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International Conference on Education Data Analytics and Learning Systems

3rd Nov – 4th Nov 2026 Perth, Australia Standard / Physical Participation
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Conference Session Tracks
SDG Wheel

SDG-Aligned Research Themes

International Conference on Education Data Analytics and Learning Systems conference tracks support global knowledge exchange, innovation, and sustainable development priorities across diverse disciplines.

SDG 4 - Quality Education SDG 8 - Decent Work and Economic Growth SDG 9 - Industry, Innovation and Infrastructure SDG 10 - Reduced Inequalities

This track focuses on the latest methodologies and technologies in education analytics. Researchers are invited to present their findings on how data-driven approaches can enhance educational outcomes.

This session will explore the application of predictive modeling techniques to forecast student performance and engagement. Contributions should highlight innovative models that inform decision-making in educational contexts.

This track examines the role of adaptive learning systems in personalizing educational experiences. Papers should discuss the integration of data analytics to tailor learning pathways for diverse student populations.

This session invites contributions that utilize data visualization techniques to communicate complex educational data effectively. The focus will be on how visual tools can enhance understanding and drive actionable insights in learning environments.

This track will highlight the use of machine learning algorithms to analyze educational data. Researchers are encouraged to share case studies that demonstrate the impact of these technologies on learning outcomes.

This session will delve into the analytics of assessment data to improve student performance metrics. Papers should explore innovative approaches to evaluating and enhancing assessment strategies through data analysis.

This track focuses on the optimization of educational curricula using data analytics. Contributions should address how data can inform curriculum design and improve alignment with student needs and industry demands.

This session examines the integration of data analytics within Learning Management Systems (LMS). Researchers are invited to discuss the implications of data integration for enhancing user experience and educational effectiveness.

This track will explore the analytics of student engagement in e-learning environments. Papers should focus on strategies to measure and enhance engagement through data-driven insights.

This session will investigate the role of cloud analytics in transforming education technology. Contributions should highlight how cloud-based solutions can facilitate data analysis and improve educational practices.

This track focuses on the strategies for effective knowledge management within educational institutions. Researchers are encouraged to present frameworks that leverage data analytics to enhance knowledge sharing and collaboration.

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