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Liuying Gong; Jingyuan Chen; Fei Wu – IEEE Transactions on Learning Technologies, 2025
The capabilities of large language models (LLMs) in language comprehension, conversational interaction, and content generation have led to their widespread adoption across various educational stages and contexts. Given the fundamental role of education, concerns are rising about whether LLMs can serve as competent teachers. To address the…
Descriptors: Artificial Intelligence, Computer Software, Computational Linguistics, Comparative Analysis
Rebeckah K. Fussell; Megan Flynn; Anil Damle; Michael F. J. Fox; N. G. Holmes – Physical Review Physics Education Research, 2025
Recent advancements in large language models (LLMs) hold significant promise for improving physics education research that uses machine learning. In this study, we compare the application of various models for conducting a large-scale analysis of written text grounded in a physics education research classification problem: identifying skills in…
Descriptors: Physics, Computational Linguistics, Classification, Laboratory Experiments
Caroline F. Rowland; Amy Bidgood; Gary Jones; Andrew Jessop; Paula Stinson; Julian M. Pine; Samantha Durrant; Michelle S. Peter – Language Learning, 2025
A strong predictor of children's language is performance on non-word repetition (NWR) tasks. However, the basis of this relationship remains unknown. Some suggest that NWR tasks measure phonological working memory, which then affects language growth. Others argue that children's knowledge of language/language experience affects NWR performance. A…
Descriptors: Vocabulary Development, Comparative Analysis, Computational Linguistics, Language Skills
Yubin Xu; Lin Liu; Jianwen Xiong; Guangtian Zhu – Journal of Baltic Science Education, 2025
As the development and application of large language models (LLMs) in physics education progress, the well-known AI-based chatbot ChatGPT4 has presented numerous opportunities for educational assessment. Investigating the potential of AI tools in practical educational assessment carries profound significance. This study explored the comparative…
Descriptors: Physics, Artificial Intelligence, Computer Software, Accuracy
Yufan Zhao; Vahid Aryadoust – Language Testing, 2025
This study examined the semantic features of the simulated mini-lectures in the listening sections of the International English Language Testing System (IELTS) and the Test of English as a Foreign Language (TOEFL) based on automatized semantic analysis to explore the content validity of the two tests. Two study corpora were utilized, the IELTS…
Descriptors: Semantics, Computational Linguistics, Academic Language, Second Language Learning
Peng Wang; Kexin Yin; Mingzhu Zhang; Yuanxin Zheng; Tong Zhang; Yanjun Kang; Xun Feng – Education and Information Technologies, 2025
In the era of educational informatization, nurturing critical thinking skills has become a central focus. However, the current state of Chinese students' critical thinking development is concerning, prompting researchers to explore effective enhancement strategies. Based on constructivist learning theory, this study leveraged the advancements in…
Descriptors: Critical Thinking, Skill Development, Artificial Intelligence, Computer Software
Fatih Yavuz; Özgür Çelik; Gamze Yavas Çelik – British Journal of Educational Technology, 2025
This study investigates the validity and reliability of generative large language models (LLMs), specifically ChatGPT and Google's Bard, in grading student essays in higher education based on an analytical grading rubric. A total of 15 experienced English as a foreign language (EFL) instructors and two LLMs were asked to evaluate three student…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Computational Linguistics
Siowai Lo – Computer Assisted Language Learning, 2025
Neural Machine Translation (NMT) has gained increasing popularity among EFL learners as a CALL tool to improve vocabulary, and many learners have reported its helpfulness for vocabulary learning. However, while there has been some evidence suggesting NMT's facilitative role in improving learners' writing on the lexical level, no study has examined…
Descriptors: Translation, Computational Linguistics, Vocabulary Development, English (Second Language)
Tanjun Liu; Dana Gablasova – Computer Assisted Language Learning, 2025
Collocations, a crucial component of language competence, remain a challenge for L2 learners across all proficiency levels. While the data-driven learning (DDL) approach has shown great potential for collocation learning from a shorter-term perspective, this study investigates its effectiveness in the long term, examining both linguistic gains and…
Descriptors: Phrase Structure, Learning Analytics, English (Second Language), Second Language Instruction
Satoru Uchida – Vocabulary Learning and Instruction, 2025
Since its emergence, generative AI has significantly impacted various fields, including English language education. Numerous academic studies have investigated its capabilities in grammar correction, writing evaluation, and dynamics of user interaction. However, there have been insufficient investigations into whether texts generated by such AI…
Descriptors: Vocabulary Development, Language Proficiency, Rating Scales, Guidelines
Toyese Najeem Dahunsi; Thompson Olusegun Ewata – Language Teaching Research, 2025
Multi-word expressions are formulaic language universals with arbitrary and idiosyncratic collocations. Their usage and mastery are required of learners of a second language in achieving naturalness. However, despite the importance of multi-word expressions to mastering a second language, their syntactic architecture and colligational…
Descriptors: Computational Linguistics, Discourse Analysis, English (Second Language), Second Language Learning
Hanne Roothooft; Amparo Lázaro-Ibarrola; Bram Bulté – Language Teaching Research, 2025
Second language (L2) writing research has demonstrated that young learners discuss linguistic issues, make use of feedback, and show a generally positive disposition toward writing tasks. However, many issues deserve further investigation. Regarding task implementation, few studies have been conducted with young learners writing individually, and…
Descriptors: Error Correction, Feedback (Response), Accuracy, Writing Instruction
Amandine Hippolyte; Nicolas Ribeiro; Laure Ibernon; Nathalie Marec-Breton; Christelle Declercq – First Language, 2025
This study aimed to establish normative data for 145 words using phonological and semantic association tasks with 242 French schoolchildren, ranging from ages 5 (Grande Section) to 8 (Cours Elémentaire 2), providing a fundamental resource for future research and educational planning. The participants were engaged in two primary tasks: a free…
Descriptors: French, Phonology, Semantics, Preschool Children
Qing Guo; Junwen Zhen; Fenglin Wu; Yanting He; Cuilan Qiao – Journal of Educational Computing Research, 2025
The rapid development of large language models (LLMs) presented opportunities for the transformation of science and STEM education. Research on LLMs was in the exploratory phase, characterized by discussions and observations rather than empirical investigations. This study presented a framework for incorporating LLMs into Science and Engineering…
Descriptors: STEM Education, Computational Linguistics, Teaching Methods, Educational Change
Ahmet Can Uyar; Dilek Büyükahiska – International Journal of Assessment Tools in Education, 2025
This study explores the effectiveness of using ChatGPT, an Artificial Intelligence (AI) language model, as an Automated Essay Scoring (AES) tool for grading English as a Foreign Language (EFL) learners' essays. The corpus consists of 50 essays representing various types including analysis, compare and contrast, descriptive, narrative, and opinion…
Descriptors: Artificial Intelligence, Computer Software, Technology Uses in Education, Teaching Methods
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