Publication Date
In 2025 | 33 |
Since 2024 | 657 |
Since 2021 (last 5 years) | 2023 |
Since 2016 (last 10 years) | 3629 |
Since 2006 (last 20 years) | 7202 |
Descriptor
Source
Author
Publication Type
Education Level
Audience
Practitioners | 182 |
Teachers | 143 |
Researchers | 129 |
Administrators | 13 |
Parents | 12 |
Students | 8 |
Counselors | 4 |
Policymakers | 4 |
Community | 1 |
Support Staff | 1 |
Location
China | 181 |
Germany | 121 |
Australia | 112 |
Canada | 109 |
United Kingdom | 104 |
Netherlands | 98 |
Japan | 93 |
Spain | 89 |
France | 61 |
Hong Kong | 57 |
Iran | 57 |
More ▼ |
Laws, Policies, & Programs
No Child Left Behind Act 2001 | 5 |
Education Consolidation… | 1 |
Head Start | 1 |
Individuals with Disabilities… | 1 |
Assessments and Surveys
What Works Clearinghouse Rating
Meets WWC Standards without Reservations | 1 |
Meets WWC Standards with or without Reservations | 2 |
Does not meet standards | 3 |
Nezihe Korkmaz Guler; Zeynep Gul Dertli; Elif Boran; Bahadir Yildiz – Pedagogical Research, 2024
The aim of the research is to investigate the academic achievement of ChatGPT, an artificial intelligence based chatbot, in a national mathematics exam. For this purpose, 3.5 and 4 versions of ChatGPT were asked mathematics questions in a national exam. The method of the research is a case study. In the research, 3.5 and 4 versions of ChatGPT were…
Descriptors: Mathematics Education, Artificial Intelligence, Man Machine Systems, Natural Language Processing
Naima Debbar – International Journal of Contemporary Educational Research, 2024
Intelligent systems of essay grading constitute important tools for educational technologies. They can significantly replace the manual scoring efforts and provide instructional feedback as well. These systems typically include two main parts: a feature extractor and an automatic grading model. The latter is generally based on computational and…
Descriptors: Test Scoring Machines, Computer Uses in Education, Artificial Intelligence, Essay Tests
Tolulope Famaye; Cinamon Sunrise Bailey; Ibrahim Adisa; Golnaz Arastoopour Irgens – International Journal of Technology in Education, 2024
The emergence of ChatGPT, an AI-powered language model, has sparked numerous debates and discussions. In educational research, scholars have raised significant questions regarding the potential, limitations, and ethical concerns around the use of this technology. While research on the application and implications of ChatGPT in academic settings…
Descriptors: Artificial Intelligence, High School Students, Technology Uses in Education, Student Attitudes
Rania Abdelghani; Yen-Hsiang Wang; Xingdi Yuan; Tong Wang; Pauline Lucas; Hélène Sauzéon; Pierre-Yves Oudeyer – International Journal of Artificial Intelligence in Education, 2024
The ability of children to ask curiosity-driven questions is an important skill that helps improve their learning. For this reason, previous research has explored designing specific exercises to train this skill. Several of these studies relied on providing semantic and linguistic cues to train them to ask more of such questions (also called…
Descriptors: Artificial Intelligence, Technology Uses in Education, Natural Language Processing, Inquiry
Priya C. Kumar; Kelley Cotter; Laura Y. Cabrera – Reading Research Quarterly, 2024
Questions and concerns about artificial intelligence (AI) technologies in education reached a fever pitch with the arrival of publicly accessible, user-facing generative AI systems, especially ChatGPT. Many of these issues will require regulation and collective action to address. But when it comes to generative AI and literacy, we argue that…
Descriptors: Artificial Intelligence, Technology Uses in Education, Influence of Technology, Literacy
Tiffany L Hutchins; Sophie E. Knox; E. Cheryl Fletcher – Autism & Developmental Language Impairments, 2024
Background and Aim: Recently, there has been a lot of interest surrounding the term gestalt language processor (GLP) which is associated with Natural Language Acquisition (NLA): a protocol intended to support the language development of autistic people. In NLA, delayed echolalia is presumed raw source material that GLPs use to acquire language in…
Descriptors: Language Acquisition, Language Processing, Autism Spectrum Disorders, Repetition
I. R. Jackson; E. Perugia; M. A. Stone; G. H. Saunders – Cognitive Research: Principles and Implications, 2024
