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Linda Espey; Marta Ghio; Christian Bellebaum; Laura Bechtold – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2024
We used a novel linguistic training paradigm to investigate the experience-dependent acquisition, representation, and processing of novel emotional and neutral abstract concepts. Participants engaged in mental imagery (n = 32) or lexico-semantic rephrasing (n = 34) of linguistic material during five training sessions and successfully learned the…
Descriptors: Linguistic Input, Concept Teaching, Concept Formation, Learning Processes
Sebastian Hobert; Florian Berens – Educational Technology Research and Development, 2024
Individualized learning support is an essential part of formal educational learning processes. However, in typical large-scale educational settings, resource constraints result in limited interaction among students, teaching assistants, and lecturers. Due to this, learning success in those settings may suffer. Inspired by current technological…
Descriptors: Individualized Instruction, Intelligent Tutoring Systems, Learning Processes, Teaching Methods
Jessie S. Barrot – Technology, Knowledge and Learning, 2024
This emerging technology report delves into the role of ChatGPT, an OpenAI conversational AI, in language learning. The initial section introduces ChatGPT's nature and highlights its features, including accessibility, personalization, immersive learning, and instant feedback, which render it a valuable asset for language learners and educators…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Language Acquisition
Linyu Zhang; Nor Shahila Mansor; Akmar Hayati Ahmad Ghazali; Mengduan Li – Eurasian Journal of Applied Linguistics, 2024
In the field of translation studies, while re-narration is commonly observed in translated works, there is a noticeable lack of research focusing on re-narration specifically within wenyan translations. Addressing this gap, this study aims to investigate how re-narration occurs in wenyan translation through the framing strategies employed by…
Descriptors: Translation, Chinese, Language Research, Language Processing
Hinano Iida; Kimi Akita – Cognitive Science, 2024
Iconicity is a relationship of resemblance between the form and meaning of a sign. Compelling evidence from diverse areas of the cognitive sciences suggests that iconicity plays a pivotal role in the processing, memory, learning, and evolution of both spoken and signed language, indicating that iconicity is a general property of language. However,…
Descriptors: Japanese, Cognitive Science, Language Processing, Memory
Clinton Chidiebere Anyanwu; Pauline Ndidi Ononiwu; Grace Ngozi Isiozor – Education and Information Technologies, 2024
In contemporary society, information and communication technology permeates every aspect of human life, including education. This study investigates the impact of WhatsApp chatbot technology and Glaser's teaching approaches on the academic performance of economics education students in tertiary institutions. Grounded in activity theory, the study…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Teaching Methods
Fábio Albuquerque; Paula Gomes Dos Santos – Cogent Education, 2024
Using a quasi-experimental method and content analysis as a technique, this study tests ChatGPT, in its version 4, by assessing its textual characteristics and overall understanding regarding the recognition criteria of provisions under International Accounting Standards (IAS) 37, as issued by the International Accounting Standards Board (IASB).…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Accounting
Jeya Amantha Kumar; Min Zhuang; Stephen Thomas – Natural Sciences Education, 2024
Chat Generative Pre-Trained Transformer (ChatGPT) has emerged as a powerful artificial intelligence (AI) tool with an aptitude to transform course design in higher education significantly. While ChatGPT's applications in education are substantially growing, its role in natural sciences, particularly in course planning and content generation among…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Natural Sciences
Maki Kubota; Jorge González Alonso; Merete Anderssen; Isabel Nadine Jensen; Alicia Luque; Sergio Miguel Pereira Soares; Yanina Prystauka; Øystein A. Vangsnes; Jade Jørgen Sandstedt; Jason Rothman – Language Learning, 2024
The current study investigated gender (control) and number (target) agreement processing in Northern and non-Northern Norwegians living in Northern Norway. Participants varied in exposure to Northern Norwegian (NN) dialect(s), where number marking differs from most other Norwegian dialects. In a comprehension task involving reading NN dialect…
Descriptors: Norwegian, Dialects, Grammar, Language Processing
David Baidoo-Anu; Daniel Asamoah; Isaac Amoako; Inuusah Mahama – Discover Education, 2024
This study examined the perspectives of Ghanaian higher education students on the use of ChatGPT. The Students' ChatGPT Experiences Scale (SCES) was developed and validated to evaluate students' perspectives of ChatGPT as a learning tool. A total of 277 students from universities and colleges participated in the study. Through exploratory factor…
Descriptors: Student Attitudes, Artificial Intelligence, Higher Education, Foreign Countries
Du Gan; Kanokporn Numtong; Hao Li; Songyu Jiang – Eurasian Journal of Applied Linguistics, 2024
This study applies the Apriori algorithm to analyse patterns, syntactic structures, and thematic clusters in Chinese studies data from various genres. This study aims to identify recurring linguistic elements in order to shed light on the dynamic nature of the Chinese language across different contexts and time periods. The Apriori algorithm is…
Descriptors: Chinese, Applied Linguistics, Algorithms, Computational Linguistics
David R. Firth; Mason Derendinger; Jason Triche – Information Systems Education Journal, 2024
In this paper we describe a framework for teaching students when they should, or should not use generative AI such as ChatGPT. Generative AI has created a fundamental shift in how students can complete their class assignments, and other tasks such as building resumes and creating cover letters, and we believe it is imperative that we teach…
Descriptors: Cheating, Artificial Intelligence, Man Machine Systems, Natural Language Processing
Joy He-Yueya; Noah D. Goodman; Emma Brunskill – International Educational Data Mining Society, 2024
Creating effective educational materials generally requires expensive and time-consuming studies of student learning outcomes. To overcome this barrier, one idea is to build computational models of student learning and use them to optimize instructional materials. However, it is difficult to model the cognitive processes of learning dynamics. We…
Descriptors: Artificial Intelligence, Natural Language Processing, Instructional Materials, Computer Uses in Education
Jiayi Zhang; Conrad Borchers; Vincent Aleven; Ryan S. Baker – International Educational Data Mining Society, 2024
Think-aloud protocols are a common method to study self-regulated learning (SRL) during learning by problem-solving. Previous studies have manually transcribed and coded students' verbalizations, labeling the presence or absence of SRL strategies and then examined these SRL codes in relation to learning. However, the coding process is difficult to…
Descriptors: Artificial Intelligence, Technology Uses in Education, Protocol Analysis, Self Management
Rajaram, Melissa – Journal of Child Language, 2022
Multisyllabic words constitute a large portion of children's vocabulary. However, the relationship between phonological neighborhood density and English multisyllabic word learning is poorly understood. We examine this link in three, four and six year old children using a corpus-based approach. While we were able to replicate the well-accepted…
Descriptors: Phonology, Language Acquisition, English, Computational Linguistics

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