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Article

AI Student: A Machine Reading Comprehension System for the Korean College Scholastic Ability Test

1
Department of Computer Science and Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Korea
2
Division of Computer Engineering, Hanshin University, Osan 18101, Korea
*
Author to whom correspondence should be addressed.
Academic Editors: Heui Seok Lim, Sanghyuk Lee, Yeongwook Yang and Imatitikua Aiyanyo
Mathematics 2022, 10(9), 1486; https://doi.org/10.3390/math10091486
Received: 7 April 2022 / Revised: 23 April 2022 / Accepted: 27 April 2022 / Published: 29 April 2022
Machine reading comprehension is a question answering mechanism in which a machine reads, understands, and answers questions from a given text. These reasoning skills can be sufficiently grafted into the Korean College Scholastic Ability Test (CSAT) to bring about new scientific and educational advances. In this paper, we propose a novel Korean CSAT Question and Answering (KCQA) model and effectively utilize four easy data augmentation strategies with round trip translation to augment the insufficient data in the training dataset. To evaluate the effectiveness of KCQA, 30 students appeared for the test under conditions identical to the proposed model. Our qualitative and quantitative analysis along with experimental results revealed that KCQA achieved better performance than humans with a higher F1 score of 3.86. View Full-Text
Keywords: academic reading skills; Korean College Scholastic Ability Test; Korean CSAT question and answering; machine reading comprehension academic reading skills; Korean College Scholastic Ability Test; Korean CSAT question and answering; machine reading comprehension
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MDPI and ACS Style

Kim, G.; Lee, S.; Park, C.; Jo, J. AI Student: A Machine Reading Comprehension System for the Korean College Scholastic Ability Test. Mathematics 2022, 10, 1486. https://doi.org/10.3390/math10091486

AMA Style

Kim G, Lee S, Park C, Jo J. AI Student: A Machine Reading Comprehension System for the Korean College Scholastic Ability Test. Mathematics. 2022; 10(9):1486. https://doi.org/10.3390/math10091486

Chicago/Turabian Style

Kim, Gyeongmin, Soomin Lee, Chanjun Park, and Jaechoon Jo. 2022. "AI Student: A Machine Reading Comprehension System for the Korean College Scholastic Ability Test" Mathematics 10, no. 9: 1486. https://doi.org/10.3390/math10091486

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