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Showing 1 to 15 of 96 results Save | Export
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Ruben Till Wittrin; Benny Platte; Christian Roschke; Marc Ritter; Maximilian Eibl; Carolin Isabel Steiner; Volker Tolkmitt – IEEE Transactions on Learning Technologies, 2024
Virtual environments open up far-reaching possibilities with respect to knowledge impartation. Nevertheless, they have the potential to negatively influence learning behavior. As a possible positive determinant, especially in the digital context, the moment "game" can be listed. Accordingly, previous studies prove an overall positive…
Descriptors: Game Based Learning, Learning Motivation, Academic Achievement, Electronic Learning
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Simone Porcu; Alessandro Floris; Luigi Atzori – IEEE Transactions on Learning Technologies, 2025
In this article, we preliminarily discuss the limitations of current video conferencing platforms in online synchronous learning. Research has shown that while the involved technologies are appropriate for collaborative video calls, they often fail to replicate the rich nature of face-to-face interactions among students and between students and…
Descriptors: Computer Simulation, Electronic Learning, Synchronous Communication, Videoconferencing
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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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Chamba-Eras, Luis; Arruarte, Ana; Elorriaga, Jon A. – IEEE Transactions on Learning Technologies, 2023
In the context of virtual learning communities (VLCs), where the participants may not know each other, it is necessary to have a mechanism to help when deciding who to work with and what reliable contents and information sources are. This study aims to design a generic trust model, named T-VLC, applicable to VLCs, which can be adapted to different…
Descriptors: Communities of Practice, Electronic Learning, Trust (Psychology), Models
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Huang, Tao; Hu, Shengze; Yang, Huali; Geng, Jing; Liu, Sannyuya; Zhang, Hao; Yang, Zongkai – IEEE Transactions on Learning Technologies, 2023
The global outbreak of the new coronavirus epidemic has promoted the development of intelligent education and the utilization of online learning systems. In order to provide students with intelligent services, such as cognitive diagnosis and personalized exercises recommendation, a fundamental task is the concept tagging for exercises, which…
Descriptors: Educational Technology, Prediction, Electronic Learning, Intelligent Tutoring Systems
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Milos Ilic; Goran Kekovic; Vladimir Mikic; Katerina Mangaroska; Lazar Kopanja; Boban Vesin – IEEE Transactions on Learning Technologies, 2024
In recent years, there has been an increasing trend of utilizing artificial intelligence (AI) methodologies over traditional statistical methods for predicting student performance in e-learning contexts. Notably, many researchers have adopted AI techniques without conducting a comprehensive investigation into the most appropriate and accurate…
Descriptors: Artificial Intelligence, Academic Achievement, Prediction, Programming
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Yao, Shu-Nung; Liang, Chaoyun – IEEE Transactions on Learning Technologies, 2023
Image processing-based augmented reality (AR) is widely used in several fields. However, audio content is also crucial in certain cases, for example, focusing on appreciating artwork in a museum, rather than a virtually synthesized image. In this study, an attempt was made to provide ubiquitous learning (u-learning) services by using audio AR for…
Descriptors: Computer Simulation, Electronic Learning, Audio Equipment, Educational Technology
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Qiusha Min; Zhongwei Zhou; Ziyi Li; Mei Wu – IEEE Transactions on Learning Technologies, 2024
Instructional videos are often a key component of online learning, and their quality significantly influences online learning outcomes and student satisfaction. However, instructional video evaluation is time-consuming. To solve this problem, this study developed an automatic evaluation method for instructional videos. This method first…
Descriptors: Electronic Learning, Outcomes of Education, Program Evaluation, Student Evaluation
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Xiangping Cui; Chen Du; Jun Shen; Susan Zhang; Juan Xu – IEEE Transactions on Learning Technologies, 2024
Research shows that gamified learning experiences can effectively improve the outstanding issues of students in online learning, such as lack of continuous motivation and easy burnout, thereby improving the effectiveness of online learning. However, how to enhance the gamified learning experience in online learning, and what impact there is…
Descriptors: Gamification, Learning Experience, Electronic Learning, Instructional Effectiveness
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Okubo, Fumiya; Shiino, Tetsuya; Minematsu, Tsubasa; Taniguchi, Yuta; Shimada, Atsushi – IEEE Transactions on Learning Technologies, 2023
In this study, we propose an integrated system to support learners' reviews. In the proposed system, the review dashboard is used to recommend review contents that are adaptive to the individual learner's level of understanding and to present other information that is useful for review. The pages of the digital learning materials that are…
Descriptors: Learning Management Systems, Student Evaluation, Automation, Artificial Intelligence
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Weijiao Huang; Khe Foon Hew – IEEE Transactions on Learning Technologies, 2025
In an online learning environment, both instruction and assessments take place virtually where students are primarily responsible for managing their own learning. This requires a high level of self-regulation from students. Many online students, however, lack self-regulation skills and are ill-prepared for autonomous learning, which can cause…
Descriptors: Independent Study, Interpersonal Relationship, Electronic Learning, Computer Software
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Deeva, Galina; De Smedt, Johannes; De Weerdt, Jochen – IEEE Transactions on Learning Technologies, 2022
Due to the unprecedented growth in available data collected by e-learning platforms, including platforms used by massive open online course (MOOC) providers, important opportunities arise to structurally use these data for decision making and improvement of the educational offering. Student retention is a strategic task that can be supported by…
Descriptors: Electronic Learning, MOOCs, Dropouts, Prediction
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Saenz, Jacobo; de la Torre, Luis; Chacon, Jesus; Dormido, Sebastian – IEEE Transactions on Learning Technologies, 2021
Researchers and teachers around the world have created newsoftware and hardware to develop, reuse, and deploy online laboratories (labs). However, due to the nature of labs, most of the available solutions depend greatly on where and how online labs can be used in the first place. Thus, there have been multiple design solutions and great…
Descriptors: Electronic Learning, Instructional Design, Learning Laboratories, Educational Strategies
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Behzad Mirzababaei; Viktoria Pammer-Schindler – IEEE Transactions on Learning Technologies, 2024
In this article, we investigate a systematic workflow that supports the learning engineering process of formulating the starting question for a conversational module based on existing learning materials, specifying the input that transformer-based language models need to function as classifiers, and specifying the adaptive dialogue structure,…
Descriptors: Learning Processes, Electronic Learning, Artificial Intelligence, Natural Language Processing
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Teemu H. Laine; Woohyun Lee – IEEE Transactions on Learning Technologies, 2024
The metaverse is a network of interoperable and persistent 3-D virtual worlds where users can coexist and interact through mechanisms, such as gamification, nonfungible tokens, and cryptocurrencies. Although the metaverse is a theoretical construct today, many collaborative virtual reality (CVR) applications have emerged as potential components of…
Descriptors: Computer Simulation, Simulated Environment, College Students, Student Attitudes
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