An approach to automatic answering for English reading comprehension tests

This study focuses on the reading comprehension problem with multiple-choice answers, using the BERT model to achieve the highest performance. The ultimate goal is to create a solution to help solve reading comprehension problems without any reasoning or knowledge, suitable for the level of students in grades six and seven. The model will solve factoid questions from a given text. Our research topic will use a deep learning model-based approach to create a model that automatically answers the English reading comprehension question. We obtain promising results to give an accuracy of 78 percent.

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Publication Details

Journal
HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE - ENGINEERING AND TECHNOLOGY
Published
2024-09-04
DOI
https://doi.org/10.46223/hcmcoujs.tech.en.14.2.2917.2024
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

An approach to automatic answering for English reading comprehension tests

Hieu Chi Tran, H. T. Duong, Phuong Bui
HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE - ENGINEERING AND TECHNOLOGY
Natural Language Processing Techniques
article

An approach to automatic answering for English reading comprehension tests

Hieu Chi Tran, H. T. Duong, Phuong Bui
article en

Abstract

This study focuses on the reading comprehension problem with multiple-choice answers, using the BERT model to achieve the highest performance. The ultimate goal is to create a solution to help solve reading comprehension problems without any reasoning or knowledge, suitable for the level of students in grades six and seven. The model will solve factoid questions from a given text. Our research topic will use a deep learning model-based approach to create a model that automatically answers the English reading comprehension question. We obtain promising results to give an accuracy of 78 percent.

HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE - ENGINEERING AND TECHNOLOGYVol. 14(2)
Ho Chi Minh City Open University (VN)
Openalex Percentile: Top 82%
Natural Language Processing Techniques
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