A Corpus-Based Word Classification Method for Detecting Difficulty Level of English Proficiency Tests

Autor: Liang-Ching Chen, Kuei-Hu Chang, Shu-Ching Yang, Shin-Chi Chen
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Applied Sciences, Vol 13, Iss 3, p 1699 (2023)
Druh dokumentu: article
ISSN: 2076-3417
DOI: 10.3390/app13031699
Popis: Many education systems globally adopt an English proficiency test (EPT) as an effective mechanism to evaluate English as a Foreign Language (EFL) speakers’ comprehension levels. Similarly, Taiwan’s military academy also developed the Military Online English Proficiency Test (MOEPT) to assess EFL cadets’ English comprehension levels. However, the difficulty level of MOEPT has not been detected to help facilitate future updates of its test banks and improve EFL pedagogy and learning. Moreover, it is almost impossible to carry out any investigation effectively using previous corpus-based approaches. Hence, based on the lexical threshold theory, this research adopts a corpus-based approach to detect the difficulty level of MOEPT. The function word list and Taiwan College Entrance Examination Center (TCEEC) word list (which includes Common European Framework of Reference for Language (CEFR) A2 and B1 level word lists) are adopted as the word classification criteria to classify the lexical items. The results show that the difficulty level of MOEPT is mainly the English for General Purposes (EGP) type of CEFR A2 level (lexical coverage = 74.46%). The findings presented in this paper offer implications for the academy management or faculty to regulate the difficulty and contents of MOEPT in the future, to effectively develop suitable EFL curriculums and learning materials, and to conduct remedial teaching for cadets who cannot pass MOEPT. By doing so, it is expected the overall English comprehension level of EFL cadets is expected to improve.
Databáze: Directory of Open Access Journals
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