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Xueqiao Zhang; Chao Zhang; Jianwen Sun; Jun Xiao; Yi Yang; Yawei Luo – IEEE Transactions on Learning Technologies, 2025
Large language models (LLMs) have significantly advanced smart education in the artificial general intelligence era. A promising application lies in the automatic generalization of instructional design for curriculum and learning activities, focusing on two key aspects: 1) customized generation: generating niche-targeted teaching content based on…
Descriptors: Artificial Intelligence, Instructional Design, Technology Uses in Education, Cognitive Ability
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Malte Rolf Teichmann – IEEE Transactions on Learning Technologies, 2025
Due to the rise of virtual reality and the--at least now--hypothetical construct of the Metaverse, learning processes are increasingly transferred to immersive virtual learning environments. While the literature provides few design guidelines, most papers miss an application and evaluation description of the design and development processes. As a…
Descriptors: Instructional Design, Computer Simulation, Educational Environment, Learning Processes
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Ronak R. Mohanty; Peter Selly; Lindsey Brenner; Shantanu Vyas; Cassidy R. Nelson; Jason B. Moats; Joseph L. Gabbard; Ranjana K. Mehta – IEEE Transactions on Learning Technologies, 2025
Immersive extended reality (XR) technologies, including augmented reality (AR), virtual reality, and mixed reality, are transforming the landscape of education and training through experiences that promote skill acquisition and enhance memory retention. These technologies have notably improved decision making and situational awareness in public…
Descriptors: Technology Integration, Artificial Intelligence, Safety Education, Instructional Design
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Pallavi Singh; Phat K. Huynh; Dang Nguyen; Trung Q. Le; Wilfrido Moreno – IEEE Transactions on Learning Technologies, 2025
In organizational and academic settings, the strategic formation of teams is paramount, necessitating an approach that transcends conventional methodologies. This study introduces a novel application of multicriteria integer programming (MCIP), which simultaneously accommodates multiple criteria, thereby innovatively addressing the complex task of…
Descriptors: Teamwork, Group Dynamics, Research Design, Models
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Amarpreet Gill; Derek Irwin; Linjing Sun; Dave Towey; Gege Zhang; Yanhui Zhang – IEEE Transactions on Learning Technologies, 2025
The rapid changes in technology available for teaching and learning have led to a wide variety of potential tools that can be deployed to support a student's education experience. This article examines the learning interfaces for pedagogical virtual reality (VR) environments, including immersive VR (iVR). It also looks at how microlearning (ML)…
Descriptors: Computer Simulation, Learning Activities, Electronic Learning, Learning Modules
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Marcela Pessoa; Marcia Lima; Fernanda Pires; Gabriel Haydar; Rafaela Melo; Luiz Rodrigues; David Oliveira; Elaine Oliveira; Leandro Galvao; Bruno Gadelha; Seiji Isotani; Isabela Gasparini; Tayana Conte – IEEE Transactions on Learning Technologies, 2024
Game designers and researchers have sought to create gameful environments that consider user preferences to increase engagement and motivation. In this sense, it is essential to identify the most suitable game elements for users' profiles. Designers and researchers must choose strategies to classify users into predefined profiles and select the…
Descriptors: Educational Environment, Game Based Learning, Classification, Learner Engagement
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Nicolas Pope; Juho Kahila; Henriikka Vartiainen; Matti Tedre – IEEE Transactions on Learning Technologies, 2025
The rapid advancement of artificial intelligence and its increasing societal impacts have turned many computing educators' focus toward early education in machine learning (ML). Limited options for educational tools for teaching novice learners about the mechanisms of ML and data-driven systems presents a recognized challenge in K-12 computing…
Descriptors: Artificial Intelligence, Computer Oriented Programs, Computer Science Education, Grade 4
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Yu Lu; Deliang Wang; Penghe Chen; Zhi Zhang – IEEE Transactions on Learning Technologies, 2024
Amid the rapid evolution of artificial intelligence (AI), the intricate model structures and opaque decision-making processes of AI-based systems have raised the trustworthy issues in education. We, therefore, first propose a novel three-layer knowledge tracing model designed to address trustworthiness for an intelligent tutoring system. Each…
