• Asia Pacific Journal of Corpus Research
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• v.1 no.1
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• pp.61-94
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• 2020

The present study examined vocabulary usage in elementary English classrooms in Japan using elementary school corpus. The authors used three wordlists to benchmark the lexical items for four classes in the corpus: the CEFR-J, the General Service List (GSL), and Academic Word List (AWL). The percentage of vocabulary usage belonging to the Level A1 in the CEFR-J was below 15% (Class A: 12.1%, Class B: 12.6%, Class C: 8.9%, and Class D: 13.6%) with no statistical difference between levels. The mean ratio of Level A2 vocabulary items was below 10%, and all classes showed less than 1% of vocabulary usage for the Levels B1 and B2. Over 70% of all vocabulary items in the corpus belonged to the most frequent 1,000-word band (level 1) of the GSL, while the next most frequent word band (level 2 of the GSL and AWL) accounted for less than 10%. The results suggest that elementary school English teachers should use more vocabulary items in the CEFR-J Level A1. The findings demonstrate that elementary school teachers are less likely to expose their pupils to grammatically well-structured sentences with an abundance of lexical items since the teachers repeatedly use the same lexemes in each class.

• Asia Pacific Journal of Corpus Research
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• v.4 no.2
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• pp.75-87
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• 2023

This paper presents a revised version of the vocabulary analyzer for self-reflection (VACSR), called VACSR v.2.0. The initial version of the VACSR automatically analyzes the occurrences and the level of vocabulary items in the transcribed texts, indicating the frequency, the unused vocabulary items, and those not belonging to either scale. However, it overlooked words with multiple parts of speech due to their identical headword representations. It also needed to provide more explanatory result tables from different corpora. VACSR v.2.0 overcomes the limitations of its predecessor. First, unlike VACSR v.1, VACSR v.2.0 distinguishes words that are different parts of speech by syntactic parsing using Stanza, an open-source Python library. It enables the categorization of the same lexical items with multiple parts of speech. Second, VACSR v.2.0 overcomes the limited clarity of VACSR v.1 by providing precise result output tables. The updated software compares the occurrence of vocabulary items included in classroom corpora for each level of the Common European Framework of Reference-Japan (CEFR-J) wordlist. A pilot study utilizing VACSR v.2.0 showed that, after converting two English classes taught by a preservice English teacher into corpora, the headwords used mostly corresponded to CEFR-J level A1. In practice, VACSR v.2.0 will promote users' reflection on their vocabulary usage and can be applied to teacher training.

• Asia Pacific Journal of Corpus Research
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• v.1 no.1
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• pp.127-132
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• 2020

The purpose of this review is to provide local readers, more specifically, Korean student readers who are not all that familiar with the English language a general overview of research articles that have been published in Asia Pacific Journal of Corpus Research vol. 1, no. 1. A brief summary of each research article focusing on research methods and then followed by an overall review and some insights on research issues will be presented.