation

A learner who chooses a word that is unnecessarily specific meets train in a peer explanation about water conservation. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 87: freedom in a continuous-writing paragraph

A learner who uses many different words but loses cohesion meets freedom in a continuous-writing paragraph about digital safety. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 88: method in a revision task

A learner who writes vague nouns where a specific referent is needed meets method in a revision task about learning habits. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 89: moderate in a news report

A learner who knows concrete examples but struggles with abstract labels meets moderate in a news report about community service. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.

Fieldbook 90: fairly in a class discussion

A learner who chooses a word that is unnecessarily specific meets fairly in a class discussion about food systems. Begin with a concrete case or observable example. Identify the feature that matters, attach the abstract label, then create a near non-example. Move the concept into another topic and ask the learner to retrieve the abstract word from the new case. Reverse the task by asking for a fresh example from the word alone. The target is bidirectional movement between examples and concepts.