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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
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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
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A. N. Varnavsky – IEEE Transactions on Learning Technologies, 2024
The most critical parameter of audio and video information output is the playback speed, which affects many viewing or listening metrics, including when learning using tutoring systems. However, the availability of quantitative models for personalized playback speed control considering the learner's personal traits is still an open question. The…
Descriptors: Hierarchical Linear Modeling, Intelligent Tutoring Systems, Individualized Instruction, Electronic Learning
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Marc Burchart; Joerg M. Haake – IEEE Transactions on Learning Technologies, 2024
In distance education courses with a large number of students and groups, the organization and facilitation of collaborative writing tasks are challenging. Teachers need support for planning, specification, execution, monitoring, and evaluation of collaborative writing tasks in their course. This requires a collaborative learning platform for…
Descriptors: Writing Instruction, Distance Education, Large Group Instruction, Learning Management Systems
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Lishan Zhang; Linyu Deng; Sixv Zhang; Ling Chen – IEEE Transactions on Learning Technologies, 2024
With the popularity of online one-to-one tutoring, there are emerging concerns about the quality and effectiveness of this kind of tutoring. Although there are some evaluation methods available, they are heavily relied on manual coding by experts, which is too costly. Therefore, using machine learning to predict instruction quality automatically…
Descriptors: Automation, Classification, Artificial Intelligence, Tutoring
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Xiang Wu; Huanhuan Wang; Yongting Zhang; Baowen Zou; Huaqing Hong – IEEE Transactions on Learning Technologies, 2024
Generative artificial intelligence has become the focus of the intelligent education field, especially in the generation of personalized learning resources. Current learning resource generation methods recommend customized courses based on learning styles and interests, improving learning efficiency. However, these methods cannot generate…
Descriptors: Artificial Intelligence, Individualized Instruction, Intelligent Tutoring Systems, Cognitive Style
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Lukac, Zeljko; Kastelan, Ivan; Vranjes, Mario; Todorovic, Branislav M. – IEEE Transactions on Learning Technologies, 2021
Education of electronics engineers is one of the most dynamic types of education due to the new technologies that are rapidly being introduced into the field. Therefore, it is necessary to use modern teaching and laboratory methods that accompany the development of new technologies. When it comes to the automotive industry, a modern vehicle must…
Descriptors: Engineering Education, Motor Vehicles, Masters Programs, Computer Software
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Wan, Pengfei; Wang, Xiaoming; Lin, Yaguang; Pang, Guangyao – IEEE Transactions on Learning Technologies, 2021
Learners' autonomous learning is at the heart of modern education, and the convenient network brings new opportunities for it. We notice that learners mainly use the combination of online and offline learning methods to complete the entire autonomous learning process, but most of the existing models cannot effectively describe the complex process…
Descriptors: Independent Study, Personal Autonomy, Learning Processes, Electronic Learning
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Che, Xiaoyin; Yang, Haojin; Meinel, Christoph – IEEE Transactions on Learning Technologies, 2018
Textbook highlighting is widely considered to be beneficial for students. In this paper, we propose a comprehensive solution to highlight the online lecture videos in both sentence- and segment-level, just as is done with paper books. The solution is based on automatic analysis of multimedia lecture materials, such as speeches, transcripts, and…
Descriptors: Online Courses, Comparative Analysis, Lecture Method, Multimedia Materials
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Karavirta, Ville; Shaffer, Clifford A. – IEEE Transactions on Learning Technologies, 2016
Data Structures and Algorithms are a central part of Computer Science. Due to their abstract and dynamic nature, they are a difficult topic to learn for many students. To alleviate these learning difficulties, instructors have turned to algorithm visualizations (AV) and AV systems. Research has shown that especially engaging AVs can have an impact…
Descriptors: Electronic Learning, Computer Science, Animation, Mathematics
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Gilman, Ekaterina; Milara, Iván Sánchez; Cortes, Marta; Riekki, Jukka – IEEE Transactions on Learning Technologies, 2015
New technologies enable novel types of learning activities that differ radically from traditional approach of visiting lectures and doing homework assignments. Namely, these technologies support transforming our everyday environments into learning environments. This concept is referred to in the literature as ubiquitous learning. Enriching…
Descriptors: Electronic Learning, Educational Technology, State of the Art Reviews, Learning Activities
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Karataev, Evgeny; Zadorozhny, Vladimir – IEEE Transactions on Learning Technologies, 2017
Many techniques have been developed to enhance learning experience with computer technology. A particularly great influence of technology on learning came with the emergence of the web and adaptive educational hypermedia systems. While the web enables users to interact and collaborate with each other to create, organize, and share knowledge via…
Descriptors: Socialization, Social Networks, Electronic Publishing, Collaborative Writing
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Verbert, K.; Manouselis, N.; Ochoa, X.; Wolpers, M.; Drachsler, H.; Bosnic, I.; Duval, E. – IEEE Transactions on Learning Technologies, 2012
Recommender systems have been researched extensively by the Technology Enhanced Learning (TEL) community during the last decade. By identifying suitable resources from a potentially overwhelming variety of choices, such systems offer a promising approach to facilitate both learning and teaching tasks. As learning is taking place in extremely…
Descriptors: Technology Uses in Education, Individualized Instruction, Electronic Learning, Educational Technology
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Chandra, Surendar – IEEE Transactions on Learning Technologies, 2011
The ability of lecture videos to capture the different modalities of a class interaction make them a good review tool. Multimedia capable devices are ubiquitous among contemporary students. Many lecturers are leveraging this popularity by distributing videos of lectures. They depend on the university to provide the video capture infrastructure.…
Descriptors: Computers, Educational Technology, Information Technology, Distance Education
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Martinez-Garcia, A.; Morris, S.; Tscholl, M.; Tracy, F.; Carmichael, P. – IEEE Transactions on Learning Technologies, 2012
This paper explores the potential of Semantic Web technologies to support teaching and learning in a variety of higher education settings in which some form of case-based learning is the pedagogy of choice. It draws on the empirical work of a major three year research and development project in the United Kingdom: "Ensemble: Semantic…
Descriptors: Foreign Countries, Program Descriptions, Teaching Methods, Instructional Innovation