Modeling Text Difficulty Using CEFR Levels

by Ike Peng4 months ago

6

This project studies text difficulty as a linguistic property rather than a black-box machine learning label. Using an existing dataset of English sentences annotated with CEFR levels, we first analyze which linguistic factors, such as lexical frequency, syntactic complexity, and language model surprisal, contribute most to perceived difficulty. We compare traditional NLP features with a pretrained BERT-based CEFR predictor and conduct diagnostic experiments to understand model behavior.

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If you are inspired by this idea, you can reach out to the authors for collaboration or cite it:

@misc{peng-modeling-text-difficulty-2026,
  author = {Peng, Ike},
  title = {Modeling Text Difficulty Using CEFR Levels},
  year = {2026},
  url = {https://hypogenic.ai/ideahub/idea/fX8u6JLRlsDz9QkeNaMm}
}

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