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Timothy Gallagher; Bert Slof; Marieke van der Schaaf; Michaela Arztmann; Sofia Garcia Fracaro; Liesbeth Kester – Journal of Computer Assisted Learning, 2024
Background: Learning analytics dashboards are increasingly being used to communicate feedback to learners. However, little is known about learner preferences for dashboard designs and how they differ depending on the self-regulated learning (SRL) phases the dashboards are presented (i.e., forethought, performance, and self-reflection phases) and…
Descriptors: Learning Analytics, Experiential Learning, Individualized Instruction, Computer System Design
Serena Lee-Cultura; Kshitij Sharma; Michail N. Giannakos – IEEE Transactions on Learning Technologies, 2024
Teacher dashboards provide insights on students' progress through visualizations and scores derived from data generated during teaching and learning activities (e.g., response times and task correctness) to improve teaching. Despite the potential usefulness of enhancing teacher dashboards, and the respective teaching practices, with rich…
Descriptors: Educational Technology, Learning Analytics, Technology Uses in Education, Student Evaluation
Tenório, Kamilla; Dermeval, Diego; Monteiro, Mateus; Peixoto, Aristoteles; Silva, Alan Pedro da – International Journal of Artificial Intelligence in Education, 2022
There is growing interest in applying gamification to adaptive learning systems to motivate and engage students during the learning process. However, previous studies have reported unexpected results about student outcomes in these systems. One of the causes of these unfavorable effects is the lack of monitoring and adaptation of gamification…
Descriptors: Gamification, Design, Individualized Instruction, Educational Objectives
Vanessa Serrano; Jordi Cuadros; Laura Fernández-Ruano; Javier García-Zubía; Unai Hernández-Jayo; Francesc Lluch – Technology, Knowledge and Learning, 2025
In science and engineering education, remote laboratories are designed to bring ubiquity to experimental scenarios, by having real laboratories operated through the Internet. Despite that remote laboratories enable the collection of students' work data, the educational use of these data is still underdeveloped. Learning analytics dashboards are…
Descriptors: Learning Analytics, Educational Technology, Distance Education, Science Education
Onur Karademir; Daniele Di Mitri; Jan Schneider; Ioana Jivet; Jörn Allmang; Sebastian Gombert; Marcus Kubsch; Knut Neumann; Hendrik Drachsler – Journal of Computer Assisted Learning, 2024
Background: Teacher dashboards can help secondary school teachers manage online learning activities and inform instructional decisions by visualising information about class learning. However, when designing teacher dashboards, it is not trivial to choose which information to display, because not all of the vast amount of information retrieved…
Descriptors: Learning Analytics, Secondary School Teachers, Educational Technology, Design
Warakon Phommanee; Boonrat Plangsorn; Sutithep Siripipattanakul – Contemporary Educational Technology, 2023
Learning experience design (LXD) is a new wave in educational technology and learning design. This study was conducted to clarify conceptual change to practice by applying a systematic literature review to a combination text mining and bibliometric analysis technique to visualization network. Based on the study selection articles from SCOPUS. Our…
Descriptors: Learning Analytics, Learning Experience, Instructional Design, Bibliometrics
Onur Karademir; Lena Borgards; Daniele Di Mitri; Sebastian Strauß; Marcus Kubsch; Markus Brobeil; Adrian Grimm; Sebastian Gombert; Nikol Rummel; Knut Neumann; Hendrik Drachsler – Journal of Learning Analytics, 2024
This paper presents a teacher dashboard intervention study in secondary school practice involving teachers (n = 16) with their classes (n = 22) and students (n = 403). A quasi-experimental treatment-control group design was implemented to compare student learning outcomes between classrooms where teachers did not have access to the dashboard and…
Descriptors: Learning Analytics, Intervention, Educational Technology, Secondary School Students
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
Zeynab Mohseni; Italo Masiello; Rafael M. Martins; Susanna Nordmark – Journal of Learning Analytics, 2024
Visual Learning Analytics (VLA) uses analytics to monitor and assess educational data by combining visual and automated analysis to provide educational explanations. Such tools could aid teachers in primary and secondary schools in making pedagogical decisions, however, the evidence of their effectiveness and benefits is still limited. With this…
Descriptors: Learning Analytics, Visual Learning, Visualization, Intervention
Riordan Alfredo; Vanessa Echeverria; Linxuan Zhao; LuEttaMae Lawrence; Jie Xiang Fan; Lixiang Yan; Xinyu Li; Zachari Swiecki; Dragan Gaševic; Roberto Martinez-Maldonado – Journal of Learning Analytics, 2024
Despite growing interest in applying human-centred design methods to create learning analytics (LA) systems, most efforts have concentrated on initial design phases, with limited exploration of how LA tools and practices can coevolve during the actual learning and teaching activities. This paper examines how a human-centred LA dashboard can be…
Descriptors: Learning Analytics, Learning Management Systems, Artificial Intelligence, Computer Software
Muslim, Arham; Chatti, Mohamed Amine; Schroeder, Ulrik – Technology, Knowledge and Learning, 2022
The demand for Open learning analytics (OLA) has grown in recent years due to the increasing interest in the usage of self-organized, networked, and lifelong learning environments. However, platforms that can deliver an effective and efficient OLA are still lacking. Most OLA platforms currently available do not continuously involve end-users in…
Descriptors: Learning Analytics, Lifelong Learning, Delivery Systems, Ecology
Zhang, Shu; Yi, Jidong; Li, Zijie; Yang, Minghong – International Journal of Information and Communication Technology Education, 2022
In this paper, CiteSpace is used to conduct metrological and visual analysis of the core journals of blended learning research (2003-2021) collected by the China National Knowledge Infrastructure (CNKI). The results show that the number of studies on blended learning in China is increasing year by year, which indicates that the research on blended…
Descriptors: Foreign Countries, Blended Learning, Educational Research, Educational Trends
Zhang, Yuyu; Chan, Kan Kan – Interactive Learning Environments, 2023
Visual analytics (VA) technology has become a significant tool for business decision-makers to explore novel insights. One of its key features is analytical reasoning through interactive visualization that users have direct sensemaking in problem-solving processes. Few studies have examined how VA can be applied in business education for improving…
Descriptors: Visual Aids, Visualization, Learning Analytics, Data Analysis
Alonso-Fernández, Cristina; Calvo-Morata, Antonio; Freire, Manuel; Martínez-Ortiz, Iván; Fernández-Manjón, Baltasar – Journal of Learning Analytics, 2022
Game learning analytics (GLA) comprise the collection, analysis, and visualization of player interactions with serious games. The information gathered from these analytics can help us improve serious games and better understand player actions and strategies, as well as improve player assessment. However, the application of analytics is a complex…
Descriptors: Educational Games, Learning Analytics, Data Collection, Educational Improvement
Prasoon Patidar; Tricia J. Ngoon; Neeharika Vogety; Nikhil Behari; Chris Harrison; John Zimmerman; Amy Ogan; Yuvraj Agarwal – Journal of Learning Analytics, 2024
Classroom sensing systems can capture data on teacher-student behaviours and interactions at a scale far greater than human observers can. These data, translated to multi-modal analytics, can provide meaningful insights to educational stakeholders. However, complex data can be difficult to make sense of. In addition, analyses done on these data…
Descriptors: Learning Analytics, Classroom Observation Techniques, Data Analysis, Student Behavior