@inproceedings{degraeuwe-goethals-2024-lexcomspal2,
    title = "{L}ex{C}om{S}pa{L}2: A Lexical Complexity Corpus for {S}panish as a Foreign Language",
    author = "Degraeuwe, Jasper  and
      Goethals, Patrick",
    editor = "Calzolari, Nicoletta  and
      Kan, Min-Yen  and
      Hoste, Veronique  and
      Lenci, Alessandro  and
      Sakti, Sakriani  and
      Xue, Nianwen",
    booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.lrec-main.912",
    pages = "10432--10447",
    abstract = "We present LexComSpaL2, a novel corpus which can be employed to train personalised word-level difficulty classifiers for learners of Spanish as a foreign/second language (L2). The dataset contains 2,240 in-context target words with the corresponding difficulty judgements of 26 Dutch-speaking students who are learning Spanish as an L2, resulting in a total of 58,240 annotations. The target words are divided over 200 sentences from 4 different domains (economics, health, law, and migration) and have been selected based on their suitability to be included in L2 learning materials. As our annotation scheme, we use a customised version of the 5-point lexical complexity prediction scale (Shardlow et al., 2020), tailored to the vocabulary knowledge continuum (which ranges from no knowledge over receptive mastery to productive mastery; Schmitt, 2019). With LexComSpaL2, we aim to address the lack of relevant data for multi-category difficult prediction at word level for L2 learners of other languages than English.",
}

We present LexComSpaL2, a novel corpus which can be employed to train personalised word-level difficulty classifiers for learners of Spanish as a foreign/second language (L2). The dataset contains 2,240 in-context target words with the corresponding difficulty judgements of 26 Dutch-speaking students who are learning Spanish as an L2, resulting in a total of 58,240 annotations. The target words are divided over 200 sentences from 4 different domains (economics, health, law, and migration) and have been selected based on their suitability to be included in L2 learning materials. As our annotation scheme, we use a customised version of the 5-point lexical complexity prediction scale (Shardlow et al., 2020), tailored to the vocabulary knowledge continuum (which ranges from no knowledge over receptive mastery to productive mastery; Schmitt, 2019). With LexComSpaL2, we aim to address the lack of relevant data for multi-category difficult prediction at word level for L2 learners of other languages than English.
Degraeuwe, Jasper Goethals, Patrick
LexComSpaL2: A Lexical Complexity Corpus for Spanish as a Foreign Language