The Community for Technology Leaders
Advanced Learning Technologies, IEEE International Conference on (2009)
Riga, Latvia
July 15, 2009 to July 17, 2009
ISBN: 978-0-7695-3711-5
pp: 88-92
This paper proposes a topic-independent method for automatically scoring essay content. Unlike conventional topic-dependent methods, it predicts the human score of a given essay without training essays written to the same topic as the target essay. To achieve this, this paper introduces a new measure called MIDF that measures how important and relevant a word is in a given essay. The proposed method predicts the score relying on the distribution of MIDF. Surprisingly, experiments show that the proposed method achieves an accuracy of 0.848 and performs as well as or even better than conventional topic-dependent methods.
automated essay scoring, language learning, corpus, essay content evaluation, English

R. Nagata, Y. Yabuta and J. Kakegawa, "A Topic-Independent Method for Automatically Scoring Essay Content Rivaling Topic-Dependent Methods," 2009 Ninth IEEE International Conference on Advanced Learning Technologies (ICALT), Riga, 2009, pp. 88-92.
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