Dr. Masayuki HIRATA

Lecturer

Email
lcmasa@ust.hk
Telephone
2358-7853
Room
3403

Dr Masayuki Hirata is a lecturer at the Center for Language Education at The Hong Kong University of Science and Technology. He received his BA in Linguistics from Waseda University, his MA in Language Studies from Lancaster University, and his PhD in Corpus Linguistics from the City University of Hong Kong. His research interests span Corpus Linguistics, Computational Linguistics, Cognitive Linguistics, Stylistics, and Lexicography. He has presented papers on these topics at international conferences such as the International Conference on Meaning-Text Theory, the UK Cognitive Linguistics Conference, and the International Cognitive Linguistics Conference. Dr Hirata has also worked as a bilingual lexicographer for Longman Dictionaries, where he contributed to building the first large-sized Japanese corpus (the Longman Japanese Corpus) and compiled the first bilingual-corpus-based English to Japanese lexicon (the Longman English-Japanese Dictionary). He has over 15 years of experience in teaching Japanese and English at the tertiary level in Japan and Hong Kong. Dr Hirata is passionate about exploring the connections between language education and the use of technology, and he aims to enhance his students' linguistic skills, intercultural competence, and individual learning.

Scholarship

2025 Conference Paper / Presentation

Evaluating the Use of a Chatbot in an Elementary Japanese Course:: Benefits, Challenges, and Student Feedback

HIRATA, Masayuki

Press: Society of Japanese Language Education Hong Kong
ISBN: 978-988-77485-2-6
Source: 第13回国際日本語教育・日本研究シンポジウム / edited by Leung Maggie . Hong Kong: Society of Japanese Language Education Hong Kong, 2025, p. 12-38

This paper evaluates the implementation of a chatbot in an elementary Japanese language course at a tertiary institution, examining its benefits and challenges through detailed student feedback. Utilising a mixed-methods approach that incorporates both qualitative and quantitative research methods, data was collected over several months from 40 students enrolled in a zero-beginner Japanese course at a university. The chatbot, designed to function as a private tutor, assisted students with vocabulary, grammar, and pronunciation and provided an interactive and personalised learning environment. Student feedback was systematically categorised and analysed to identify trends and patterns in usage and satisfaction. The results indicate that while chatbots offer personalised and interactive learning experiences, their effectiveness is contingent on the accuracy of responses and their ability to adapt to the evolving needs of students as their proficiency increases. The study underscores the need for enhanced features, such as improved contextual understanding and accuracy, to support students’ progress in language learning. The study identifies several challenges, such as ensuring the accuracy of chatbot responses by constantly monitoring the information provided in relation to learners’ proficiency levels. These challenges highlight areas for future improvement and research.

2025 Conference Paper / Presentation

Understanding Metaphorical Expressions in Japanese by Generative AIs: A Comparative Study of Text and Image Generation

HIRATA, Masayuki

Location: , Hong Kong
Source: Paper presented at The 14th International Symposium on Japanese Language Education and Japanese Studies, , Hong Kong, p. 271-278

<br/>

2025 Conference Paper / Presentation

日本語教育におけるチャットボットの正確性と文脈理解の向上

HIRATA, Masayuki

Location: , Taiwan, Province of China
Source: Paper presented at 2025年第8回AIと日本語教育国際シンポジウム【日本語教育AI サミット2025 in Taiwan】, , Taiwan, Province of China, p. 102-109

チャットボットの言語教育への利用は、個人化されたインタラクティブな学習体験を提供する可能性を示唆している。一方、チャットボットによる応答の正確性や文脈に即した情報提供などには課題が残り、その使用の効果を妨げる障壁となっている。初級日本語コースにおけるチャットボット使用を評価した先行研究を基に、本研究では、チャットボットの応答の正確性や文脈に即したフィードバックを提供する能力など、改善すべき重要な領域を特定し、文法データベース、語彙定義、誤用などの情報を参照させ、より先進的なAIモデルを活用することで、チャットボットの正確性を向上させるためのフレームワークを提案する。この提案は、実験的な環境で調査・テストされ、予備結果は、チャットボットの応答の正確性と文脈理解において改善を示している。本研究は、AIを活用した教育に関して実践的な解決策を示し、言語学習におけるチャットボットの有用性を高めることに貢献する。今後の研究課題としては、チャットボットの長期的な影響を評価するための縦断的研究や、異なる学習者レベル間での比較など、チャットボットの使用に関するより包括的な理解を提供することなどが挙げられる。

2023 Conference Paper / Presentation

Text-Generative AI in Language Learning: Assessing its Impact and Advantages over Corpus-based Approaches

Hirata, Masayuki

Press: The University of Hong Kong, School of Professional and Continuing Education
Source: Paper presented at Proceedings of the 13th International Symposium on Japanese Language Education and Japanese Studies, p. 112-118
2020 Conference Paper / Presentation

Practices and possibilities of online learning and teaching in foreign language education

Hirata, Masayuki

Source: Paper presented at Conference Contribution
2015 Conference Paper / Presentation

A corpus-based study of noun-adjective continuum in Japanese and English

Fang, A.C.; Hirata, Masayuki

Source: Paper presented at Proceedings of the 9th International Conference of Asian Association of Lexicography, p. 281-301
2014 Conference Paper / Presentation

A corpus-based study of bilingual encoding processes from the Japanese language to the English language

Hirata, Masayuki

Source: Paper presented at 30 Years of Research and Innovation@CityU
2013 Conference Paper / Presentation

Emotional adjectives in Japanese and their subjectivity

Hirata, Masayuki

Source: Paper presented at 12th International Cognitive Linguistics Conference
2012 Conference Paper / Presentation

Schematic variations of the grammatical construction ‘X-wa Y-ga Z (adjective)’ in Japanese

Hirata, Masayuki

Source: Paper presented at 4th UK Cognitive Linguistics Conference
2011 Conference Paper / Presentation

A lexicogrammatical perspective in encoding dictionaries

Hirata, Masayuki

Source: Paper presented at Conference on Corpus Linguistics in China
2011 Conference Paper / Presentation

A lexicogrammatical perspective in encoding dictionaries––with reference to ‘pain’ examples in English and in Japanese

Hirata, Masayuki

Source: Paper presented at Proceedings of the 5th International Conference on Meaning-Text Theory, p. 98-107