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Tommy Hastomo; Utami Widiati; Francisca Maria Ivone; Evynurul Laily Zen; Muhamad Hasbi; Buyun Khulel – Intercultural Communication Education, 2025
Globalization has increased the demand for English proficiency and intercultural competence. However, English instruction in Indonesia often focuses on grammar and vocabulary, with limited emphasis on cultural understanding. Although AI tools are commonly used to support language learning, their potential to promote intercultural learning remains…
Descriptors: Artificial Intelligence, Foreign Countries, English (Second Language), Second Language Learning
Jongwon Lee; Tereza Cimová; Ellen J. Foster; Derek France; Lenka Krajnáková; Lynn Moorman; Sonja Rewhorn; Jiaqi Zhang – International Research in Geographical and Environmental Education, 2025
Generative artificial intelligence (GenAI) represents a major leap forward in AI technology, offering the potential to reshape education in various aspects. This paper explores the transformative potential of GenAI in geography education, focusing on its impacts across curriculum, pedagogy, assessment, and fieldwork, through the lens of the…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Geography
Maria Navío-Inglés; Sergio Tirado-Olivares; Javier del Olmo-Muñoz; Jesús Guzmán Mora – Computers in the Schools, 2025
Artificial intelligence (AI), specifically conversational AI, is increasingly utilized to enhance writing skills, necessitating future teachers' awareness of its capabilities for implementation. The present mixed-methods study explores the ability of AI to write a summary and an argumentative text and pre-service teachers' perceptions of it. A…
Descriptors: Artificial Intelligence, Writing Skills, Preservice Teachers, Student Attitudes
Mimi Li; Flavia Belpoliti; Gouda Taha; Meixiu Zhang – Foreign Language Annals, 2025
This qualitative study, drawing on positioning analysis, examines four world language teachers' reported practices of integrating ChatGPT into their instruction. The participants were enrolled in the graduate-level Applied Linguistics or Spanish Language Teaching program at a public university in the southcentral US. This study addresses two…
Descriptors: Artificial Intelligence, Natural Language Processing, Teaching Methods, Technology Integration
Ortín, Ramsés; Simonet, Miquel – Studies in Second Language Acquisition, 2022
One feature of Spanish that presents some difficulties to second language (L2) learners whose first language (L1) is English concerns lexical stress. This study explores one aspect of the obstacle these learners face, weak phonological processing routines concerning stress inherited from their native language. Participants were L1 English L2…
Descriptors: Spanish, Second Language Learning, Phonology, Suprasegmentals
Bordag, Denisa; Opitz, Andreas – Studies in Second Language Acquisition, 2022
In two visual priming experiments, we investigated the relation of form-identical word forms with different grammatical functions in L1 and L2 German. Four different grammatical types (inflected verbs, infinitives, deverbal conversion forms, and countable nouns) were used as primes and their influence on the processing of form-identical inflected…
Descriptors: Language Processing, Second Language Instruction, Second Language Learning, Native Language
Lin, Jiayin; Sun, Geng; Beydoun, Ghassan; Li, Li – Educational Technology & Society, 2022
A newly emerged micro learning service offers a flexible formal, informal, or non-formal online learning opportunity to worldwide users with different backgrounds in real-time. With the assist of big data technology and cloud computing service, online learners can access tremendous fine-grained learning resources through micro learning service.…
Descriptors: Translation, Natural Language Processing, Informal Education, Online Courses
Dotan, Dror; Brutman, Nadin – Cognitive Research: Principles and Implications, 2022
Representing the base-10 structure of numbers is a challenging cognitive ability, unique to humans, but it is yet unknown how precisely this is done. Here, we examined whether and how literate adults represent a number's full syntactic structure. In 5 experiments, participants repeated number-word sequences and we systematically varied the order…
