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Showing 1 to 15 of 154 results Save | Export
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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
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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
Jacobus Ignatius DeBruyn – ProQuest LLC, 2024
This study explored the role of artificial intelligence (AI)-powered conversational agents in human-computer interaction, particularly in the post-coronavirus (COVID-19) era, where digital technologies are central to healthcare, customer service, and education sectors. The research investigated the disruption of context continuity when users…
Descriptors: Artificial Intelligence, Computer Mediated Communication, Man Machine Systems, Dialogs (Language)
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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
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Ruth Li – English Teaching: Practice and Critique, 2024
Purpose: This paper aims to offer an approach to cyborg composing with artificial intelligence (AI). The author posits that the hybridity of the cyborg, which amalgamates human and artificial elements, invites a cascade of creative and emancipatory possibilities. The author critically examines the biases embedded in AI systems while gesturing…
Descriptors: Artificial Intelligence, Man Machine Systems, Creative Writing, Poetry
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Yuan Liu; Shuaifei Huang; Weiguo Xu; Zhuang Wang; Dong Ming – npj Science of Learning, 2024
Generalization is central to motor learning. However, few studies are on the learning generalization of BCI-actuated supernumerary robotic finger (BCI-SRF) for human-machine interaction training, and no studies have explored its longitudinal neuroplasticity mechanisms. Here, 20 healthy right-handed participants were recruited and randomly assigned…
Descriptors: Man Machine Systems, Robotics, Brain Hemisphere Functions, Psychomotor Skills
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George Veletsianos; Shandell Houlden; Nicole Johnson – TechTrends: Linking Research and Practice to Improve Learning, 2024
Much of the literature on artificial intelligence (AI) in education imagines AI as a tool in the service of teaching and learning. Is such a one-way relationship all that exists between AI and learners? In this paper we report on a thematic analysis of 92 participant responses to a story completion exercise which asked them to describe a classroom…
Descriptors: Artificial Intelligence, Technology Uses in Education, Man Machine Systems, Interaction
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Daniel Wildcat – Tribal College Journal of American Indian Higher Education, 2024
The following is offered as only one Indigenous person's perspective--a Yuchi Muscogee tribal member's perspective. Several questions about AI emerge when we consider it through an (not the) Indigenous lens. Where is AI's heart and where is its spirit? Does this complex, fast source of intelligence have feelings or emotions? Does machine-generated…
Descriptors: Artificial Intelligence, Indigenous Populations, Cultural Context, Sustainability
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Yung-Ming Cheng – Interactive Technology and Smart Education, 2024
Purpose: The purpose of this study is to propose a research model based on the stimulus-organism-response (S-O-R) model to examine whether media richness (MR), human-system interaction (HSI) and human-human interaction (HHI) as technological feature antecedents to medical professionals' learning engagement (LE) can affect their learning…
Descriptors: MOOCs, Academic Persistence, Medical Education, Learner Engagement
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Daniel J. Carragher; Daniel Sturman; Peter J. B. Hancock – Cognitive Research: Principles and Implications, 2024
The human face is commonly used for identity verification. While this task was once exclusively performed by humans, technological advancements have seen automated facial recognition systems (AFRS) integrated into many identification scenarios. Although many state-of-the-art AFRS are exceptionally accurate, they often require human oversight or…
Descriptors: Automation, Human Body, Man Machine Systems, Accuracy
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Dominic Lohr; Hieke Keuning; Natalie Kiesler – Journal of Computer Assisted Learning, 2025
Background: Feedback as one of the most influential factors for learning has been subject to a great body of research. It plays a key role in the development of educational technology systems and is traditionally rooted in deterministic feedback defined by experts and their experience. However, with the rise of generative AI and especially large…
Descriptors: College Students, Programming, Artificial Intelligence, Feedback (Response)
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Changyu Yang; Adam Stivers – Journal of Education for Business, 2024
The rapid advancement of artificial intelligence (AI) has given rise to sophisticated language models that excel in understanding and generating human-like text. With the capacity to process vast amounts of information, these models effectively tackle problems across diverse domains. In this paper, we present a comparative analysis of prominent AI…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Comparative Analysis
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Letty Rising – Montessori Life: A Publication of the American Montessori Society, 2024
In the ever-evolving landscape of education, you have most likely experienced a significant expansion in your teaching responsibilities. Your role may have stretched to encompass being proficient in various technology platforms, nurturing the social and emotional learning of your students, and adjusting to amplified documentation requirements.…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Technology Uses in Education
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Ümmühan Avci; Feyza Akgül – Journal of Educational Technology and Online Learning, 2024
Digital transformation encompasses all the principles of people, working methods, and technology that support organizations in achieving their goals with the possibilities provided by the constantly developing information technologies that are in almost every aspect of our lives. Today, the impact of digital transformation is visible in every…
Descriptors: Computer Simulation, Technology Uses in Education, Man Machine Systems, Interaction
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Mohammed Saqr; Sonsoles López-Pernas – Smart Learning Environments, 2024
In learning analytics and in education at large, AI explanations are always computed from aggregate data of all the students to offer the "average" picture. Whereas the average may work for most students, it does not reflect or capture the individual differences or the variability among students. Therefore, instance-level…
Descriptors: Artificial Intelligence, Decision Making, Predictor Variables, Feedback (Response)
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