APJCR_2023_4_2_57

Asia Pacific Journal of Corpus Research Vol. 4, No. 2, pp. 57-74
Abbreviation: APJCR
e-ISSN: 2733-8096
Publication date: 31 December 2023
Received: 16 October 2023 / Received in Revised Form: 17 November 2023 / Accepted: 11 December 2023
DOI: https://doi.org/10.22925/apjcr.2023.4.2.57

An attempt to measure the familiarity of specialized Japanese in the nursing care field

Haihong Huang (Kyoto University), JAPAN; Hiroyuki Muto (Osaka Metropolitan University), JAPAN; Toshiyuki Kanamaru (Kyoto University), JAPAN
Copyright 2023 APJCR

This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Having a firm grasp of technical terms is essential for learners of Japanese for Specific Purposes (JSP). This research aims to analyze Japanese nursing care vocabulary based on objective corpus-based frequency and subjectively rated word familiarity. For this purpose, we constructed a text corpus centered on the National Examination for Certified Care Workers to extract nursing care keywords. The Log-Likelihood Ratio (LLR) was used as the statistical criterion for keyword identification, giving a list of 300 keywords as target words for a further word recognition survey. The survey involved 115 participants of whom 51 were certified care workers (CW group) and 64 were individuals from the general public (GP group). These participants rated the familiarity of the target keywords through crowdsourcing. Given the limited sample size, Bayesian linear mixed models were utilized to determine word familiarity rates. Our study conducted a comparative analysis of word familiarity between the CW group and the GP group, revealing key terms that are crucial for professionals but potentially unfamiliar to the general public. By focusing on these terms, instructors can bridge the knowledge gap more efficiently.

Keywords

Corpus Frequency, Word Familiarity, Nursing Care, JSP, Technical Terms

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The Authors

Haihong Huang is a PhD candidate at Graduate School of Human and Environmental Studies of Kyoto University. Her principal research lies in the field of corpus linguistics and Japanese for Specific Purposes. Her research areas include Japanese vocabulary learning, in particular corpus compilation.

Hiroyuki Muto is an Associate Professor at Graduate School of Sustainable System Sciences of Osaka Metropolitan University. He completed a PhD in Human Sciences at Osaka University. His research interests include perceptual / cognitive psychology and Bayesian statistical modeling.

Toshiyuki Kanamaru is an Associate Professor at the Institute for Liberal Arts and Sciences of Kyoto University. He holds a Ph.D. in Human and Environmental Studies from Kyoto University. His research interests include teaching English using cognitive linguistics and natural language processing.

The Authors’ Addresses

First Author
Haihong Huang
PhD Student
Graduate School of Human and Environmental Studies, Kyoto University
Yoshida-nihonmatsu-cho, Sakyo-ku, Kyoto 606-8501, JAPAN
E-mail: huang.haihong.46x@st.kyoto-u.ac.jpCo-author
Hiroyuki Muto
Associate Professor
Graduate School of Sustainable System Sciences, Osaka Metropolitan University
1-1 Gakuen-cho, Naka-ku, Sakai, Osaka 599-8531, JAPAN.
E-mail: mutopsy@omu.ac.jp

Co-author and Corresponding Author
Toshiyuki Kanamaru
Associate Professor
Institute for Liberal Arts and Sciences, Kyoto University
Yoshida-nihonmatsu-cho, Sakyo-ku, Kyoto 606-8501, JAPAN
E-mail: kanamaru.toshiyuki.4z@kyoto-u.ac.jp

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