Abstract
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 institutions. To estimate the Japanese learner's English proficiency expressed 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 such as range, accuracy, fluency, interaction and coherence. Considering that each the category included at least 8 items, Recognition-Taguchi method was used for compressing these items and analyzing correlations between them and the Global Rating scores simply. Outputs were calculated in the 5 respective subcategories by the method, and correlations to the scores were analyzed. As the result, one of the outputs, sensitivity βs showed correlations to the scores, and especially the 4 sensitivity βs except for the subcategory accuracy indicated correlations of being more than to 0.650 the scores. The estimation experiment was carried out using a multiple regression model trained by data set of 135 learners and the 4 sensitivity βs with higher correlations to the CEFR Global Rating scores in cross-validation. The correlation coefficients of 0.900 was shown between predicted proficiency scores and the L2 learners' actual CEFR Global Rating scores. These results confirmed the usability of the 4 sensitivity βs extracted from the total 94 statistics for the objective evaluation of L2 learner's language proficiency.
Highlights
A number of approaches have been proposed to evaluate second language (L2) learners' proficiency
From the standpoint of quality engineering, ranking candidates and selecting criteria that influence in evaluating best students are conducted based on their suitability for MBA program by using Mahalanobis-Taguchi System (MTS) approach of Mahalanobis-Taguchi (MT) methods(9) adding Mahalanobis Distance (MD), orthogonal array (OA) and the signal/noise (SN) ratio as its outputs
To estimate the English learner's proficiencies, the adaptability of statistical measures extracted from English conversation data of groups of Japanese English learners in educational institutions is examined
Summary
A number of approaches have been proposed to evaluate second language (L2) learners' proficiency. In the field of education, statistical methods including data mining or machine learning are often adopted. These methods plays major roles in finding, extracting and analyzing both L2 learners' learning information such as patterns or processes from speech data(1)-(3). The L2 learners' proficiencies can be predicted by combining the data mining methods and L2 learner' data (4)-(8). These results are expected to feedback to many educational scenes in order to improve in studying and teaching approaches possible for both learners and educators more effectively. Correcting evaluation for learning efforts and results of every subjects in medical course students is tried by using Recognition-Taguchi method and the Mahalanobis Distance (MD) as its output (10)
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