The use of face coverings can make communication more difficult by removing access to visual cues as well as affecting the physical transmission of speech sounds. This study aimed to assess the independent and combined contributions of visual and auditory cues to impaired communication when using face coverings. In an online task, 150 participants…
Descriptors: Verbal Communication, Cues, Auditory Perception, Visual Perception
Sang-Gu Kang – Journal of Pan-Pacific Association of Applied Linguistics, 2024
This paper reports on a young Korean boy's target-like and non-target-like uses of the Korean negation marker "ani" to express various types of negation in Korean, observed approximately between the ages of 2;2 and 2;5. Besides the target-like usage of "ani" as a sentential adverb for a 'no' response, he used "ani" in…
Descriptors: Korean, Morphemes, Toddlers, Language Acquisition
Claudio-Rafael Vasquez-Martinez; Francisco Flores-Cuevas; Felipe-Anastacio Gonzalez-Gonzalez; Luz-Maria Zuniga-Medina; Graciela-Esperanza Giron-Villacis; Irma-Carolina Gonzalez-Sanchez; Joaquin Torres-Mata – Bulgarian Comparative Education Society, 2024
Language is the basis of human communication and is the most important key to complete mental development and thinking. Therefore, children must learn to communicate using appropriate language. For this to happen, the development of language in the child must be understood as a biological process, complete with internal laws and with marked stages…
Descriptors: Infants, Morphology (Languages), Syntax, Phonology
Erin Pacquetet – ProQuest LLC, 2024
This dissertation explores the relationship between language production processes and recorded typing behaviors among native speakers of English writing in their native language. Typing is quite prevalent in modern societies, as its use is becoming increasingly required in professional and personal settings but it remains largely understudied in…
Descriptors: English, Native Language, Writing (Composition), Word Processing
Stefan Ruseti; Ionut Paraschiv; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2024
Automated Essay Scoring (AES) is a well-studied problem in Natural Language Processing applied in education. Solutions vary from handcrafted linguistic features to large Transformer-based models, implying a significant effort in feature extraction and model implementation. We introduce a novel Automated Machine Learning (AutoML) pipeline…
Descriptors: Computer Assisted Testing, Scoring, Automation, Essays
Stefan Ruseti; Ionut Paraschiv; Mihai Dascalu; Danielle S. McNamara – International Journal of Artificial Intelligence in Education, 2024
Automated Essay Scoring (AES) is a well-studied problem in Natural Language Processing applied in education. Solutions vary from handcrafted linguistic features to large Transformer-based models, implying a significant effort in feature extraction and model implementation. We introduce a novel Automated Machine Learning (AutoML) pipeline…
Descriptors: Computer Assisted Testing, Scoring, Automation, Essays
Sang-Gu Kang – Journal of Pan-Pacific Association of Applied Linguistics, 2024
This paper reports on a young Korean boy's target-like and non-target-like uses of the Korean negation marker "ani" to express various types of negation in Korean, observed approximately between the ages of 2;2 and 2;5. Besides the target-like usage of "ani" as a sentential adverb for a 'no' response, he used "ani" in…
Descriptors: Korean, Morphemes, Toddlers, Language Acquisition
Farrow, Robert – Learning, Media and Technology, 2023
Explicable AI in education (XAIED) has been proposed as a way to improve trust and ethical practice in algorithmic education. Based on a critical review of the literature, this paper argues that XAI should be understood as part of a wider socio-technical turn in AI. The socio-technical perspective indicates that explicability is a relative term.…
Descriptors: Artificial Intelligence, Algorithms, Computer Uses in Education, Language Usage
Cychosz, Margaret; Mahr, Tristan; Munson, Benjamin; Newman, Rochelle; Edwards, Jan R. – Child Development, 2023
To learn language, children must map variable input to categories such as phones and words. How do children process variation and distinguish between variable pronunciations ("shoup" for "soup") versus new words? The unique sensory experience of children with cochlear implants, who learn speech through their device's degraded…
Descriptors: Preschool Children, Child Language, Pronunciation, Assistive Technology