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Updated: Jan 7, 2026
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Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes
Published on: June 10, 2021
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Data-Driven Precision Learning: Transforming Adult Education with AI and Analytics
Elissavet Karageorgou1, Styliani Adam1, Spyridon Doukakis1
1Department of Informatics, Bioinformatics and Human Electrophysiology Laboratory, Ionian University, Corfu, Greece.
Advances in Experimental Medicine and Biology
|January 1, 2026
Summary
E-learning, powered by artificial intelligence (AI), enhances adult education through personalized learning and data analytics. Addressing ethical concerns and digital divides is key to its effective implementation for lifelong learning.
Area of Science:
- Educational Technology
- Artificial Intelligence in Education
- Adult Learning
Background:
- Lifelong learning is crucial due to rapid technological change and skill demands.
- E-learning platforms offer accessible, flexible, and personalized educational experiences.
- The COVID-19 pandemic accelerated e-learning adoption, making it central to education.
Purpose of the Study:
- To examine the impact of e-learning on adult education, with a focus on AI-driven personalization and data analytics.
- To explore the potential of data mining in optimizing instructional methods and predicting learning outcomes.
- To propose a framework for precision education integrating multimodal data for enhanced individualized learning.
Main Methods:
- Analysis of AI-driven personalization features in e-learning.
- Investigation of data analytics and data mining techniques in educational contexts.
- Review of national and European policies supporting digital education in Greece.
- Conceptualization of a precision education framework using multimodal data.
Main Results:
- AI and data analytics can significantly enhance e-learning engagement and outcomes.
- E-learning adoption has been accelerated, but infrastructure and digital inequalities remain challenges.
- Data mining offers potential for optimizing teaching and predicting student success.
- A precision education framework can improve individualized learning experiences.
Conclusions:
- AI-powered e-learning presents transformative opportunities for adult education and lifelong learning.
- Ethical considerations, including data privacy and equitable access, are paramount for responsible implementation.
- Inclusive policies and responsible data management are essential for the future of digital education.
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