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Khalid Alalawi; Rukshan Athauda; Raymond Chiong – International Journal of Artificial Intelligence in Education, 2025
The use of educational data mining and machine learning to analyse large data sets collected by educational institutions has the potential to discover valuable insights for decision-making. One such area that has gained attention is to predict student performance by analysing large educational data sets. In the relevant literature, many studies…
Descriptors: Learning Analytics, Technology Integration, Electronic Learning, Educational Practices
Nedime Selin Çöpgeven; Mehmet Firat – Journal of Educators Online, 2024
Learning processes can now be transferred to digital environments, allowing for the tracking of learners' digital footprints. The field of learning analytics focuses on the efficient use of these digital records to improve both learning experiences and processes. Dashboards are the tangible outputs of learning analytics. The use of dashboards in…
Descriptors: Electronic Learning, Distance Education, Academic Achievement, Educational Technology
Zhennan Sun; Mingyong Pang; Yi Zhang – Education and Information Technologies, 2025
The evolution of individual and global learning preferences is influenced by correlation factors. This study introduces a novel evolutionary modeling approach to observe and analyze factors that affect the evolution of learning preferences. The influencing factors considered in this study are closely interwoven with the underlying personality of…
Descriptors: Learning Analytics, Learning Processes, Preferences, Student Characteristics
Golnaz Arastoopour Irgens; Ibrahim Oluwajoba Adisa; Deepika Sistla; Tolulope Famaye; Cinamon Bailey; Atefeh Behboudi; Adenike Omalara Adefisayo – International Educational Data Mining Society, 2024
Although the fields of educational data mining and learning analytics have grown significantly in terms of analytical sophistication and the breadth of applications, the impact on theory-building has been limited. To move these fields forward, studies should not only be driven by learning theories, but should also use analytics to in form and…
Descriptors: Learning Theories, Learning Analytics, Electronic Learning, Elementary School Students
Christothea Herodotou; Sagun Shrestha; Catherine Comfort; Heshan Andrews; Paul Mulholland; Vaclav Bayer; Claire Maguire; John Lee; Miriam Fernandez – Journal of Learning Analytics, 2025
In this paper, we explore the design of a student-facing dashboard for online and distance learning with a focus on capturing and addressing specific learning needs. A participatory process involving 20 students was employed, which included a screening questionnaire and focus group discussions. The selection of data points to be displayed on the…
Descriptors: Electronic Learning, Distance Education, Student Attitudes, Educational Technology
Oleksandra Poquet; Sven Trenholm; Marc Santolini – Educational Technology Research and Development, 2024
Interpersonal online interactions are key to digital learning pedagogies and student experiences. Researchers use learner log and text data collected by technologies that mediate learner interactions online to provide indicators about interpersonal interactions. However, analytical approaches used to derive these indicators face conceptual,…
Descriptors: Computer Mediated Communication, Interpersonal Communication, Online Courses, Discussion
Raymond A. Opoku; Bo Pei; Wanli Xing – Journal of Learning Analytics, 2025
While high-accuracy machine learning (ML) models for predicting student learning performance have been widely explored, their deployment in real educational settings can lead to unintended harm if the predictions are biased. This study systematically examines the trade-offs between prediction accuracy and fairness in ML models trained on the…
Descriptors: Prediction, Accuracy, Electronic Learning, Artificial Intelligence
Yiming Liu; Lingyun Huang; Tenzin Doleck – Education and Information Technologies, 2024
Learning analytics dashboards (LADs) are emerging tools that convert abstract, complex information with visualizations to facilitate teachers' data-driven pedagogical decision-making. While many LADs have been designed, teachers' capacities for using such LADs are not well articulated in the literature. To fill the gap, this study provided a…
Descriptors: Learning Analytics, Teacher Attitudes, Self Management, Psychological Patterns
Fischer, Gerhard; Lundin, Johan; Lindberg, Ola J. – International Journal of Information and Learning Technology, 2023
Purpose: The main argument behind this paper is learning in the digital age should not be restricted to creating digital infrastructures for supporting current forms of learning nor taking schools in their current form as God-given, natural entities, but changing current forms of education by developing new frameworks and socio-technical…
Descriptors: Electronic Learning, Lifelong Learning, Transformative Learning, Educational Change
Anuradha Peramunugamage; Uditha W. Ratnayake; Shironica P. Karunanayaka; Ellen Francine Barbosa; William Simão de Deus; Chulantha L. Jayawardena; R. K. J. de Silva – Journal of Learning for Development, 2025
Interactions among students in online learning environments are difficult to monitor but can be crucial for their academic performance. Moodle is one of the best and most popular online learning platforms, where its log records can reveal important information on students' engagement and the respective performance. This study examines the degree…
Descriptors: Cooperative Learning, Interaction, Electronic Learning, Learning Management Systems
Liu, Lingyan; Zhao, Bo; Rao, Yiqiang – International Journal of Information and Communication Technology Education, 2022
A lot of studies have shown that there is an "inverse U-curve" relationship between learners' grades and cognitive load. Learners' grades are closely related to their learning behavior characteristics on online learning. Is there any relationship between online learners' behavior characteristics and cognitive load? Based on this, the…
Descriptors: Cognitive Processes, Difficulty Level, Learning Analytics, Electronic Learning
Eamon Vale; Garry Falloon – Online Learning, 2024
This research investigated the potential of learning analytics (LA) as a tool for identifying and evaluating K-12 student behaviors associated with active learning when using video learning objects within an online learning environment (OLE). The study focused on the application of LA for evaluating K-12 student engagement in videobased…
Descriptors: Learning Analytics, Elementary School Students, Secondary School Teachers, Electronic Learning
Xinyu Li; Yizhou Fan; Tongguang Li; Mladen Rakovic; Shaveen Singh; Joep van der Graaf; Lyn Lim; Johanna Moore; Inge Molenaar; Maria Bannert; Dragan Gaševic – Journal of Learning Analytics, 2025
The focus of education is increasingly on learners' ability to regulate their own learning within technology-enhanced learning environments. Prior research has shown that self-regulated learning (SRL) leads to better learning performance. However, many learners struggle to productively self-regulate their learning, as they typically need to…
Descriptors: Learning Analytics, Metacognition, Independent Study, Skill Development
Elissavet Papageorgiou; Jacqueline Wong; Mohammad Khalil; Annoesjka J. Cabo – Journal of Learning Analytics, 2025
Behavioural engagement as a predictor of academic success hinges on the interplay between effort and time. Exploring the longitudinal development of engagement is vital for understanding adaptations in learning behaviour and informing educational interventions. However, person-oriented longitudinal studies on student engagement are scarce.…
Descriptors: Learner Engagement, Student Behavior, Electronic Learning, Web Based Instruction
Badal, Yudish Teshal; Sungkur, Roopesh Kevin – Education and Information Technologies, 2023
The outbreak of COVID-19 has caused significant disruption in all sectors and industries around the world. To tackle the spread of the novel coronavirus, the learning process and the modes of delivery had to be altered. Most courses are delivered traditionally with face-to-face or a blended approach through online learning platforms. In addition,…
Descriptors: Prediction, Models, Learning Analytics, Grades (Scholastic)

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