L2 learners' proficiency evaluation using statistics based on dimensional compression of CEFR criteria

The purpose of this paper is to evaluate L2 (second language) learners' proficiency objectively. It was examined to estimate language proficiency using 94 statistics extracted from English conversation data on Japanese English learners' groups in educational institution. To predict Japanese learner's English proficiency represented as Global Rating scores of the Common European Framework of Reference for Languages (CEFR), the statistics were extracted automatically and/or manually, and were classified into 5 subcategories. By using canonical correlation analysis to the subcategories, canonical score, canonical loading and cross loading were calculated, and were analyzed on correlation to the CEFR Global Rating scores. The estimation experiment was carried out using a multiple regression model trained by data set of 135 learners and 12 canonical scores with higher correlation the CEFR Global Rating scores in cross-validation. The correlation score 0.888 was shown between predicted proficiency scores and the L2 learners' actual CEFR Global Rating scores. These results confirmed the usability of the 12 statistics compressed from the total 94 statistics for the objective evaluation of L2 learner's language proficiency.