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Tal Ness; Valerie J. Langlois; Albert E. Kim; Jared M. Novick – Perspectives on Psychological Science, 2025
Understanding language requires readers and listeners to cull meaning from fast-unfolding messages that often contain conflicting cues pointing to incompatible ways of interpreting the input (e.g., "The cat was chased by the mouse"). This article reviews mounting evidence from multiple methods demonstrating that cognitive control plays…
Descriptors: Cognitive Ability, Language Processing, Psycholinguistics, Cues
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Jorge González Alonso; Pablo Bernabeu; Gabriella Silva; Vincent DeLuca; Claudia Poch; Iva Ivanova; Jason Rothman – International Journal of Multilingualism, 2025
The burgeoning field of third language (L3) acquisition has increasingly focused on intermediate stages of language development, aiming to establish the groundwork for comprehensive models of L3 learning that encompass the entire developmental sequence. This article underscores the importance of a robust epistemological foundation, advocating for…
Descriptors: Multilingualism, Artificial Languages, Second Language Learning, Individual Differences
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Takumi Kosaka – Reading and Writing: An Interdisciplinary Journal, 2025
This study examines context effects on lexical processing by low-proficiency Japanese learners of English during sentence comprehension, and the role of individual differences in verbal working memory (WM). Thirty Japanese learners of English as a second language (L2) and 27 speakers of English as a first language (L1) were recruited for a…
Descriptors: Second Language Learning, English (Second Language), Foreign Countries, Lexicology
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Linh Huynh; Danielle S. McNamara – Grantee Submission, 2025
We conducted two experiments to assess the alignment between Generative AI (GenAI) text personalization and hypothetical readers' profiles. In Experiment 1, four LLMs (i.e., Claude 3.5 Sonnet; Llama; Gemini Pro 1.5; ChatGPT 4) were prompted to tailor 10 science texts (i.e., biology, chemistry, physics) to accommodate four different profiles…
Descriptors: Natural Language Processing, Profiles, Individual Differences, Semantics
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Ellana Black; Kristen Betts – Impacting Education: Journal on Transforming Professional Practice, 2025
This convergent mixed methods research study investigated how a small, non-representative sample of Educational Doctorate (EdD) faculty perceive and use generative AI and how they have leveraged the technology to support EdD students. A cross-sectional survey was used to gather data from 27 EdD faculty members to assess their generative AI…
Descriptors: Doctoral Programs, Education Majors, College Faculty, Artificial Intelligence
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Chanyuan Gu; Samuel A. Nastase; Zaid Zada; Ping Li – npj Science of Learning, 2025
While evidence has accumulated to support the argument of shared computational mechanisms underlying language comprehension between humans and large language models (LLMs), few studies have examined this argument beyond native-speaker populations. This study examines whether and how alignment between LLMs and human brains captures the homogeneity…
Descriptors: Reading Comprehension, Native Language, Second Language Learning, Brain Hemisphere Functions
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Ke Li; Lulu Lun; Pingping Hu – Education and Information Technologies, 2025
Amid the ongoing discussion about the potential of LLMs (Large Language Models) to facilitate language learning, there has been a broad spectrum of views in academia. However, little is known about the different viewpoints of students and what contributes to these differences. In light of this, this study adopts Q-methodology, a mixed-methods…
Descriptors: Student Attitudes, Language Attitudes, Affordances, Artificial Intelligence