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Melissa Fortner; Iva Katzarska-Miller – Teaching of Psychology, 2025
Introduction: Recent advancements in generative AI (GAI) platforms appear to mark an abrupt shift in higher education. Statement of the Problem: Instructors have a responsibility to teach students to use GAI, which is a promising tool for promoting personalized, student-centered, process-focused learning environments. Literature Review: Drawing on…
Descriptors: Artificial Intelligence, Majors (Students), Computer Software, Student Centered Learning
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Ted K. Mburu; Kangxuan Rong; Campbell J. McColley; Alexandra Werth – Journal of Engineering Education, 2025
Background: This study investigates the use of large language models to create adaptive, contextually relevant survey questions, aiming to enhance data quality in educational research without limiting scalability. Purpose: We provide step-by-step methods to develop a dynamic survey instrument, driven by artificial intelligence (AI), and introduce…
Descriptors: Artificial Intelligence, Computer Software, Technology Integration, Computational Linguistics
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Yu Ji; Mingxuan Zhong; Siyan Lyu; Tingting Li; Shijing Niu; Zehui Zhan – Education and Information Technologies, 2025
The emergence of generative artificial intelligence (GAI) has significantly transformed learning patterns and innovative approaches. Human-machine (generative artificial intelligence) co-creation will become the norm, necessitating that learners possess the requisite AI literacy (AIL) to adapt to this shift. The mechanisms by which individual AIL…
Descriptors: Artificial Intelligence, Digital Literacy, Innovation, Psychological Needs
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Preet Chandan Kaur; Leena Ragha – Education and Information Technologies, 2025
Video summarization is a method of deducing the content of video content for generating a summary in video format. The generated summary should have the significant segments of raw video. Recently, the content of video has been rapidly increasing, thus automatic video summarization is beneficial for individuals who want to keep time and learn more…
Descriptors: Semantics, Video Technology, Audio Equipment, Linguistic Input
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Amy J. Heston; Ling Qian; Tatiana C. Tolson; Madeline M. Heston – Intersection: A Journal at the Intersection of Assessment and Learning, 2025
In an effort to explore the integration of Artificial Intelligence (AI) in higher education, this project focused on the evaluation of perceptions of AI-related assessment strategies between student researchers and professional researchers. With English composition as a focal point, the AI-driven framework consisted of the policy, guidelines, and…
Descriptors: Artificial Intelligence, Technology Uses in Education, Writing (Composition), Writing Evaluation
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Laura Hamilton Brown – Communication Teacher, 2025
Students will analyze article excerpts that demonstrate how the opioid crisis was fueled by a five-sentence "letter to the editor" that was uncritically cited as "evidence" that opioid addiction was rare. Indirectly this activity demonstrates why ChatGPT and other generative artificial intelligence platforms should never be…
Descriptors: Letters (Correspondence), Citations (References), Evidence, Misinformation
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Long Kim; Rungrawee Jitpakdee; Wasin Praditsilp; Sook Fern Yeo – Education and Information Technologies, 2025
Smart classrooms which are facilitated by advanced technology have become a digital learning platform for all university students. Despite their significance in higher education, the number of students adopting the current technology has remained significantly low; thus, universities have to find new solutions to convince their students to quickly…
Descriptors: Artificial Intelligence, Educational Technology, Technology Uses in Education, Higher Education
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Elisabeth Bauer; Constanze Richters; Amadeus J. Pickal; Moritz Klippert; Michael Sailer; Matthias Stadler – British Journal of Educational Technology, 2025
This study explores whether AI-generated adaptive feedback or static feedback is favourable for student interest and performance outcomes in learning statistics in a digital learning environment. Previous studies have favoured adaptive feedback over static feedback for skill acquisition, however, without investigating the outcome of students'…
Descriptors: Artificial Intelligence, Technology Uses in Education, Feedback (Response), Statistics Education
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Anni Silvola; Anu Kajamaa; Joonas Merikko; Hanni Muukkonen – British Journal of Educational Technology, 2025
Despite a proliferation of research on generative artificial intelligence (GenAI) and its applications in higher education (HE), our understanding of the transformative processes where students create productive and ethically grounded uses of GenAI and how AI mediates students' sensemaking is still limited. Based on an empirical investigation of…
Descriptors: Artificial Intelligence, Technology Uses in Education, College Students, Learning Processes
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Yimin Ning; Wenjun Zhang; Dengming Yao; Bowen Fang; Binyan Xu; Tommy Tanu Wijaya – Education and Information Technologies, 2025
The integration of AI in education highlights the significance of Teachers' AI Literacy (TAIL). Existing assessment tools, however, are hindered by incomplete indicators and a lack of practicality for large-scale application, necessitating a more systematic and credible evaluation method. This study is based on a systematic literature review and…
Descriptors: Artificial Intelligence, Rating Scales, Technological Literacy, Factor Analysis
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Yulu Cui; Hai Zhang – Education and Information Technologies, 2025
With the development of artificial intelligence technology, it has become increasingly difficult to distinguish between Artificial Intelligence Generated Content (AIGC) and non-AIGC. Inaccuracies in identifying AIGC in higher education may lead to academic misconduct and risks, and the credibility of AIGC is also subject to certain doubts. Users…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Technology, Identification
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Nurlaela Nurlaela; Andi Muhammad Irfan; Muhammad Haristo Rahman; Kurnia Prima Putra; Amiruddin Mahmud; Wirawan Setialaksana – Education and Information Technologies, 2025
Integrating advanced technologies like Virtual Reality (VR) and Augmented Reality (AR) in educational settings can significantly enhance learning, especially in vocational education, where practical application is crucial. However, understanding the factors influencing student acceptance of these technologies remains challenging. This study…
Descriptors: Career and Technical Education, Technology Uses in Education, Technology Integration, Artificial Intelligence
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J. Weidlich; D. Gaševic; H. Drachsler; P. Kirschner – Journal of Computer Assisted Learning, 2025
Background: As researchers rush to investigate the potential of AI tools like ChatGPT to enhance learning, well-documented pitfalls threaten the validity of this emerging research. Issues of media comparison research, where the confounding of instructional methods and technological affordances is unrecognised, may render effects uninterpretable.…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Benefits, Barriers
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Thoriqi Firdaus; Noura Aulya Damayanti; Rika Nur Hamida; Roukhil Ummu Hani; Najwa Salma Khoirun Nisa – International Online Journal of Primary Education, 2025
Artificial Intelligence (AI) holds significant potential to transform education, particularly in teaching methodologies and task completion. This study aims to identify the factors influencing the perceptions and behaviors of elementary education students in utilizing ChatGPT and Gemini to complete science-related assignments. The research design…
Descriptors: Technology Uses in Education, Science Instruction, Assignments, Preservice Teachers
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Thomas Corbin; Phillip Dawson; Kelli Nicola-Richmond; Helen Partridge – Assessment & Evaluation in Higher Education, 2025
As higher education grapples with ensuring assessment validity in an increasingly AI-populated time, institutions and educators are working to establish appropriate boundaries for AI use. However, little is known about how students and teachers conceptualize and experience these boundaries in practice. This study investigates how students and…
Descriptors: Artificial Intelligence, Technology Uses in Education, College Students, Student Attitudes
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