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Aaron L. Norton – Rehabilitation Research, Policy, and Education, 2025
Background: Artificial intelligence (AI) and generative artificial intelligence (GenAI) technology have rapidly evolved in recent years, posing substantial implications for counselors, counselor educators, supervisors, and researchers. However, research on AI and counseling is in its infancy, and while some counseling organizations have recently…
Descriptors: Artificial Intelligence, Computer Use, Counseling, Rehabilitation Counseling
Inna Artemova – Online Learning, 2025
While existing literature documents the benefits and concerns of Generative Artificial Intelligence (GAI) for learning processes, it largely overlooks fundamental learning theories such as Cognitive Load Theory, Constructivism, Activity Theory, and Bloom's Taxonomy. This study employs a scoping review methodology to identify current research gaps…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Research, Risk
Tammy Jorgensen Smith; Howard Kaplan; Estefania Simon; Larry Tartaglino; Anthony Denham; Jaimie Timmons; Juliana Cortes – Rehabilitation Research, Policy, and Education, 2025
Background: Competitive, integrated employment (CIE) rates for individuals with disabilities have continued to be much lower than their peers without disabilities. Integration of advanced technologies to develop and refine innovative, scalable, and sustainable programs that promote CIE in high-demand, economically self-sustaining fields will lead…
Descriptors: Artificial Intelligence, Computer Simulation, Disabilities, Employment
Shai Farber – Innovative Higher Education, 2025
This pilot study explores the potential role of artificial intelligence (AI) technologies in enhancing the academic manuscript-to-journal matching process, focusing on Large Language Models (LLMs). Through a focused evaluation of LLM-based recommendation systems, the study analyzes their performance across 40 papers from four distinct disciplines:…
Descriptors: Pilot Projects, Decision Making, Artificial Intelligence, Higher Education
Farzad Rezavandzayeri; José María Cancela Carral; Helena Vila Suarez – Journal of Youth Development, 2025
This study examines that does training volume affect the quality of life, emotional intelligence, and performance of shooting athletes with physical disabilities? Ninety participants were randomly assigned to three groups based on weekly shooting durations of 2, 4, and 6 hours, maintaining a 1:1 female-to-male ratio until the total sample size…
Descriptors: Training, Quality of Life, Emotional Intelligence, Performance
Malissa Maria Mahmud; Wali Khan Monib; Atika Qazi; Shiau Foong Wong; Chandra Reka Ramachandiran; Siti Norbaya Azizan – Open Praxis, 2025
Artificial Intelligence (AI) is rapidly transforming education, yet many institutions lack a comprehensive framework to integrate AI effectively. This paper develops an AI Education Competency Framework to guide the integration of AI in educational settings through a systematic literature review. Methodologically, a rigorous systematic literature…
Descriptors: Artificial Intelligence, Technology Uses in Education, Technology Integration, Guidelines
Anupkumar D. Dhanvijay; Amita Kumari; Mohammed Jaffer Pinjar; Anita Kumari; Abhimanyu Ganguly; Ankita Priya; Ayesha Juhi; Pratima Gupta; Himel Mondal – Advances in Physiology Education, 2025
Multiple-choice questions (MCQs) are widely used for assessment in medical education. While human-generated MCQs benefit from pedagogical insight, creating high-quality items is time intensive. With the advent of artificial intelligence (AI), tools like DeepSeek R1 offer potential for automated MCQ generation, though their educational validity…
Descriptors: Multiple Choice Tests, Physiology, Artificial Intelligence, Test Items
Tristan Lim; Swapna Gottipati; Michelle Cheong – International Journal of Educational Technology in Higher Education, 2025
The rise of AI in educational assessments has significantly enhanced efficiency and accuracy. However, it also introduces critical ethical challenges, including bias in grading, data privacy risks, and accountability gaps. These issues can undermine trust in AI-driven assessments and compromise educational fairness, making a structured ethical…
Descriptors: Student Attitudes, Artificial Intelligence, Technology Uses in Education, Ethics
Habiba Al-Mughairi; Preeti Bhaskar – Journal of Research in Innovative Teaching & Learning, 2025
Purpose: ChatGPT, an artificial intelligence (AI)-powered chatbot, has gained substantial attention in the academic world for its potential to transform the education industry. While ChatGPT offers numerous benefits, concerns have also been raised regarding its impact on the quality of education. This study aims to bridge the gap in research by…
Descriptors: Educational Technology, Technology Uses in Education, Technology Integration, Artificial Intelligence
Regan Mozer; Luke Miratrix – Grantee Submission, 2025
For randomized trials that use text as an outcome, traditional approaches for assessing treatment impact require that each document first be manually coded for constructs of interest by trained human raters. This process, the current standard, is both time-consuming and limiting: even the largest human coding efforts are typically constrained to…
Descriptors: Artificial Intelligence, Coding, Efficiency, Statistical Inference
Hotaka Maeda; Yikai Lu – Journal of Educational Measurement, 2025
We fine-tuned and compared several encoder-based Transformer large language models (LLM) to predict differential item functioning (DIF) from the item text. We then applied explainable artificial intelligence (XAI) methods to identify specific words associated with the DIF prediction. The data included 42,180 items designed for English language…
Descriptors: Artificial Intelligence, Prediction, Test Bias, Test Items
German Cuaya-Simbro; Serguei Drago Domínguez Ruíz – International Journal of Assessment Tools in Education, 2025
This study introduces a novel Generative Artificial Intelligence (GAI) platform designed to streamline the peer review process. By analyzing a case study of 10 scientific articles, we demonstrate that GAI effectively evaluates article quality and pinpoints specific areas requiring improvement. Our platform achieves an average similarity of 63.6%…
Descriptors: Peer Evaluation, Artificial Intelligence, Scientific Research, Journal Articles
Kathryn C. Wymer – International Journal for the Scholarship of Teaching and Learning, 2025
Discussions about generative artificial intelligence (AI) seem to predominate current conversations about higher education. It is urgent for those engaged in the Scholarship of Teaching and Learning to evaluate how generative AI could be used appropriately in course development and evaluation, but it is also important for SoTL practitioners to…
Descriptors: Artificial Intelligence, Technology Uses in Education, Higher Education, Scholarship
Omid Noroozi; Golnoush Haddadian; Xingshi Gao; Christian Schunn; Maryam Alqassab; Seyyed Kazem Banihashem – International Journal of Educational Technology in Higher Education, 2025
Generative Artificial Intelligence (GenAI) has sparked a global debate on its potential as a feedback source for students, yet research in this area remains limited. This study explores students' use of GenAI during peer feedback provision. Fifty-four graduate students enrolled in a master's course in the food science domain at a Dutch university…
Descriptors: Artificial Intelligence, Feedback (Response), Peer Evaluation, Graduate Students
Philip M. Newton – Assessment & Evaluation in Higher Education, 2025
There has been considerable speculation about the risk that new generative AI tools like ChatGPT pose to higher education, particularly assessments and cheating. However it is unclear how much risk the UK higher education sector is exposed to. This survey study used a modified list experiment to evaluate that risk. Most students surveyed were…
Descriptors: Foreign Countries, Artificial Intelligence, Cheating, Higher Education

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