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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
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
Houssam El Aouifi; Mohamed El Hajji; Youssef Es-Saady; Hassan Douzi – IEEE Transactions on Learning Technologies, 2024
Recently, using videos as a learning resource has received a lot of attention and turned widely exploited as an effective learning tool. With the rapid spread of instructional videos, the number of these tools in all disciplines is becoming very high. It is fractious for learners to find video courses adapted to their needs. Recommender system is…
Descriptors: Video Technology, Teaching Methods, Instructional Effectiveness, Cognitive Style
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
Yufeng Wang; Dehua Ma; Jianhua Ma; Qun Jin – IEEE Transactions on Learning Technologies, 2024
As one of the fundamental tasks in the online learning platform, interactive course recommendation (ICR) aims to maximize the long-term learning efficiency of each student, through actively exploring and exploiting the student's feedbacks, and accordingly conducting personalized course recommendation. Recently, deep reinforcement learning (DRL)…
Descriptors: Electronic Learning, Student Interests, Artificial Intelligence, Intelligent Tutoring Systems
Shuanghong Shen; Qi Liu; Zhenya Huang; Yonghe Zheng; Minghao Yin; Minjuan Wang; Enhong Chen – IEEE Transactions on Learning Technologies, 2024
Modern online education has the capacity to provide intelligent educational services by automatically analyzing substantial amounts of student behavioral data. Knowledge tracing (KT) is one of the fundamental tasks for student behavioral data analysis, aiming to monitor students' evolving knowledge state during their problem-solving process. In…
Descriptors: Student Behavior, Electronic Learning, Data Analysis, Models
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
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
Qin Ni; Yifei Mi; Yonghe Wu; Liang He; Yuhui Xu; Bo Zhang – IEEE Transactions on Learning Technologies, 2024
Learning style recognition is an indispensable part of achieving personalized learning in online learning systems. The traditional inventory method for learning style identification faces the limitations such as subject and static characteristics. Therefore, an automatic and reliable learning style recognition mechanism is designed in this…
Descriptors: Cognitive Style, Electronic Learning, Prediction, Identification
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
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
Villalonga-Gomez, Cristina; Ortega-Fernandez, Eglee; Borau-Boira, Elena – IEEE Transactions on Learning Technologies, 2023
The application of the metaverse poses important challenges for the field of education. The aim of this article is to analyze the evolution of the development of the metaverse experiences in Higher Education and thus identify the key aspects of its application as a virtual environment for teaching and learning. To this end, a systematic literature…
Descriptors: Higher Education, Electronic Learning, Educational Environment, Second Language Instruction
Chen, Xu; Zhong, Zheng; Wu, Di – IEEE Transactions on Learning Technologies, 2023
As a third-generation Internet form, the Metaverse has received widespread attention for its spatio-temporal expansion, high immersion, sensory extension, and human--computer integration. Considering the prospect of application in the field of education, a series of studies on the design of Education Metaverse frameworks and applications have…
Descriptors: Computer Simulation, Simulated Environment, Design, Technology Uses in Education
Automatic Evaluation of Instructional Videos Based on Video Features and Student Watching Experience
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
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