Personalized Automatic Quiz Generation Based on Reading Difficulty and Proficiency Level Prediction
Date Issued
2011
Date
2011
Author(s)
Chang, Hsiao-Pei
Abstract
A lot of research works have been done in the field of automatic quiz generation, however, almost all those studies generate all possible combination of quizzes and only few research consider difficulties of different quizzes. In this study, not only a quiz‘s difficulty but also the difference between learners and the reading difficulty of a document are taken into consideration. Therefore, we design a personalized automatic quiz generation system based on reading difficulty estimation scheme in a given document and proficiency level prediction for a second language learner. In the reading difficulty estimation scheme, we consult some meaningful lexical and grammatical features in early work, and then further consider several word frequency features from corpora, official grading indexes of vocabulary from language experts, and grammar patterns collected from textbooks — those which represent words and grammar patterns that the L2 learners have learned at various grade levels. In the proficiency level prediction, we estimate a learner‘s ability from three dimensions, which are vocabulary ability, grammar ability, and reading comprehension ability, and then further consider his historical performance to determine his proficiency level by weighted exponential moving average. A personalized news reading and testing experiment was conducted. The experimental results show that the proposed estimation outperforms the other estimations, and is close to the annotation of human experts. Moreover, It also shows that our system can increase learners‘ English proficiency, and provide a good prediction of learners‘ proficiency level.
Subjects
readability
reading difficulty
second language learning
linear regression model
automatic quiz generation
personalization
exponential moving average(EMA)
Type
thesis
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