M. Zakaria Kurdi - Text Complexity Classification Based on Linguistic Information: Application to Intelligent Tutoring of ESL

jdmdh:6012 - Journal of Data Mining & Digital Humanities, 19 septembre 2020, 2020 - https://doi.org/10.46298/jdmdh.6012
Text Complexity Classification Based on Linguistic Information: Application to Intelligent Tutoring of ESLArticle

Auteurs : M. Zakaria Kurdi

    The goal of this work is to build a classifier that can identify text complexity within the context of teaching reading to English as a Second Language (ESL) learners. To present language learners with texts that are suitable to their level of English, a set of features that can describe the phonological, morphological, lexical, syntactic, discursive, and psychological complexity of a given text were identified. Using a corpus of 6171 texts, which had already been classified into three different levels of difficulty by ESL experts, different experiments were conducted with five machine learning algorithms. The results showed that the adopted linguistic features provide a good overall classification performance (F-Score = 0.97). A scalability evaluation was conducted to test if such a classifier could be used within real applications, where it can be, for example, plugged into a search engine or a web-scraping module. In this evaluation, the texts in the test set are not only different from those from the training set but also of different types (ESL texts vs. children reading texts). Although the overall performance of the classifier decreased significantly (F-Score = 0.65), the confusion matrix shows that most of the classification errors are between the classes two and three (the middle-level classes) and that the system has a robust performance in categorizing texts of class one and four. This behavior can be explained by the difference in classification criteria between the two corpora. Hence, the observed results confirm the usability of such a classifier within a real-world application.


    Volume : 2020
    Publié le : 19 septembre 2020
    Accepté le : 28 février 2020
    Soumis le : 8 janvier 2020
    Mots-clés : Computer Science - Computation and Language

    3 Documents citant cet article

    Statistiques de consultation

    Cette page a été consultée 1929 fois.
    Le PDF de cet article a été téléchargé 1185 fois.