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Todd Cherner; Teresa S. Foulger; Margaret Donnelly – TechTrends: Linking Research and Practice to Improve Learning, 2025
The ethics surrounding the development and deployment of generative artificial intelligence (genAI) is an important topic as institutions of higher education adopt the technology for educational purposes. Concurrently, stakeholders from various organizations have reviewed the literature about the ethics of genAI and proposed frameworks about it.…
Descriptors: Artificial Intelligence, Natural Language Processing, Decision Making, Models
Zhao Wanli; Tang Youjun; Ma Xiaomei – SAGE Open, 2025
Deeper learning (DL) is firmly rooted in learning science and computer science. However, a dearth of review studies has probed its trajectory in DL in foreign languages (DLFL). Utilizing SSCI from the Web of Science Core Collection, we employ Citespace and Vosviewer to analyze the scientific knowledge graph of DLFL literature. Our analysis…
Descriptors: Bibliometrics, Second Language Learning, Computer Science, Educational Research
Maria Korochkina; Kathleen Rastle – npj Science of Learning, 2025
Breaking down complex words into smaller meaningful units (e.g., "unhappy = un- + happy"), known as morphemes, is vital for skilled reading as it allows readers to rapidly compute word meanings. There is agreement that children rely on reading experience to acquire morphological knowledge in English; however, the nature of this…
Descriptors: Childrens Literature, Morphemes, Morphology (Languages), Reading Skills
Samah AlKhuzaey; Floriana Grasso; Terry R. Payne; Valentina Tamma – International Journal of Artificial Intelligence in Education, 2024
Designing and constructing pedagogical tests that contain items (i.e. questions) which measure various types of skills for different levels of students equitably is a challenging task. Teachers and item writers alike need to ensure that the quality of assessment materials is consistent, if student evaluations are to be objective and effective.…
Descriptors: Test Items, Test Construction, Difficulty Level, Prediction
Jutta Kray; Linda Sommerfeld; Arielle Borovsky; Katja Häuser – Child Development Perspectives, 2024
Prediction error plays a pivotal role in theories of learning, including theories of language acquisition and use. Researchers have investigated whether and under which conditions children, like adults, use prediction to facilitate language comprehension at different levels of linguistic representation. However, many aspects of the reciprocal…
Descriptors: Prediction, Child Development, Language Acquisition, Error Analysis (Language)
Amal Abdullah Alibrahim – South African Journal of Education, 2024
After ChatGPT was released late in 2022, many arguments about its accuracy and use in education arose. In this article, I seek to provide evidence of the accuracy and validity of ChatGPT's responses to users' queries in education by applying a systematic review methodology to analyse publications in specific databases following PRISMA guidelines…
Descriptors: Artificial Intelligence, Technology Uses in Education, Reliability, Natural Language Processing
Ingrid Del Valle García Carreño – European Educational Researcher, 2025
The main objective of this article is to search into the exploration of the ChatGPT trend in the field of Social Sciences, focusing on its trend and its widespread global application in the digital era. It is noted that ChatGPT is an artificial intelligence system that utilizes the GPT (Generative Pre-trained Transformer) language model developed…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Social Sciences
Putnikovic, Marko; Jovanovic, Jelena – IEEE Transactions on Learning Technologies, 2023
Automatic grading of short answers is an important task in computer-assisted assessment (CAA). Recently, embeddings, as semantic-rich textual representations, have been increasingly used to represent short answers and predict the grade. Despite the recent trend of applying embeddings in automatic short answer grading (ASAG), there are no…
Descriptors: Automation, Computer Assisted Testing, Grading, Natural Language Processing
Caroline Larson; Hannah R. Thomas; Jason Crutcher; Michael C. Stevens; Inge-Marie Eigsti – Review Journal of Autism and Developmental Disorders, 2025
Autism Spectrum Disorder (ASD) is a heterogeneous condition associated with differences in functional neural connectivity relative to neurotypical (NT) peers. Language-based functional connectivity represents an ideal context in which to characterize connectivity because language is heterogeneous and linked to core features in ASD, and NT language…
Descriptors: Autism Spectrum Disorders, Brain, Brain Hemisphere Functions, Language Processing
Patrícia Takaki; Moisés Lima Dutra – Education and Information Technologies, 2024
Much of the data produced and consumed by students, teachers, and educational managers is in textual format. Text Mining (TM) and Natural Language Processing (NLP) have been applied in the educational context in different ways. Ideally, such applications combine computational, linguistic, pedagogical, and psychological aspects. This article aims…
Descriptors: Literature Reviews, Higher Education, Distance Education, Content Analysis
Enhanced Sensitivity to Pitch Perception and Its Possible Relation to Language Acquisition in Autism
Megumi Hisaizumi; Digby Tantam – Autism & Developmental Language Impairments, 2024
Background and aims: Fascinations for or aversions to particular sounds are a familiar feature of autism, as is an ability to reproduce another person's utterances, precisely copying the other person's prosody as well as their words. Such observations seem to indicate not only that autistic people can pay close attention to what they hear, but…
Descriptors: Autism Spectrum Disorders, Phonology, Language Processing, Auditory Perception
Sello Prince Sekwatlakwatla; Vusumuzi Malele – International Journal of Education and Development using Information and Communication Technology, 2023
The emerging generative artificial intelligence (AI) chatbots, such as Chat Generative Pre-Trained Transformer (ChatGPT), have recently taken different disciplines by surprise. Very few scholarly papers show the collaborative effort by researchers on the impact of generative AI in higher education (HE) and its implication on HE disciplines and…
Descriptors: Artificial Intelligence, Natural Language Processing, Higher Education, Technology Uses in Education
Silvia García-Méndez; Francisco de Arriba-Pérez; María del Carmen Somoza-López – Science & Education, 2025
Transformer architectures contribute to managing long-term dependencies for natural language processing, representing one of the most recent changes in the field. These architectures are the basis of the innovative, cutting-edge large language models (LLMs) that have produced a huge buzz in several fields and industrial sectors, among the ones…
Descriptors: Natural Language Processing, Artificial Intelligence, Literature Reviews, Technology Uses in Education
Schwen Blackett, Deena; Harnish, Stacy M. – Journal of Speech, Language, and Hearing Research, 2022
Purpose: Emotional stimuli have been shown to influence language processing (both language comprehension and production) in people with aphasia (PWA); however, this finding is not universally reported. Effects of emotional stimuli on language performance in PWA could have clinical and theoretical implications, yet the sparsity of studies and…
Descriptors: Aphasia, Emotional Response, Stimuli, Language Processing
Lena Schmidt; Saleh Mohamed; Nick Meader; Jaume Bacardit; Dawn Craig – Research Synthesis Methods, 2024
The amount of grey literature and 'softer' intelligence from social media or websites is vast. Given the long lead-times of producing high-quality peer-reviewed health information, this is causing a demand for new ways to provide prompt input for secondary research. To our knowledge, this is the first review of automated data extraction methods or…
Descriptors: Automation, Natural Language Processing, Literature Reviews, Data Collection