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Abdelmadjid Benmachiche; Abdelhadi Sahia; Soundes Oumaima Boufaida; Khadija Rais; Makhlouf Derdour; Faiz Maazouzi – Education and Information Technologies, 2025
In the context of massive open online courses (MOOCs), searching and retrieving information can be challenging because there is a huge amount of unstructured content, which creates a problem and makes it difficult for users to quickly find relevant lessons or resources. As a result, learners and teachers face significant barriers to accessing the…
Descriptors: MOOCs, Natural Language Processing, Artificial Intelligence, Search Engines
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David Troy – Community College Enterprise, 2025
This paper argues that generative AI has become ubiquitous in academia, making irrelevant the debates about whether or not to allow it. Instead, the author advocates for transparency and accountability frameworks that acknowledge AI's presence while preserving academic integrity. The paper examines the challenges educators face: unreliable…
Descriptors: Artificial Intelligence, Integrity, Technology Uses in Education, Accountability
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Mytsyk Hanna; Suchikova Yana – International Journal of Language & Communication Disorders, 2025
Background: Integrating large language models (LLMs), such as ChatGPT, into speech-language pathology (SLP) presents promising opportunities and notable challenges. While these tools can support diagnostics, streamline documentation and assist in therapy planning, they also raise concerns related to misinformation, cultural insensitivity,…
Descriptors: Artificial Intelligence, Speech Language Pathology, Natural Language Processing, Technology Integration
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Eric Rudolph; Philipp Steigerwald; Jens Albrecht – International Educational Data Mining Society, 2025
This study investigates the capabilities of Large Language Models to simulate counselling clients in educational role-plays in comparison to human role-players. Initially, we recorded role-playing sessions, where novice counsellors interacted with human peers acting as clients, followed by role-plays between humans and clients simulated by…
Descriptors: Artificial Intelligence, Technology Uses in Education, Counselor Training, Role Playing
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Ellie Ingle; Andrew Williams – International Journal for Students as Partners, 2025
This case study reports on a co-creation initiative that explored the use of generative artificial intelligence (AI) technologies in the context of higher education assessments. The AI Co-Creators project aimed to promote dialogue between students and staff on the impact of AI with the objective of using AI tools more effectively. The case study…
Descriptors: Teacher Student Relationship, Test Construction, Artificial Intelligence, Man Machine Systems
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Berrin Cefa; Felicitas Macgilchrist; Hebatullah ElGamal; John Y. H. Bai; Olaf Zawacki-Richter; Frank S. Loglo – Open Praxis, 2025
Immediately after its public launch in November 2022, ChatGPT quickly gained widespread attention across various research fields, including education. The excitement surrounding ChatGPT is not an isolated event as education experienced other innovations that heralded the novelty as a potential game-changer in learner support and teaching. Open,…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Technology Uses in Education
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Lauren S. Baron; Anna M. Ehrhorn; Peter Shlanta; Jane Ashby; Bethany A. Bell; Suzanne M. Adlof – Reading and Writing: An Interdisciplinary Journal, 2025
Phonological processing is an important contributor to decoding and spelling difficulties, but it does not fully explain word reading outcomes for all children. As orthographic knowledge is acquired, it influences phonological processing in typical readers. In the present study, we examined whether orthography affects phonological processing…
Descriptors: Orthographic Symbols, Phonology, Language Processing, Reading Difficulties
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Qinghao Guan; Yangxi Han – Innovations in Education and Teaching International, 2025
As generative AI (GenAI) continues to permeate academia, distinguishing between student-authored essays and those by Large Language Models (LLMs) becomes crucial for maintaining academic integrity. This study conducted a survey on the ethical awareness of using generative AI tools among a group of STEM students (n=156). Also, we empirically…
Descriptors: Foreign Countries, College Students, Artificial Intelligence, Intelligent Tutoring Systems
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Kirkwood Adams; Maria G. Baker – Thresholds in Education, 2025
In response to (1) studies finding that essay feedback generated by ChatGPT might be useful for student writers and (2) studies observing ChatGPT's tendency to adhere to narrow genre definitions when producing writing, our study seeks to examine whether ChatGPT can provide useful feedback in a first-year writing learning environment that targets a…
Descriptors: Freshman Composition, Artificial Intelligence, Man Machine Systems, Natural Language Processing
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Rosa María Jiménez Catalán, Editor – Educational Linguistics, 2025
This book delves into psycholinguistic and cognitive aspects of lexical activation, availability, and production in English or Spanish as additional languages in classroom settings. Instead of focusing sociologically and pedagogically on lexical availability, this collective work adopts a cognitive approach. Ten studies, conducted by experienced…
Descriptors: English (Second Language), Spanish, Second Language Learning, Vocabulary
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Yu Zhai; Yajing Xing; Jianlong Zhao; XiangYu He; Kexin Jiang; Tengfei Zhang; Chunming Lu – Journal of Speech, Language, and Hearing Research, 2025
Purpose: Children with congenital hearing loss (HL) have auditory impairments that may place them at increased risk for delays or variability in language development. However, obtaining reliable brain markers for early classification of young children with HL versus those with normal hearing (NH), as well as for precise assessment of HL children's…
Descriptors: Young Children, Hard of Hearing, Congenital Impairments, Mothers
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Wesley Morris; Langdon Holmes; Joon Suh Choi; Scott Crossley – International Journal of Artificial Intelligence in Education, 2025
Recent developments in the field of artificial intelligence allow for improved performance in the automated assessment of extended response items in mathematics, potentially allowing for the scoring of these items cheaply and at scale. This study details the grand prize-winning approach to developing large language models (LLMs) to automatically…
Descriptors: Automation, Computer Assisted Testing, Mathematics Tests, Scoring
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Alex Goslen; Yeo Jin Kim; Jonathan Rowe; James Lester – International Journal of Artificial Intelligence in Education, 2025
The development of large language models offers new possibilities for enhancing adaptive scaffolding of student learning in game-based learning environments. In this work, we present a novel framework for automatic plan generation that utilizes text-based representations of students' actions within a game-based learning environment, Crystal…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Game Based Learning
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Darius Hennekeuser; Daryoush Daniel Vaziri; David Golchinfar; Dirk Schreiber; Gunnar Stevens – International Journal of Artificial Intelligence in Education, 2025
Large Language Models (LLMs) are rapidly gaining attention across the open-source and commercial fields, bolstered by their constantly growing capabilities. While such models have a vast array of applications, their integration into higher education--as supportive tools for lecturers--has been largely unexplored. Exploring this area entails…
Descriptors: Lecture Method, College Instruction, Higher Education, College Faculty
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Smitha S. Kumar; Michael A. Lones; Manuel Maarek; Hind Zantout – ACM Transactions on Computing Education, 2025
Programming demands a variety of cognitive skills, and mastering these competencies is essential for success in computer science education. The importance of formative feedback is well acknowledged in programming education, and thus, a diverse range of techniques has been proposed to generate and enhance formative feedback for programming…
Descriptors: Automation, Computer Science Education, Programming, Feedback (Response)
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