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Sonsoles Lopez-Pernas; Kamila Misiejuk; Rogers Kaliisa; Mohammed Saqr – IEEE Transactions on Learning Technologies, 2025
Despite the growing use of large language models (LLMs) in educational contexts, there is no evidence on how these can be operationalized by students to generate custom datasets suitable for teaching and learning. Moreover, in the context of network science, little is known about whether LLMs can replicate real-life network properties. This study…
Descriptors: Students, Artificial Intelligence, Man Machine Systems, Interaction
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Chen, Xieling; Zou, Di; Xie, Haoran; Wang, Fu Lee – IEEE Transactions on Learning Technologies, 2023
Research on Educational Metaverse (Edu-Metaverse) has developed into an active research field. Based on 310 academic papers published from 2004 to 2022, this study identifies contributors, scientific cooperations, and research themes using bibliometrics, social network analysis, topic modeling, and keyword analysis. Results suggest that…
Descriptors: Computer Simulation, Technology Uses in Education, Bibliometrics, Social Networks
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Muhuri, Samya; Mukhopadhyay, Debajyoti – IEEE Transactions on Learning Technologies, 2022
A paradigm shift can be expected in the education sector, especially after the COVID-19 pandemic. E-learning systems are being adopted by all the stakeholders as physical meetings are not feasible. Different online learning attributes, such as video conferencing tools, coding platforms, online learning frameworks, digital books, and online videos,…
Descriptors: Students, Online Courses, Social Networks, Interpersonal Relationship
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Joksimovic, Srecko; Jovanovic, Jelena; Kovanovic, Vitomir; Gasevic, Dragan; Milikic, Nikola; Zouaq, Amal; van Staalduinen, Jan Paul – IEEE Transactions on Learning Technologies, 2020
Learning in computer-mediated setting represents a complex, multidimensional process. This complexity calls for a comprehensive analytical approach that would allow for understanding of various dimensions of learner generated discourse and the structure of the underlying social interactions. Current research, however, primarily focuses on manual…
Descriptors: Group Discussion, Speech Acts, Computer Assisted Instruction, Discourse Analysis
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Fincham, Ed; Rozemberczki, Benedek; Kovanovic, Vitomir; Joksimovic, Srecko; Jovanovic, Jelena; Gasevic, Dragan – IEEE Transactions on Learning Technologies, 2021
In this article, we empirically validate Tinto's Student Integration model, in particular, the predictions the model makes regarding both students' academic outcomes and their dropout decisions. In doing so, we analyze three decades' worth of student enrollments at an Australian university and present a novel methodological approach using graph…
Descriptors: Models, Prediction, Outcomes of Education, Dropouts
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Alemany, Jose; Del Val, Elena; Garcia-Fornes, Ana – IEEE Transactions on Learning Technologies, 2020
The concept of privacy in online social networks (OSNs) is a challenge, especially for teenagers. Previous works deal with teaching about privacy using educational online content, and media literacy. However, these tools do not necessarily promote less risky behaviors, and do not allow the assessment of users' behavior after the learning period.…
Descriptors: Social Networks, Adolescents, Privacy, Educational Technology
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Krouska, Akrivi; Virvou, Maria – IEEE Transactions on Learning Technologies, 2020
Social networking-based learning (SN-learning) is one of the most promising innovations to promote learning via a social network, and thus, providing a more interactive, student-centered, cooperative, and on-demand environment. In such an environment, group formation plays an important role to the effectiveness of learning process. Adequate groups…
Descriptors: Social Networks, Cooperative Learning, Computer Uses in Education, Grouping (Instructional Purposes)
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Claros, Iván; Cobos, Ruth; Collazos, César A. – IEEE Transactions on Learning Technologies, 2016
The Social Network Analysis (SNA) techniques allow modelling and analysing the interaction among individuals based on their attributes and relationships. This approach has been used by several researchers in order to measure the social processes in collaborative learning experiences. But oftentimes such measures were calculated at the final state…
Descriptors: Social Networks, Network Analysis, Cooperative Learning, Learning Experience
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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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Achilleos, Achilleas P.; Mettouris, Christos; Yeratziotis, Alexandros; Papadopoulos, George A.; Pllana, Sabri; Huber, Florian; Jager, Bernhard; Leitner, Peter; Ocsovszky, Zsofia; Dinnyes, Andras – IEEE Transactions on Learning Technologies, 2019
Scientific and technological innovations have become increasingly important as we face the benefits and challenges of both globalization and a knowledge-based economy. Still, enrolment rates in STEM degrees are low in many European countries and consequently there is a lack of adequately educated workforce in industries. We believe that this can…
Descriptors: Social Media, STEM Education, Student Motivation, Foreign Countries
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Chao, Han-Chieh; Lai, Chin-Feng; Chen, Shih-Yeh; Huang, Yueh-Min – IEEE Transactions on Learning Technologies, 2014
With the rapid development of the Internet and the popularization of mobile devices, participating in a mobile community becomes a part of daily life. This study aims the influence impact of social interactions on mobile learning communities. With m-learning content recommendation services developed from mobile devices and mobile network…
Descriptors: Electronic Learning, Interpersonal Relationship, Social Networks, Elementary School Students
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Chen, Weiyu; Brinton, Christopher G.; Cao, Da; Mason-Singh, Amanda; Lu, Charlton; Chiang, Mung – IEEE Transactions on Learning Technologies, 2019
We study learning outcome prediction for online courses. Whereas prior work has focused on semester-long courses with frequent student assessments, we focus on short-courses that have single outcomes assigned by instructors at the end. The lack of performance data and generally small enrollments makes the behavior of learners, captured as they…
Descriptors: Online Courses, Outcomes of Education, Prediction, Course Content
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Gitinabard, Niki; Xu, Yiqiao; Heckman, Sarah; Barnes, Tiffany; Lynch, Collin F. – IEEE Transactions on Learning Technologies, 2019
Blended courses that mix in-person instruction with online platforms are increasingly common in secondary education. These platforms record a rich amount of data on students' study habits and social interactions. Prior research has shown that these metrics are correlated with students performance in face-to-face classes. However, predictive models…
Descriptors: Blended Learning, Educational Technology, Technology Uses in Education, Prediction
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Dong, Jian-Jie; Hwang, Wu-Yuin; Shadiev, Rustam; Chen, Ginn-Yein – IEEE Transactions on Learning Technologies, 2019
In this study, we developed an on-call-tutor system to facilitate peer-help activities. The system was implemented in a face-to-face heterogeneous classroom with 119 students from different departments who were not familiar with each other. Students learned Geographic Information System (GIS) in a computer classroom in two groups: students, who…
Descriptors: Peer Teaching, Synchronous Communication, Social Networks, Friendship
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Castellanos, Jorge; Haya, Pablo A.; Urquiza-Fuentes, Jaime – IEEE Transactions on Learning Technologies, 2017
STEM (Science, Technology, Engineering, and Math) education is currently receiving much attention from governments and educational institutions. Our work is based on active learning and video-based learning approaches to support STEM education. Here, we aimed to increase students' engagement through reflective processes that embrace video…
Descriptors: STEM Education, Educational Technology, Technology Uses in Education, Video Technology
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