Vocabulary Size of Thai Graduate Students in Different Disciplines and Their Opinions of Its Influences on the Use of AI in English Language Learning

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Bibliographic Details
Title: Vocabulary Size of Thai Graduate Students in Different Disciplines and Their Opinions of Its Influences on the Use of AI in English Language Learning
Language: English
Authors: Sumanee Pinweha, Sutthirak Sapsirin
Source: LEARN Journal: Language Education and Acquisition Research Network. 2026 19(1):343-375.
Availability: Language Institute of Thammasat University. The Prachan Campus, 2 Prachan Road, Bangkok 10200 Thailand. e-mail: learnjournal@gmail.com; Web site: https://www.tci-thaijo.org/index.php/learn
Peer Reviewed: Y
Page Count: 33
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Graduate Students, Vocabulary, Student Attitudes, Artificial Intelligence, English (Second Language), Second Language Learning, Technology Uses in Education, Intellectual Disciplines, Foreign Countries
Geographic Terms: Thailand
ISSN: 2630-0672
2672-9431
Abstract: This study investigates the vocabulary size of Thai graduate students across science and non-science disciplines, alongside their opinions on the effects of vocabulary size on their use of AI tools in their English language learning. A total of 217 students from a public Thai university completed the Updated Vocabulary Levels Test (Webb et al., 2017) and engaged in semi-structured interviews. Quantitative data were analyzed using descriptive statistics, revealing that most students had a low vocabulary size. The Mann-Whitney U test showed significantly higher performance among science students at the 1,000-, 4,000-, and 5,000-word levels. Qualitative data from interviews showed that vocabulary size may not influence most types of AI-assisted language learning activities, their trust in it, or their reliance on AI for language learning, except for the choice of prompt language. These findings offer implications for English vocabulary instruction and highlight the importance of integrating AI-assisted language learning tools with lexical development in higher education contexts.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1508722
Database: ERIC
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