A data-driven taxonomy organizing the meanings of concrete and abstract along a learner–representation–concept dimension¶
Research Method · All research methods
Evidence · 3 claims (3 for) · 1 study (1 qualitative),q2· 0 of 1 report an effect size · 3 claims rest on one study
Description¶
The article proposes a taxonomy of the semantic landscape of concreteness and abstraction in mathematics education, built from qualitative coding of a corpus of 368 papers. It models learning as follows: "To learn a concept ( C ), a learner ( L ) interacts with a representation ( R) of C , designed through mapping." Axes are placed at the interaction level (learner–representation) or the mapping level (representation–concept), each running between a concrete and an abstract end, and each paired with a design question to make the taxonomy usable in research and practice.
Accounts¶
- A data-driven taxonomy organizing the meanings of concrete and abstract along a learner–representation–concept dimension: The article proposes a taxonomy of the semantic landscape of concreteness and abstraction in mathematics education, built from qualitative coding of a corpus of 368 papers. It models learning as follows: "To learn a concept ( C ), a learner ( L ) interacts with a representation ( R) of C , designed through mapping." Axes are placed at the interaction level (learner–representation) or the mapping level (representation–concept), each running between a concrete and an abstract end, and each paired with a design question to make the taxonomy usable in research and practice. (Julia Chatain et al. (2025))
Claims¶
- Mathematics education literature uses the terms concrete and abstract with multiple distinct meanings [+W]
- A single representation can be abstract along one dimension and concrete along another, and concrete for one learner but abstract for another [+W]
- Disagreements about concreteness and abstraction in mathematics education may be verbal disputes rooted in word meaning [+W]
Related Research Methods¶
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Key Sources¶
- Julia Chatain, Charlotte Müller, Keny Chatain, Leon Calabrese, Manu Kapur. (2025). Concreteness and Abstraction in Mathematics Education: A Taxonomy of the Semantic Landscape. Educational Psychology Review. https://doi.org/10.1007/s10648-025-10073-9
Page metadata
| Field | Value |
|---|---|
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research-method |
id |
a-data-driven-taxonomy-organizing-the-meanings-of-concrete-and-abstract-along-a-learnerrep |
title |
A data-driven taxonomy organizing the meanings of concrete and abstract along a learner–representation–concept dimension |
description |
The article proposes a taxonomy of the semantic landscape of concreteness and abstraction in mathematics education, built from qualitative coding of a corpus of 368 papers. |
status |
review |
generated |
by process:settle-candidates on 2026-10-20 |
trust |
unverified — no one has confirmed this page's content |
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