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Brian Clements; Tamirat T. Abegaz; Bryson Payne – Information Systems Education Journal, 2025
The rise of artificial intelligence (AI) has made life and work easier; however, AI has also made it almost impossible to determine whether the information we consume is legitimate, AI-generated, or AI-manipulated. This paper examines how the use of artificial intelligence, specifically GPT-4, Gemini Advanced, and Claude Opus, can aid a user in…
Descriptors: Artificial Intelligence, Perception, Man Machine Systems, Natural Language Processing
Victoria Abramenka-Lachheb; Ahmed Lachheb; Gamze Ozogul – British Journal of Educational Technology, 2025
Philosophical stances and design frameworks, such as value-sensitive design, manifest in design praxis through enacting specific design approaches and employing a variety of methods by the designers. Although it could overlap with other frameworks and approaches in the Instructional Design and Technology (IDT) field, value-sensitive design remains…
Descriptors: Instructional Design, Praxis, Values, Online Courses
Dariusz Witko; Yair Levy; Catherine Neubauer; Gregory Simco; Laurie P. Dringus; Melissa Carlton – Journal of Cybersecurity Education, Research and Practice, 2025
The increasing volume of cyber threats, combined with a critical shortage of skilled professionals and rising burnout among practitioners, highlights the urgent need for innovative solutions in cybersecurity operations. Generative Artificial Intelligence (GenAI) offers promising potential to augment human analysts in cybersecurity, but its…
Descriptors: Computer Security, Competence, Artificial Intelligence, Expertise
Jonathon Love; Quentin F. Gronau; Gemma Palmer; Ami Eidels; Scott D. Brown – Cognitive Research: Principles and Implications, 2024
With the growing role of artificial intelligence (AI) in our lives, attention is increasingly turning to the way that humans and AI work together. A key aspect of human-AI collaboration is how people integrate judgements or recommendations from machine agents, when they differ from their own judgements. We investigated trust in human-machine…
Descriptors: Artificial Intelligence, Man Machine Systems, Trust (Psychology), Decision Making
Lord J. Hyeamang; Tejas C. Sekhar; Emily Rush; Amy C. Beresheim; Colleen M. Cheverko; William S. Brooks; Abbey C. M. Breckling; M. Nazmul Karim; Christopher Ferrigno; Adam B. Wilson – Anatomical Sciences Education, 2025
Evidence suggests custom chatbots are superior to commercial generative artificial intelligence (GenAI) systems for text-based anatomy content inquiries. This study evaluates ChatGPT-4o's and Claude 3.5 Sonnet's capabilities to interpret unlabeled anatomical images. Secondarily, ChatGPT o1-preview was evaluated as an AI rater to grade AI-generated…
Descriptors: Artificial Intelligence, Anatomy, Identification, Man Machine Systems
Florent Vinchon; Todd Lubart; Sabrina Bartolotta; Valentin Gironnay; Marion Botella; Samira Bourgeois-Bougrine; Jean-Marie Burkhardt; Nathalie Bonnardel; Giovanni Emanuele Corazza; Vlad Glaveanu; Michael Hanchett Hanson; Zorana Ivcevic; Maciej Karwowski; James C. Kaufman; Takeshi Okada; Roni Reiter-Palmon; Andrea Gaggioli – Journal of Creative Behavior, 2023
With the advent of artificial intelligence (AI), the field of creativity faces new opportunities and challenges. This manifesto explores several scenarios of human--machine collaboration on creative tasks and proposes "fundamental laws of generative AI" to reinforce the responsible and ethical use of AI in the creativity field. Four…
Descriptors: Artificial Intelligence, Creativity, Man Machine Systems, Ethics
Fangshu Yao; Bin Zhou – Cognitive Research: Principles and Implications, 2025
Humans usually adjust their attentional mode to tackle the challenges posed by environmental inputs. Depending on the uncertainty level, different attentional strategies may be adopted. As people face increasingly complicated daily situations--e.g., driving a car or chatting online--where intervals between significant events do not necessarily…
Descriptors: Attention Control, Eye Movements, Time, Time Perspective
Mohd Kamal Othman; Rahimah Mat; Norehan Zulkiply – Education and Information Technologies, 2025
This research addresses the critical need for robust usability evaluation tools in Wearable Virtual Reality Educational Applications. We developed a comprehensive set of Wearable Virtual Reality Educational Applications usability heuristics through a multi-stage process. Initial heuristics were established through a literature review. Validation…
Descriptors: Assistive Technology, Computer Simulation, Technology Uses in Education, Usability
Maria Ranieri; Gabriele Biagin – Research on Education and Media, 2025
This paper explores a new perspective on the relationship between human intelligence and artificial intelligence (AI), challenging the traditional dualistic and competitive view. Drawing on the concept of a "third space" -- inspired by postcolonial and philosophical theories such as those of Homi K. Bhabha and Donna Haraway -- this study…
Descriptors: Artificial Intelligence, Intelligence, Man Machine Systems, Computer Use
Feng Hsu Wang – IEEE Transactions on Learning Technologies, 2024
Due to the development of deep learning technology, its application in education has received increasing attention from researchers. Intelligent agents based on deep learning technology can perform higher order intellectual tasks than ever. However, the high deployment cost of deep learning models has hindered their widespread application in…
Descriptors: Learning Processes, Models, Man Machine Systems, Cooperative Learning
Laura E. Matzen; Zoe N. Gastelum; Breannan C. Howell; Kristin M. Divis; Mallory C. Stites – Cognitive Research: Principles and Implications, 2024
This study addressed the cognitive impacts of providing correct and incorrect machine learning (ML) outputs in support of an object detection task. The study consisted of five experiments that manipulated the accuracy and importance of mock ML outputs. In each of the experiments, participants were given the T and L task with T-shaped targets and…
Descriptors: Artificial Intelligence, Error Patterns, Decision Making, Models
Habeeb Yusuf; Arthur Money; Damon Daylamani-Zad – Educational Technology Research and Development, 2025
The ever-changing global educational landscape, coupled with the advancement of Web3, is seeing rapid changes in the ways pedagogical artificially intelligent conversational agents are being developed and used to advance teaching and learning in higher education. Given the rapidly evolving research landscape, there is a need to establish what the…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Higher Education
Yan Li; Xinyan Zhou; Hong-biao Yin; Thomas K. F. Chiu – Smart Learning Environments, 2025
Artificial Intelligence (AI) chatbots, with their ability to engage in conversations that resemble human interactions, have been increasingly applied to language teaching. Most recent review studies overlook student learning outcomes and the methods to achieve these outcomes in chatbot-supported language learning. Activity Theory (AT) offers a…
Descriptors: Artificial Intelligence, Educational Technology, Language Acquisition, Outcomes of Education
Evaluation of AI Content Generation Tools for Verification of Academic Integrity in Higher Education
Muhammad Bilal Saqib; Saba Zia – Journal of Applied Research in Higher Education, 2025
Purpose: The notion of using a generative artificial intelligence (AI) engine for text composition has gained excessive popularity among students, educators and researchers, following the introduction of ChatGPT. However, this has added another dimension to the daunting task of verifying originality in academic writing. Consequently, the market…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Evaluation
Abdullah Al-Abri – Education and Information Technologies, 2025
This study explores the impact of ChatGPT, an advanced Large Language Model (LLM), as a virtual tutor in online education across five key dimensions: answering questions, writing assistance, study resources, exam preparation, and availability. Utilizing an experimental design, 68 undergraduate students from a public university interacted with…
Descriptors: Artificial Intelligence, Natural Language Processing, Man Machine Systems, Intelligent Tutoring Systems

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