Publication Date
In 2025 | 22 |
Descriptor
Source
Author
Abhishek Chugh | 1 |
Anjee Gorkhali | 1 |
Anna Paradís | 1 |
Ares Llop Naya | 1 |
Asim Shrestha | 1 |
Atika Qazi | 1 |
Bora Demir | 1 |
Borja Blanco | 1 |
Chaogang Wei | 1 |
Chia-Ju Lin | 1 |
Christina Manouilidou | 1 |
More ▼ |
Publication Type
Reports - Research | 22 |
Journal Articles | 21 |
Tests/Questionnaires | 2 |
Education Level
Higher Education | 13 |
Postsecondary Education | 13 |
Elementary Education | 1 |
Audience
Laws, Policies, & Programs
Assessments and Surveys
Raven Progressive Matrices | 1 |
What Works Clearinghouse Rating
Eleni Tsaprouni; Christina Manouilidou – Journal of Psycholinguistic Research, 2025
Deverbal formations in Greek, e.g. "mi'razo" 'to distribute' < "'mirazma" 'distributing' are considered morphologically complex lexical items. Previous psycholinguistic studies in Greek and English already highlighted the importance of lexical category and argument structure of the base verb in the processing of deverbal…
Descriptors: Language Processing, Word Processing, Greek, Psycholinguistics
Q. Feltgen; G. Cislaru – Discourse Processes: A Multidisciplinary Journal, 2025
The broader aim of this study is the corpus-based investigation of the written language production process. To this end, temporal markers have been keylog recorded alongside the writing processes to exploit pauses to segment the speech product into linear units of performance. However, identifying these pauses requires selecting the relevant…
Descriptors: Writing Processes, Writing Skills, Written Language, Intervals
Wali Khan Monib; Atika Qazi; Malissa Maria Mahmud – Education and Information Technologies, 2025
ChatGPT has emerged as a transformative technology with its remarkable ability to generate human-like responses, propelling its widespread adoption. While prior research has investigated the general landscape of AI-driven tools such as ChatGPT, the current study focuses specifically on exploring learners' experiences and perceptions regarding the…
Descriptors: Student Attitudes, Student Experience, Artificial Intelligence, Natural Language Processing
Borja Blanco; Monika Molnar; Irene Arrieta; César Caballero-Gaudes; Manuel Carreiras – Developmental Science, 2025
Language learning is influenced by both neural development and environmental experiences. This work investigates the influence of early bilingual experience on the neural mechanisms underlying speech processing in 4-month-old infants. We study how an early environmental factor such as bilingualism interacts with neural development by comparing…
Descriptors: Brain, Cognitive Processes, Cognitive Development, Speech Communication
Haerim Hwang – Written Communication, 2025
The use of subordination enables language users to achieve syntactic efficiency by allowing them to connect ideas in temporal/logical relation. Although the importance of subordination has been recognized in previous research on second language (L2) writing, it has been typically assessed with global indices that measure overall ratio of…
Descriptors: Second Language Learning, Writing (Composition), Form Classes (Languages), Syntax
Meiyun Wu; Haotian Liu; Xue Zhao; Li Lu; Yuyang Wang; Chaogang Wei; Yuhe Liu; Yu-Xuan Zhang – Developmental Science, 2025
To reveal the formation process of speech processing with early hearing experiences, we tracked the development of functional connectivity in the auditory and language-related cortical areas of 84 (36 female) congenitally deafened toddlers using repeated functional near-infrared spectroscopy for up to 36 months post cochlear implantation (CI).…
Descriptors: Speech Communication, Language Processing, Auditory Perception, Assistive Technology
Elisabeth Bauer; Michael Sailer; Frank Niklas; Samuel Greiff; Sven Sarbu-Rothsching; Jan M. Zottmann; Jan Kiesewetter; Matthias Stadler; Martin R. Fischer; Tina Seidel; Detlef Urhahne; Maximilian Sailer; Frank Fischer – Journal of Computer Assisted Learning, 2025
Background: Artificial intelligence, particularly natural language processing (NLP), enables automating the formative assessment of written task solutions to provide adaptive feedback automatically. A laboratory study found that, compared with static feedback (an expert solution), adaptive feedback automated through artificial neural networks…
Descriptors: Artificial Intelligence, Feedback (Response), Computer Simulation, Natural Language Processing
Leveraging Large Language Models to Generate Course-Specific Semantically Annotated Learning Objects
