Publicly released UK Key Stage readability dataset of 20,000 balanced text chunks¶
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Evidence · 4 claims (3 for, 1 mixed) · 1 study (1 design),q2· 0 of 1 report an effect size · 4 claims rest on one study
Description¶
A publicly released corpus of 20,000 Project Gutenberg text chunks balanced across UK Key Stages 2–5 and linked to Lexile readability scores, created by Jordan J. Bird for matching literature texts to educational reading levels.
Components¶
Claims¶
- Unimodal classification confuses Key Stage 4 with Key Stage 3, while the best multimodal model classifies Key Stages 4 and 5 perfectly [+W]
- Fusing transformer text classifiers with a linguistic-feature neural network significantly outperforms unimodal models for UK Key Stage classification, with ELECTRA + ANN reaching F1 = 0.996 [+W]
- BERT was the best unimodal text classifier for Key Stage classification with an F1 score of 0.75 [+W]
- Neural networks on linguistic features classify Key Stages poorly, with deeper networks performing worse; the best (one hidden layer, 175 ReLU) reached F1 = 0.392 [~W]
Related Products and Programmes¶
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Key Sources¶
- Jordan J. Bird. (2024). What Differentiates Educational Literature? A Multimodal Fusion Approach of Transformers and Computational Linguistics. arXiv preprint. https://arxiv.org/abs/2411.17593
Page metadata
| Field | Value |
|---|---|
type |
product |
id |
publicly-released-uk-key-stage-readability-dataset-of-20000-balanced-text-chunks |
title |
Publicly released UK Key Stage readability dataset of 20,000 balanced text chunks |
description |
A publicly released corpus of 20,000 Project Gutenberg text chunks balanced across UK Key Stages 2–5 and linked to Lexile readability scores, created by Jordan J. |
status |
review |
product_kind |
dataset |
generated |
by process:settle-candidates on 2026-10-12 |
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unverified — no one has confirmed this page's content |
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