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Dan Zhao – Education and Information Technologies, 2025
Artificial intelligence is revolutionizing the education landscape and has been widely applied to language teaching and learning. This study investigates the transformative potential of AI-driven Natural Language Processing (NLP) tools in enhancing writing proficiency, focusing on language precision, content summarization, and creative writing…
Descriptors: Artificial Intelligence, Writing Skills, English (Second Language), Second Language Instruction
Muhammad Farrukh Shahzad; Shuo Xu; Hira Zahid – Education and Information Technologies, 2025
Artificial Intelligence (AI) technologies have rapidly transformed the education sector and affect student learning performance, particularly in China, a burgeoning educational landscape. The development of generative artificial intelligence (AI) based technologies, such as chatbots and large language models (LLMs) like ChatGPT, has completely…
Descriptors: Artificial Intelligence, Technology Uses in Education, Academic Achievement, Self Efficacy
Ray Buss; Amy Markos; Josephine Marsh – Impacting Education: Journal on Transforming Professional Practice, 2025
Generative AI has emerged as a tool to assist doctoral students as they conduct academic research and writing. In this study, we explored two ways AI has been used by students in our EdD program--informally and independently and in a more formalized, guided manner. First, we found students have been engaged in self-directed, informal, independent…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Doctoral Students
Mubina Khan Schroeder; Joanna Alcruz – Impacting Education: Journal on Transforming Professional Practice, 2025
The landscape of generative AI in Education Doctorate (EdD) programs is multifaceted and rapidly evolving, demonstrating a significant impact on educational methodologies and student engagement. In the Molloy University EdD program, AI is leveraged extensively for a range of purposes, from assessment tools like Perusall to advanced platforms like…
Descriptors: Artificial Intelligence, Doctoral Dissertations, Doctoral Students, Education Majors
Nisar Ahmed Dahri; Noraffandy Yahaya; Waleed Mugahed Al-Rahmi – Education and Information Technologies, 2025
Enhancing student academic success and career readiness is important in the rapidly evolving educational field. This study investigates the influence of ChatGPT, an AI tool, on these outcomes using the Stimulus-Organism-Response (SOR) theory and constructs from the Technology Acceptance Model (TAM). The aim is to explore how ChatGPT impacts…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Career Readiness
André Markus; Maximilian Baumann; Jan Pfister; Andreas Hotho; Astrid Carolus; Carolin Wienrich – Discover Education, 2025
Intelligent Voice Assistants (IVAs) have become integral to many users' daily lives, using advanced algorithms to automate various tasks. Nevertheless, many users do not understand the underlying algorithms and how they work, posing potential risks to the competent and self-determined use of IVAs. This work develops three online training modules…
Descriptors: Algorithms, Digital Literacy, Training, Artificial Intelligence
Chang, Tammy; DeJonckheere, Melissa; Vydiswaran, V. G. Vinod; Li, Jiazhao; Buis, Lorraine R.; Guetterman, Timothy C. – Journal of Mixed Methods Research, 2021
Situations of catastrophic social change, such as COVID-19, raise complex, interdisciplinary research questions that intersect health, education, economics, psychology, and social behavior and require mixed methods research. The pandemic has been a quickly evolving phenomenon, which pressures the time necessary to perform mixed methods research.…
Descriptors: Mixed Methods Research, Natural Language Processing, Data, Change
Zhu, Mengyan; Zhuang, Xiangling; Ma, Guojie – Reading and Writing: An Interdisciplinary Journal, 2021
In Chinese reading, the possibility and mechanism of semantic parafoveal processing has been debated for a long time. To advance the topic, "semantic preview benefit" in Chinese reading was reexamined, with a specific focus on how it is affected by the semantic relatedness between preview and target words at the two-character word level.…
Descriptors: Chinese, Reading Processes, Semantics, Eye Movements
Kate Powell – Montessori Life: A Publication of the American Montessori Society, 2024
In a span of about three days in the spring of 2023, the author's Instagram feed became inundated with mentions of artificial intelligence (AI), including Chat GPT, text-to-image models, and much more. She would turn on the radio and hear about the controversy surrounding AI, or look at her cousin's social media posts about the injustices of her…
Descriptors: Artificial Intelligence, Teaching Methods, Elementary School Teachers, Montessori Schools
Stefan E. Huber; Kristian Kiili; Steve Nebel; Richard M. Ryan; Michael Sailer; Manuel Ninaus – Educational Psychology Review, 2024
This perspective piece explores the transformative potential and associated challenges of large language models (LLMs) in education and how those challenges might be addressed utilizing playful and game-based learning. While providing many opportunities, the stochastic elements incorporated in how present LLMs process text, requires domain…
Descriptors: Artificial Intelligence, Language Processing, Models, Play
Elizabeth Roepke – Perspectives of the ASHA Special Interest Groups, 2024
Purpose: Phonological processing skills, or using phoneme knowledge to process language, in preschool- and kindergarten-age children are an important indicator of children's future reading abilities. However, assessing phonological processing skills can be difficult in children with speech sound disorders because scoring often requires that…
Descriptors: Phonological Awareness, Speech Impairments, Preschool Children, Kindergarten
Behzad Mirzababaei; Viktoria Pammer-Schindler – IEEE Transactions on Learning Technologies, 2024
In this article, we investigate a systematic workflow that supports the learning engineering process of formulating the starting question for a conversational module based on existing learning materials, specifying the input that transformer-based language models need to function as classifiers, and specifying the adaptive dialogue structure,…
Descriptors: Learning Processes, Electronic Learning, Artificial Intelligence, Natural Language Processing
Robin Elizabeth Miller – portal: Libraries and the Academy, 2024
In the year since ChatGPT was released by OpenAI, librarians, instructors, and higher education administrators have grappled with generative artificial intelligence (AI) and its implications for teaching, learning, research, and writing. Drawn from informal conversations, professional observations, discussion groups, and professional development…
Descriptors: Higher Education, Artificial Intelligence, Man Machine Systems, Natural Language Processing
Amanda Saksida; Alan Langus – Child Development, 2024
The account that word learning starts in earnest during the second year of life, when infants have mastered the disambiguation skills, has recently been challenged by evidence that infants during the first year already know many common words. The preliminary ability to rapidly map and disambiguate linguistic labels was tested in Italian-speaking…
Descriptors: Naming, Infants, Cognitive Mapping, Vocabulary Development
Semere Kiros Bitew; Amir Hadifar; Lucas Sterckx; Johannes Deleu; Chris Develder; Thomas Demeester – IEEE Transactions on Learning Technologies, 2024
Multiple-choice questions (MCQs) are widely used in digital learning systems, as they allow for automating the assessment process. However, owing to the increased digital literacy of students and the advent of social media platforms, MCQ tests are widely shared online, and teachers are continuously challenged to create new questions, which is an…
Descriptors: Multiple Choice Tests, Computer Assisted Testing, Test Construction, Test Items