Dominic Lohr; Marc Berges; Abhishek Chugh; Michael Kohlhase; Dennis Müller – Journal of Computer Assisted Learning, 2025
Background: Over the past few decades, the process and methodology of automatic question generation (AQG) have undergone significant transformations. Recent progress in generative natural language models has opened up new potential in the generation of educational content. Objectives: This paper explores the potential of large language models…
Descriptors: Resource Units, Semantics, Automation, Questioning Techniques
Hao Zhou; Wenge Rong; Jianfei Zhang; Qing Sun; Yuanxin Ouyang; Zhang Xiong – IEEE Transactions on Learning Technologies, 2025
Knowledge tracing (KT) aims to predict students' future performances based on their former exercises and additional information in educational settings. KT has received significant attention since it facilitates personalized experiences in educational situations. Simultaneously, the autoregressive (AR) modeling on the sequence of former exercises…
Descriptors: Learning Experience, Academic Achievement, Data, Artificial Intelligence
Anjee Gorkhali; Asim Shrestha – International Journal of Information and Learning Technology, 2025
Purpose: Educators are raising ethical concerns over the use of ChatGPT in schools. They have implemented various strategies to minimize its use, particularly by labeling ChatGPT-produced work as plagiarism. However, the use of ChatGPT among students is still on the rise. Our study aims to find the behavioral motivation behind students' increased…
Descriptors: Self Concept, Prevention, Student Behavior, Artificial Intelligence
Nur Basak Karatas; Oya Özemir; Jarrett T. Lovelett; Bora Demir; Kemal Erkol; João Veríssimo; Gülcan Erçetin; Michael T. Ullman – Language Teaching Research, 2025
We investigated whether learning and retaining vocabulary in a second language (L2) can be improved by leveraging a combination of memory enhancement techniques. Specifically, we tested whether combining retrieval practice, spacing, and related manipulations in a 'multidomain' pedagogical approach enhances vocabulary acquisition as compared to a…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Accuracy
Jinhee Kim; Seongryeong Yu; Rita Detrick; Na Li – Education and Information Technologies, 2025
The rapid development of generative artificial intelligence (GenAI), including large language models (LLM), has merged to support students in their academic writing process. Keeping pace with the technical and educational landscape requires careful consideration of the opportunities and challenges that GenAI-assisted systems create within…
Descriptors: Student Attitudes, Artificial Intelligence, Technology Uses in Education, Natural Language Processing
Usani Joseph Ofem; Valentine Joseph Owan; Mary Arikpo Iyam; Maryrose Ify Udeh; Pauline Mbua Anake; Sylvia Victor Ovat – Education and Information Technologies, 2025
While previous studies have explored students' use of different AI tools for academic purposes, studies that have specifically investigated students' use of ChatGPT for dishonest academic purposes in Nigeria are lacking. The consequence of this contextual and knowledge gap is a lack of specific understanding regarding students' engagement with…
Descriptors: Student Attitudes, Usability, Artificial Intelligence, Technology Uses in Education
Dabae Lee; Taekwon Son; Sheunghyun Yeo – Journal of Computer Assisted Learning, 2025
Background: Artificial Intelligence (AI) technologies offer unique capabilities for preservice teachers (PSTs) to engage in authentic and real-time interactions using natural language. However, the impact of AI technology on PSTs' responsive teaching skills remains uncertain. Objectives: The primary objective of this study is to examine whether…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Preservice Teachers
Katarína Žáková; Diana Urbano; Ricardo Cruz-Correia; José Luis Guzmán; Jakub Matišák – Education and Information Technologies, 2025
Understanding how students interact with AI bots is a first step towards integrating them into instructional design. In this report, the results of a survey conducted in three European higher education institutions, and in the context of four different areas are presented. Among other things, they reveal for what purposes students use ChatGPT,…
Descriptors: Student Attitudes, Teacher Attitudes, Artificial Intelligence, Natural Language Processing
Previous Page | Next Page »
Pages: 1 | 2