| Title |
AI based Learning System for Grammar and Reading Comprehension Training |
| Authors |
조범근(Beom Geun Cho) ; 박상현(Sang Hyun Park) ; 최소미(So Mi Choi) ; 이수열(Suyeol Lee) ; 구형일(Hyung Il Koo) |
| DOI |
https://doi.org/10.5573/ieie.2025.62.1.67 |
| Keywords |
Syntactic parsing; Pattern matching; English education; Computational linguistics |
| Abstract |
Native speakers learn grammatical structures and modified relationships naturally. However, L2 learners who are learning a foreign language other than their native language do so through a conscious training process. In this paper, we propose a system to assist L2 learners in grammar and reading comprehension training using artificial intelligence. Specifically, the proposed system uses the results of Dependency Parsing and Constituency Parsing and represents each grammatical element as a Grammar Unit Fern. For a given sentence, by searching for the Grammar Unit Ferns contained in the parsing results in the given sentence, We are able to identify the grammatical components contained in the sentence and retrieve related example sentences in the corpus. We also propose an interactive way to express modified relations. Unlike existing methods, the proposed method allows users to freely navigate the complex and nested modified relations in a sentence. To evaluate the performance, we have constructed a database of 5,921 sentences from 10-year Korean college admission exam and their official preparation tests. The proposed system identified the grammatical elements in the sentences with an accuracy of 90.9% for 6 grammar unit. |