Lifelong learning has become essential in modern society, driven by technological advancements and the increasing demand for continuous skill development. E-learning platforms have transformed education by enhancing accessibility, flexibility, and personalization. Artificial intelligence (AI) and data-driven technologies further refine these platforms, enabling adaptive learning, real-time feedback, and predictive analytics to improve engagement and outcomes. The COVID-19 pandemic accelerated the adoption of e-learning, shifting it from a supplementary tool to a primary mode of education. This study examines the impact of e-learning on adult education, focusing on AI-driven personalization and data analytics. In Greece, national and European policies have facilitated digital education, yet challenges such as infrastructure limitations and digital inequalities persist. Additionally, data mining in e-learning environments has the potential to optimize instructional methods and predict learning outcomes. A proposed framework for precision education integrates multimodal data sources, including biometric indicators, to enhance individualized learning experiences. While AI-powered e-learning systems offer transformative opportunities, ethical concerns surrounding data privacy and equitable access must be addressed. Ensuring responsible data management and inclusive policies will be crucial in maintaining the effectiveness of digital education and fostering lifelong learning in an increasingly technology-driven world.

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Data-Driven Precision Learning: Transforming Adult Education with AI and Analytics

  • Elissavet Karageorgou,
  • Styliani Adam,
  • Spyridon Doukakis,
  • Panagiotis Vlamos

摘要

Lifelong learning has become essential in modern society, driven by technological advancements and the increasing demand for continuous skill development. E-learning platforms have transformed education by enhancing accessibility, flexibility, and personalization. Artificial intelligence (AI) and data-driven technologies further refine these platforms, enabling adaptive learning, real-time feedback, and predictive analytics to improve engagement and outcomes. The COVID-19 pandemic accelerated the adoption of e-learning, shifting it from a supplementary tool to a primary mode of education. This study examines the impact of e-learning on adult education, focusing on AI-driven personalization and data analytics. In Greece, national and European policies have facilitated digital education, yet challenges such as infrastructure limitations and digital inequalities persist. Additionally, data mining in e-learning environments has the potential to optimize instructional methods and predict learning outcomes. A proposed framework for precision education integrates multimodal data sources, including biometric indicators, to enhance individualized learning experiences. While AI-powered e-learning systems offer transformative opportunities, ethical concerns surrounding data privacy and equitable access must be addressed. Ensuring responsible data management and inclusive policies will be crucial in maintaining the effectiveness of digital education and fostering lifelong learning in an increasingly technology-driven world.