Descriptors: Syntax, Phrase Structure, Cognitive Ability, Numbers
Hsu, Hao-Hsuan; Huang, Nen-Fu – IEEE Transactions on Learning Technologies, 2022
This article introduces Xiao-Shih, the first intelligent question answering bot on Chinese-based massive open online courses (MOOCs). Question answering is critical for solving individual problems. However, instructors on MOOCs must respond to many questions, and learners must wait a long time for answers. To address this issue, Xiao-Shih…
Descriptors: Foreign Countries, Artificial Intelligence, Online Courses, Natural Language Processing
Wan, Yao; Dechsubha, Thawascha – Education Quarterly Reviews, 2022
The world is familiar with Chinese wine but neglects its attractive partner, Thumb Fight ([foreign characters omitted]). The Thumb Fight is a precious traditional Chinese drinking game. However, its rare research still focuses on its history, not the translation process during its dynamic playing logic. The semiotic is access to logic from…
Descriptors: Chinese, Semiotics, Translation, Language Processing
Tamaoka, Katsuo; Ito, Takane; Mansbridge, Michael P. – Journal of Psycholinguistic Research, 2022
The present study investigated the canonical position of instrumental and locative adverbial phrases in both Japanese sentences and noun phrases to determine whether the canonical positions are parallel. A series of sentence/phrase decision tasks were used to compare sentences with different word-orders, including sentences with SA"dv"OV…
Descriptors: Sentence Structure, Phrase Structure, Japanese, Nouns
Almotairi, Maram; Fkih, Fethi – Journal of Education and e-Learning Research, 2022
The Question answering (QA) system plays a basic role in the acquisition of information and the e-learning environment is considered to be the field that is most in need of the question-answering system to help learners ask questions in natural language and get answers in short periods of time. The main problem in this context is how to understand…
Descriptors: Semantics, Natural Language Processing, Intelligent Tutoring Systems, Ambiguity (Semantics)
Wu, Shi Hui; Henderson, Lisa-Marie; Gennari, Silvia P. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2022
Sentence production and comprehension both draw on linguistic knowledge, but current research is unclear on whether these fundamental language tasks involve similar or distinct competitive processes. Previous studies suggest that production and comprehension may involve similar conflict resolution processes, but that production may additionally…
Descriptors: Individual Differences, Reading Comprehension, Sentences, Vocabulary
AuBuchon, Angela M.; Elliott, Emily M.; Morey, Candice C.; Jarrold, Christopher; Cowan, Nelson; Adams, Eryn J.; Attwood, Meg; Bayram, Büsra; Blakstvedt, Taran Y.; Büttner, Gerhard; Castelain, Thomas; Cave, Shari; Crepaldi, Davide; Fredriksen, Eivor; Glass, Bret A.; Guitard, Dominic; Hoehl, Stefanie; Hosch, Alexis; Jeanneret, Stéphanie; Joseph, Tanya N.; Koch, Christopher; Lelonkiewicz, Jaroslaw R.; Meissner, Grace; Mendenhall, Whitney; Moreau, David; Ostermann, Thomas; Özdogru, Asil Ali; Padovani, Francesca; Poloczek, Sebastian; Röer, Jan Philipp; Schonberg, Christina; Tamnes, Christian K.; Tomasik, Martin J.; Valentini, Beatrice; Vergauwe, Evie; Vlach, Haley; Voracek, Martin – Journal of Cognition and Development, 2022
A recent Registered Replication Report (RRR) of the development of verbal rehearsal during serial recall revealed that children verbalized at younger ages than previously thought, but did not identify sources of individual differences. Here, we use mediation analysis to reanalyze data from the 934 children ranging from 5 to 10 years old from the…
Descriptors: Language Processing, Phonology, Serial Ordering, Recall (Psychology)
Mead, Alan D.; Zhou, Chenxuan – Journal of Applied Testing Technology, 2022
This study fit a Naïve Bayesian classifier to the words of exam items to predict the Bloom's taxonomy level of the items. We addressed five research questions, showing that reasonably good prediction of Bloom's level was possible, but accuracy varies across levels. In our study, performance for Level 2 was poor (Level 2 items were misclassified…
Descriptors: Artificial Intelligence, Prediction, Taxonomy, Natural Language Processing

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