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R. Thapa; A. Garikipati; M. Ciobanu; N.P. Singh; E. Browning; J. DeCurzio; G. Barnes; F.A. Dinenno; Q. Mao; R. Das – Journal of Autism and Developmental Disorders, 2024
Purpose: Disorders on the autism spectrum have characteristics that can manifest as difficulties with communication, executive functioning, daily living, and more. These challenges can be mitigated with early identification. However, diagnostic criteria has changed from DSM-IV to DSM-5, which can make diagnosing a disorder on the autism spectrum…
Descriptors: Autism Spectrum Disorders, Symptoms (Individual Disorders), Clinical Diagnosis, Artificial Intelligence
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Giulio F. Marchena Sekli; Amy Godo; José Carlos Véliz – Journal of Information Technology Education: Research, 2024
Aim/Purpose: This paper aims to address the gap in comprehensive, real-world applications of Generative Artificial Intelligence (GenAI) in education, particularly in higher education settings. Despite the evident potential of GenAI in transforming educational practices, there is a lack of consolidated knowledge about its practical effectiveness…
Descriptors: Artificial Intelligence, Technology Uses in Education, Higher Education, Educational Research
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Xiang Feng; Keyi Yuan; Xiu Guan; Longhui Qiu – Interactive Learning Environments, 2024
Datasets are critical for emotion analysis in the machine learning field. This study aims to explore emotion analysis datasets and related benchmarks in online learning, since, currently, there are very few studies that explore the same. We have scientifically labeled the topic and nine-category emotion of 4715 comment texts in online learning…
Descriptors: MOOCs, Psychological Patterns, Artificial Intelligence, Prediction
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Shang Shanshan; Geng Sen – Journal of Computer Assisted Learning, 2024
Background: Artificial intelligence-generated content (AIGC) has stepped into the spotlight with the emergence of ChatGPT, making effective use of AIGC for education a hot topic. Objectives: This study seeks to explore the effectiveness of integrating AIGC into programming learning through debugging. First, the study presents three levels of AIGC…
Descriptors: Artificial Intelligence, Educational Technology, Technology Integration, Programming
Liunian Li – ProQuest LLC, 2024
To build an Artificial Intelligence system that can assist us in daily lives, the ability to understand the world around us through visual input is essential. Prior studies train visual perception models by defining concept vocabularies and annotate data against the fixed vocabulary. It is hard to define a comprehensive set of everything, and thus…
Descriptors: Artificial Intelligence, Visual Stimuli, Visual Perception, Models
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Jinsook Lee; Yann Hicke; Renzhe Yu; Christopher Brooks; René F. Kizilcec – British Journal of Educational Technology, 2024
Large language models (LLMs) are increasingly adopted in educational contexts to provide personalized support to students and teachers. The unprecedented capacity of LLM-based applications to understand and generate natural language can potentially improve instructional effectiveness and learning outcomes, but the integration of LLMs in education…
Descriptors: Artificial Intelligence, Technology Uses in Education, Equal Education, Algorithms
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Kalervo N. Gulson; Sam Sellar – Journal of Education Policy, 2024
The growing use of artificial intelligence in education extends and intensifies technologies of governing, including datafication, performativity and accountability. In this article, we outline how the use of AI and data science has the disruptive potential to create new norms in education policy and governance. We report on an ethnographic…
Descriptors: Artificial Intelligence, Educational Policy, Governance, Evidence
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Karlis Kanders; Louis Stupple-Harris; Laurie Smith; Jenny Louise Gibson – Infant and Child Development, 2024
Generative artificial intelligence (GAI) is rapidly becoming ubiquitous in many contexts. There is limited scholarship, however, in the fields of Developmental Psychology and Early Childhood Education exploring the implications of generative AI for babies and young children. In this Perspectives piece, we discuss potential use cases,…
Descriptors: Artificial Intelligence, Early Childhood Education, Child Development, Infants
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Hao Tran; Annita Stell – Australian Review of Applied Linguistics, 2024
Generative Artificial Intelligence (GenAI) has been offering unprecedented opportunities for language education. However, its capacity to embrace linguistic diversity, particularly for learners of dialect-rich languages like Vietnamese and Mandarin, remains underexamined. Without careful consideration, GenAI risks reinforcing language hegemonies,…
Descriptors: Artificial Intelligence, Land Settlement, Vietnamese, Dialects
Emmanuel Dumbuya – Online Submission, 2025
Artificial Intelligence (AI) is revolutionizing industries, yet its integration into education remains underutilized. This paper advocates for embedding AI tools in curriculum design to personalize learning experiences, address diverse student needs, and equip learners with future-ready skills. By leveraging AI's capabilities, educators can create…
Descriptors: Artificial Intelligence, Curriculum Design, Individualized Instruction, Technology Uses in Education
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Mary Kalantzis; Bill Cope – Reading Research Quarterly, 2025
The latest mutation of Artificial Intelligence, Generative AI, is more than anything a technology of writing. It is a machine that can write. In a world-historical frame, the significance of this cannot be understated. This is a technology in which the unnatural language of code tangles with the natural language of everyday life. Its form of…
Descriptors: Artificial Intelligence, Natural Language Processing, Literacy Education, Technology Uses in Education
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Gulnara Z. Karimova; Yevgeniya D. Kim; Amir Shirkhanbeik – Education and Information Technologies, 2025
This exploratory study investigates the convergence of marketing communications and AI-powered technology in higher education, adopting a perspective on student interactions with generative AI tools. Through a comprehensive content analysis of learners' responses, we employed a blend of manual scrutiny, Python-generated Word Cloud, and Latent…
Descriptors: Artificial Intelligence, Marketing, Student Attitudes, Higher Education
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Jeffrey A. Greene; Helen Crompton – TechTrends: Linking Research and Practice to Improve Learning, 2025
The increasing ubiquity of digital technologies in the twenty-first century has led to calls for education reform focused on digital literacy, but what exactly does this term mean? The concept of digital literacy has evolved much since its evolution from media and new literacies scholarship, resulting in a myriad of definitions. Previous attempts…
Descriptors: Digital Literacy, Definitions, Educational Policy, Instructional Design
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Ercikan, Kadriye; McCaffrey, Daniel F. – Journal of Educational Measurement, 2022
Artificial-intelligence-based automated scoring is often an afterthought and is considered after assessments have been developed, resulting in nonoptimal possibility of implementing automated scoring solutions. In this article, we provide a review of Artificial intelligence (AI)-based methodologies for scoring in educational assessments. We then…
Descriptors: Artificial Intelligence, Automation, Scores, Educational Assessment
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Monsalve-Pulido, Julian; Aguilar, Jose; Montoya, Edwin – Education and Information Technologies, 2023
The adaptation of traditional systems to service-oriented architectures is very frequent, due to the increase in technologies for this type of architecture. This has led to the construction of frameworks or methodologies for adapting computational projects to service-oriented architecture (SOA) technology. In this work, a framework for adaptation…
Descriptors: Artificial Intelligence, Information Technology, Design, Governance
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