Papers with computational indices tracking learners

    1 papers
    Exploring the Semantic Space of Second Language Learners (2026.eacl-srw)

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    Challenge: Using machine learning models, we compared the semantic space of university-level students learning French with native speakers' (L1) .
    Approach: They extracted semantic features from narrative text and used interpretability techniques to identify the most informative features per model.
    Outcome: The results show that the second language learners had higher semantic similarity scores than the native speakers at the token level, whereas the similarity decreased over time but did not reach native-level values.

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