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Showing all 11 results Save | Export
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Xia, Xiaona; Qi, Wanxue – Education and Information Technologies, 2023
MOOCs might be an important organization way to realize the online learning process. Online technology and sharing technology enable MOOCs to realize the adaptive scheduling of learning resources, as well as the independent construction of learning sequences. At the same time, it also generates a large number of complex learning behaviors. How to…
Descriptors: MOOCs, Learning Processes, Learning Analytics, Graphs
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Fan, Yizhou; Tan, Yuanru; Rakovic, Mladen; Wang, Yeyu; Cai, Zhiqiang; Shaffer, David Williamson; Gaševic, Dragan – Journal of Computer Assisted Learning, 2023
Background: Select and enact appropriate learning tactics that advance learning has been considered a critical set of skills to successfully complete highly flexible online courses, such as Massive open online courses (MOOCs). However, limited by analytic methods that have been used in the past, such as frequency distribution, sequence mining and…
Descriptors: MOOCs, Students, Learning Processes, Learning Strategies
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Xia, Xiaona; Qi, Wanxue – International Journal of Educational Technology in Higher Education, 2023
The temporal sequence of learning behavior is multidimensional and continuous in MOOCs. On the one hand, it supports personalized learning methods, achieves flexible time and space. On the other hand, it also makes MOOCs produce a large number of dropouts and incomplete learning behaviors. Dropout prediction and decision feedback have become an…
Descriptors: MOOCs, Dropouts, Prediction, Decision Making
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Xiaona Xia; Wanxue Qi – European Journal of Education, 2025
Massive Open Online Courses (MOOCs) effectively support online learning behaviour; while constructing a sustainable learning process, MOOCs have also formed the social network. In addition, learners' burnout state has become a serious obstacle to the development and promotion of MOOCs. This study analyzes the potential social behaviour associated…
Descriptors: MOOCs, Burnout, Social Behavior, Feedback (Response)
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Olga Agatova; Alexander Popov; Suad Abdalkareem Alwaely – Interactive Learning Environments, 2024
The paper examines the special aspects of using Big Data technology in education. The population was made up of 356 third-year university students. To study Big Data technology, a questionnaire was used where respondents rated: cloud technology; apps; Massive Open Online Courses (MOOCs) and digital learning platforms. The study suggested that the…
Descriptors: Data Use, Learning Processes, Technology Uses in Education, Information Storage
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John Stamper; Steven Moore; Carolyn P. Rosé; Philip I. Pavlik Jr.; Kenneth Koedinger – Journal of Educational Data Mining, 2024
LearnSphere is a web-based data infrastructure designed to transform scientific discovery and innovation in education. It supports learning researchers in addressing a broad range of issues including cognitive, social, and motivational factors in learning, educational content analysis, and educational technology innovation. LearnSphere integrates…
Descriptors: Learning Analytics, Web Sites, Data Use, Educational Technology
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Karmijn van de Oudeweetering; Jeremy Knox; Mathias Decuypere – Learning, Media and Technology, 2024
This paper examines the enactment of feedback in Massive Open Online Courses (MOOCs), focusing on analytics dashboards. Building on scholarship that recognizes data practices as entangled and 'messy', the paper problematizes the model of the feedback loop that assumes that analytics dashboards 'feed back' data to instructors and/or learners…
Descriptors: MOOCs, Learning Analytics, Instructional Design, Student Role
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Švábenský, Valdemar; Baker, Ryan S.; Zambrano, Andrés; Zou, Yishan; Slater, Stefan – International Educational Data Mining Society, 2023
Students who take an online course, such as a MOOC, use the course's discussion forum to ask questions or reach out to instructors when encountering an issue. However, reading and responding to students' questions is difficult to scale because of the time needed to consider each message. As a result, critical issues may be left unresolved, and…
Descriptors: Generalization, Computer Mediated Communication, MOOCs, State Universities
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Zeng, Shuang; Zhang, Jingjing; Gao, Ming; Xu, Kate M.; Zhang, Jiang – Computer Assisted Language Learning, 2022
Learning analytics (LA) has the potential to generate new insights into the complexities of learning behaviours in language massive open online courses (LMOOCs). In LA, the collective attention model takes an ecological system view of the dynamic process of unequal participation patterns in online and flexible learning environments. In this study,…
Descriptors: Learning Analytics, MOOCs, Oral Language, English (Second Language)
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Abdulkadir Palanci; Rabia Meryem Yilmaz; Zeynep Turan – Education and Information Technologies, 2024
This study aims to reveal the main trends and findings of the studies examining the use of learning analytics in distance education. For this purpose, journal articles indexed in the SSCI index in the Web of Science database were reviewed, and a total of 400 journal articles were analysed within the scope of this study. The systematic review…
Descriptors: Learning Analytics, Distance Education, Educational Trends, Periodicals
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Azhar, Aqil Zainal; Segal, Avi; Gal, Kobi – International Educational Data Mining Society, 2022
This paper studies the use of Reinforcement Learning (RL) policies for optimizing the sequencing of online learning materials to students. Our approach provides an end to end pipeline for automatically deriving and evaluating robust representations of students' interactions and policies for content sequencing in online educational settings. We…
Descriptors: Reinforcement, Instructional Materials, Learning Analytics, Policy Analysis