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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
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
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
Xiao, Hui; Hu, Wenshan; Liu, Guo-Ping – IEEE Transactions on Learning Technologies, 2023
In conventional laboratories, engineering students must attend in person to conduct experiments with real equipment in a physical place, where their work is mainly assessed through self-reports and attendance records. By comparison, online labs can record and analyze students' activities and behaviors automatically. Thus, this article proposes a…
Descriptors: Electronic Learning, Science Laboratories, Engineering Education, Distance Education
Analysis and Prediction of Students' Performance in a Computer-Based Course through Real-Time Events
Lucia Uguina-Gadella; Iria Estevez-Ayres; Jesus Arias Fisteus; Carlos Alario-Hoyos; Carlos Delgado Kloos – IEEE Transactions on Learning Technologies, 2024
Students learn not only directly from their teachers and books, but also by using their computers, tablets, and phones. Monitoring these learning environments creates new opportunities for teachers to track students' progress. In particular, this article is based on gathering real-time events as students interact with learning tools and materials…
Descriptors: Predictor Variables, Academic Achievement, Computer Assisted Instruction, Electronic Learning
Maiti, Ananda; Raza, Ali; Kang, Byeong Ho – IEEE Transactions on Learning Technologies, 2021
The Internet-of-Things (IoT) is a collection of technologies to bring the Internet to physically embedded devices and to embed them deeply into human activities to aid in a variety of activities. IoT gained traction with developers and consumers in recent years, driven by low-cost open-source hardware that enables easy prototyping and testing. IoT…
Descriptors: Internet, Active Learning, Student Projects, College Students
Kim, Hodam; Chae, Younsoo; Kim, Suhye; Im, Chang-Hwan – IEEE Transactions on Learning Technologies, 2023
Owing to the rapid development of information and communication technologies, online or mobile learning content is widely available on the Internet. Unlike traditional face-to-face learning, online learning exhibits a critical limitation: real-time interactions between learners and teachers are generally not feasible in online learning. To…
Descriptors: College Students, Control Groups, Attention, Comprehension
Nabizadeh, Amir Hossein; Goncalves, Daniel; Gama, Sandra; Jorge, Joaquim – IEEE Transactions on Learning Technologies, 2022
The main challenge in higher education is student retention. While many methods have been proposed to overcome this challenge, early and continuous feedback can be very effective. In this article, we propose a method for predicting student final grades in a course using only their performance data in the current semester. It assists students in…
Descriptors: College Students, Prediction, Grades (Scholastic), Game Based Learning
Kim, Jihyung; Kim, Kyeongsun; Kim, Wooksung – IEEE Transactions on Learning Technologies, 2022
This article investigated the impact of immersive virtual reality (VR) content, using 360-degree videos, in undergraduate education. To improve the delivery and reality of 360-degree VR content, we filmed the video in the third person so that the viewers could feel like they were in the environment where the lecture was conducted. To verify the…
Descriptors: Computer Simulation, Video Technology, Undergraduate Study, College Students
Asiri, Yousef A.; Millard, David E.; Weal, Mark J. – IEEE Transactions on Learning Technologies, 2021
Digital behavior change interventions (DBCIs) provide customized advice, ongoing support, and Web- and mobile-based platforms for learners who want to change their undesirable behaviors. DBCIs have been successful in the past for delivering interventions that support sustained changes to health behaviors, such as disease prevention and health…
Descriptors: Learner Engagement, Feedback (Response), Behavior Change, Intervention
Kappagantula, Sri Rama Kartheek; Adamo-Villani, Nicoletta; Wu, Meng-Lin; Popescu, Voicu – IEEE Transactions on Learning Technologies, 2020
We present a system that automatically generates deictic gestures for animated pedagogical agents (APAs). The system takes audio and text as input, which define what the APA has to say, and generates animated gestures based on a set of rules. The automatically generated gestures point to the exact locations of elements on a whiteboard nearby the…
Descriptors: Animation, Nonverbal Communication, Lecture Method, Video Technology
Holmes, Mike; Latham, Annabel; Crockett, Keeley; O'Shea, James D. – IEEE Transactions on Learning Technologies, 2018
Comprehension is an important cognitive state for learning. Human tutors recognize comprehension and non-comprehension states by interpreting learner non-verbal behavior (NVB). Experienced tutors adapt pedagogy, materials, and instruction to provide additional learning scaffold in the context of perceived learner comprehension. Near real-time…
Descriptors: Comprehension, Classification, Artificial Intelligence, Networks
Auvinen, Tapio; Hakulinen, Lasse; Malmi, Lauri – IEEE Transactions on Learning Technologies, 2015
In online learning environments where automatic assessment is used, students often resort to harmful study practices such as procrastination and trial-and-error. In this paper, we study two teaching interventions that were designed to address these issues in a university-level computer science course. In the first intervention, we used achievement…
Descriptors: Student Behavior, Electronic Learning, Online Courses, Computer Assisted Testing
Grunewald, Franka; Meinel, Christoph – IEEE Transactions on Learning Technologies, 2015
The use of video lectures in distance learning involves the two major problems of searchability and active user participation. In this paper, we promote the implementation and usage of a collaborative educational video annotation functionality to overcome these two challenges. Different use cases and requirements, as well as details of the…
Descriptors: Web Based Instruction, Lecture Method, Video Technology, Notetaking
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