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Han, Insook; Obeid, Iyad; Greco, Devon – Technology, Knowledge and Learning, 2023
This report describes the use of electroencephalography (EEG) to collect online learners' physiological information. Recent technological advancements allow the unobtrusive collection of live neurosignals while learners are engaged in online activities. In the context of multimodal learning analytics, we discuss the potential use of this new…
Descriptors: Learning Analytics, Diagnostic Tests, Metacognition, Brain Hemisphere Functions
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Murad, Dina Fitria; Murad, Silvia Ayunda; Irsan, Muhamad – Journal of Educators Online, 2023
This study discusses the use of an online learning recommendation system as a smart solution related to changing the face-to-face learning process to online. This study uses user-based collaborative filtering, item-based collaborative filtering, and hybrid collaborative filtering. This research was conducted in two stages using the KNN machine…
Descriptors: Online Courses, Grades (Scholastic), Prediction, Context Effect
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Chun Yan Enoch Sit; Siu-Cheung Kong – Journal of Educational Computing Research, 2024
Educational process mining aims (EPM) to help teachers understand the overall learning process of their students. Although deep learning models have shown promising results in many domains, the event log dataset in many online courses may not be large enough for deep learning models to approximate the probability distribution of students' learning…
Descriptors: Learning Processes, Learning Analytics, Algorithms, Guidelines
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So, Joseph Chi-Ho; Ho, Yik Him; Wong, Adam Ka-Lok; Chan, Henry C. B.; Tsang, Kia Ho-Yin; Chan, Ada Pui-Ling; Wong, Simon Chi-Wang – IEEE Transactions on Learning Technologies, 2023
Generic competence (GC) development is an integral part of higher education to provide holistic education and enhance student career development. It also plays a critical role in complementing the curriculum. Many tertiary institutions provide various GC development activities (GCDA). Moreover, institutions strongly need to further understand…
Descriptors: Predictor Variables, Higher Education, Online Courses, Correlation
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Xia, Xiaona – Interactive Learning Environments, 2023
The interactive learning is a continuous process, which is full of a large number of learning interaction activities. The data generated between learners and learning interaction activities can reflect the online learning behaviors. Through the correlation analysis among learning interaction activities, this paper discusses the potential…
Descriptors: Behavior Patterns, Learning Analytics, Decision Making, Correlation
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Aleksandra Maslennikova; Daniela Rotelli; Anna Monreale – Journal of Learning Analytics, 2023
Students organize and manage their own learning time, choosing when, what, and how to study due to the flexibility of online learning. Each person has unique learning habits that define their behaviours and distinguish them from others. To investigate the temporal behaviour of students in online learning environments, we seek to identify suitable…
Descriptors: Learning Analytics, Online Courses, Time Management, Self Management
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Jamal Eddine Rafiq; Abdelali Zakrani; Mohammed Amraouy; Said Nouh; Abdellah Bennane – Turkish Online Journal of Distance Education, 2025
The emergence of online learning has sparked increased interest in predicting learners' academic performance to enhance teaching effectiveness and personalized learning. In this context, we propose a complex model APPMLT-CBT which aims to predict learners' performance in online learning settings. This systemic model integrates cognitive, social,…
Descriptors: Models, Online Courses, Educational Improvement, Learning Processes
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Ni Li – International Journal of Web-Based Learning and Teaching Technologies, 2025
In depth exploration of how the pandemic has reshaped the education ecosystem over the past three years, especially in the context of the surge in demand for online education courses and learning platforms, this article focuses on the field of student ideological and political education, and innovatively constructs a moral and political education…
Descriptors: Artificial Intelligence, Computer Software, Technology Integration, Algorithms
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Zhongzhou Chen; Tom Zhang; Michelle Taub – Journal of Learning Analytics, 2024
The current study measures the extent to which students' self-regulated learning tactics and learning outcomes change as the result of a deliberate, data-driven improvement in the learning design of mastery-based online learning modules. In the original design, students were required to attempt the assessment once before being allowed to access…
Descriptors: Learning Analytics, Algorithms, Instructional Materials, Course Content
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Robert L. Peach; Sophia N. Yaliraki; David Lefevre; Mauricio Barahona – npj Science of Learning, 2019
The widespread adoption of online courses opens opportunities for analysing learner behaviour and optimising web-based learning adapted to observed usage. Here, we introduce a mathematical framework for the analysis of time-series of online learner engagement, which allows the identification of clusters of learners with similar online temporal…
Descriptors: Learning Analytics, Web Based Instruction, Online Courses, Learner Engagement