• The Journal of the Korea Contents Association
• /
• v.20 no.10
• /
• pp.679-687
• /
• 2020

The present study aims to investigate lexical coverage of BNC (British National Corpus) word lists and 2015 Basic Vocabulary of Ministry of Education in 2020 EBS-linked textbooks and CSAT. For the data analysis, AntWordProfiler was used to find lexical coverage and frequency. The findings showed that Students can understand 95% of the tokens with a vocabulary of BNC 3,000 and 4,000 word-families in 2020 EBS-linked listening and reading books respectively. 98% can be understood with 4,000 word-families in the EBS-linked listening book while the same lexical coverage can be covered with 8,000 word-families in the EBS-linked reading textbook. By the way, 95% of the tokens can be understood with 2,000 and 4,000 word-families in 2020 CSAT listening and reading tests respectively, while 98% requires 4,000 and 7,000 word-families in the 2020 listening and reading tests respectively. In summary, students should understand more words in 2020 EBS-linked textbooks than in 2020 CSAT tests confirming Kim's (2016) findings. In summary, students should understand more words in 2020 EBS-linked textbooks than in 2020 CSAT tests.

• The Journal of the Korea Contents Association
• /
• v.21 no.12
• /
• pp.132-139
• /
• 2021

This corpus-driven research expounded the compilation of the most frequently occurring academic words in the domain of syntax and compared the extracted wordlist with Academic Word List(AWL) of Coxhead(2000) and General Service List(GSL) of West(1953) to examine their distribution and coverage within the syntax corpus. A specialized 546,074 token corpus, composed of widely used must-read syntax textbooks for English education majors, was loaded into and analyzed with AntWordProfiler 1.4.1. Under the parameter of lexical frequency, the analysis identified 288(50.5%) AWL word forms, appeared 16 times or more, as well as 218(38.2%) AWL items, occurred not exceeding 15 times. The analysis also indicated that the coverage of AWL and GSL accounted for 9.19% and 78.92% respectively and the combination of GSL and AWL amounted to 88.11% of all tokens. Given that AWL can be instrumental in serving broad disciplinary needs, this study highlighted the necessity to compile the domain-specific AWL as a lexical repertoire to promote academic literacy and competence.