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Leveling L2 Texts Through Readability: Combining Multilevel Linguistic Features with the CEFR.
- Source :
-
Modern Language Journal . Jun2015, Vol. 99 Issue 2, p371-391. 21p. 1 Black and White Photograph, 5 Diagrams, 6 Charts, 2 Graphs. - Publication Year :
- 2015
-
Abstract
- Selecting appropriate texts for L2 (second/foreign language) learners is an important approach to enhancing motivation and, by extension, learning. There is currently no tool for classifying foreign language texts according to a language proficiency framework, which makes it difficult for students and educators to determine the precise difficulty/complexity levels of an unclassified text. Taking the Chinese language as an example, this study aimed to create a readability assessment system, called the Chinese Readability Index Explorer for Chinese as a Foreign Language (CRIE-CFL), in order to level-that is, to sort by proficiency level-texts that will be used for instructional purposes. The framework of choice in this project is the Common European Framework of Reference (CEFR). A team of expert CFL teachers first classified 1,578 CFL texts into their appropriate CEFR levels. A set of 30 CFL readability features was then developed or drawn from previous research, and sorted according to importance using F-scores. In addition, a support vector machine model was trained by sequentially integrating the features into the model to optimize accuracy. The empirical evaluation of CRIE-CFL revealed average exact- and adjacent-level accuracies of 74.97% and 99.62%, respectively, for predicting the expert classification of a text. The functionalities of CRIE-CFL are introduced and discussed. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00267902
- Volume :
- 99
- Issue :
- 2
- Database :
- Academic Search Index
- Journal :
- Modern Language Journal
- Publication Type :
- Academic Journal
- Accession number :
- 108580335
- Full Text :
- https://doi.org/10.1111/modl.12213