Descriptors: Models, Intelligent Tutoring Systems, Artificial Intelligence, Technology Uses in Education
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Esteban Villalobos; Mar Perez-Sanagustin; Roger Azevedo; Cedric Sanza; Julien Broisin – IEEE Transactions on Learning Technologies, 2024
Blended learning (BL) has become increasingly popular in higher education institutions. Despite its popularity and the advances in methodologies for the detection of learning tactics and strategies from trace data, little is known about how they apply to BL settings and, therefore, how students use them to plan, organize, monitor, and regulate…
Descriptors: Metacognition, Learning Strategies, Blended Learning, Instructional Design
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Bihao Hu; Longwei Zheng; Jiayi Zhu; Lishan Ding; Yilei Wang; Xiaoqing Gu – IEEE Transactions on Learning Technologies, 2024
This study explores and analyzes the specific performance of large language models (LLMs) in instructional design, aiming to unveil their potential strengths and possible weaknesses. Recently, the influence of LLMs has gradually increased in multiple fields, yet exploratory research on their application in education remains relatively scarce. In…
Descriptors: Artificial Intelligence, Natural Language Processing, Instructional Design, Prompting
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Yussy Chinchay; Cesar A. Collazos; Javier Gomez; German Montoro – IEEE Transactions on Learning Technologies, 2024
This research focuses on the assessment of attention to identify the design needs for optimized learning technologies for children with autism. Within a single case study incorporating a multiple-baseline design involving baseline, intervention, and postintervention phases, we developed an application enabling personalized attention strategies.…
Descriptors: Autism Spectrum Disorders, Educational Technology, Technology Uses in Education, Interaction
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Jose Barambones; Cristian Moral; Angelica de Antonio; Ricardo Imbert; Loic Martinez-Normand; Elena Villalba-Mora – IEEE Transactions on Learning Technologies, 2024
Before interacting with real users, developers must be proficient in human--computer interaction (HCI) so as not to exhaust user patience and availability. For that, substantial training and practice are required, but it is costly to create a variety of high-quality HCI training materials. In this context, chat generative pretrained transformer…
Descriptors: Artificial Intelligence, Synchronous Communication, Computer Mediated Communication, Man Machine Systems
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Chen Li; Yue Jiang; Peter H. F. Ng; Yixin Dai; Francis Cheung; Henry C. B. Chan; Ping Li – IEEE Transactions on Learning Technologies, 2024
Computer-supported collaborative learning aims to use information technologies to support collaborative knowledge construction by practicing the relevant pedagogical approaches, especially in the distance learning setting. The enabling technologies are fast advancing, and the need for solutions during the COVID-19 global pandemic led to the…
Descriptors: Computer Simulation, Computer Assisted Instruction, Cooperative Learning, Technology Uses in Education
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Huaiya Liu; Yuyue Zhang; Jiyou Jia – IEEE Transactions on Learning Technologies, 2024
Intelligent tutoring systems (ITSs) aim to deliver personalized learning support to each learner, aligning with the educational aspiration of many countries, including China. ITSs' personalized support is mainly achieved by providing individual prompts to learners when they encounter difficulties in problem-solving. The guiding principles and…
Descriptors: Intelligent Tutoring Systems, Mathematics Achievement, Individualized Instruction, Foreign Countries
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Roshan Lal Neupane; Prasad Calyam; Songjie Wang; Kiran Neupane; Ashish Pandey; Xiyao Cheng; Durbek Gafurov; Hemanth Sai Yeddulapalli; Noah Glaser; Kanu Priya Singh; Yuanyuan Gu; Shangman Li; Sharan Srinivas – IEEE Transactions on Learning Technologies, 2024
Cloud-hosted services are being increasingly used in hosting business and scientific applications due to cost-effectiveness, scalability, and ease of deployment. To facilitate rapid development, change and release process of cloud-hosted applications, the area of development and operations (DevOps) is fast evolving. It is necessary to train the…
Descriptors: Online Courses, Computer Assisted Instruction, Learning Management Systems, Computer Assisted Design
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