Using Linguistic Features to Predict Readability of Short Essays for Senior High School Students in Taiwan

We investigated the problem of classifying short essays used in comprehension tests for senior high school students in Taiwan. The tests were for first and second year students, so the answers included only four categories, each for one semester of the first two years. A random-guess approach would achieve only 25% in accuracy for our problem. We analyzed three publicly available scores for readability, but did not find them directly applicable. By considering a wide array of features at the levels of word, sentence, and essay, we gradually improved the F measure achieved by our classifiers from 0.381 to 0.536.