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This study aims to develop a system to classify English sentences by the degree of difficulty by using English textbooks of Finland, Japan, and South Korea. First, the data sets are built by extracting features from English sentences included in 20 paragraphs from English textbooks used in Finland. The Random Forests algorithm is applied to the data set to build a classifier. This method leads to a classifier which is able to classify sentences with higher accuracy. Second, a two-tier classifier method is applied to wider datasets from textbooks of Finland. The experiment shows the effectiveness of implementing multi-tier classifiers. These two new methods are applied to textbooks used in Japan and South Korea. The results of the experiments show that a model which classifies English sentences with higher accuracy can be developed by following the proposed methods.

Classification of English sentences by the degree of difficulty using machine learning