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Enhancing Educational Outcomes Through Learning Pathways and Artificial Intelligence-Driven Learning Analytics

  • Martin Trommer,
  • Susanne Franke,
  • Tobias Teich,
  • Ralph Riedel,
  • Sven Hellbach,
  • Daniel Franke

摘要

This paper explores the implementation of personalized learning pathways using Learning Analytics to enhance educational quality. It addresses the challenges posed by learner heterogeneity, varying learning speeds, and different learning styles, emphasizing the need for individualized learning approaches to optimize learning outcomes. Especially in the context of e-learning, the integration of Learning Analytics and Artificial Intelligence (AI) allows enhancing educational quality through the definition and dynamic adaption of learning pathways. This is achieved by adapting learning content, questions and difficulty levels in real-time based on the students’ performance and behaviors. The paper includes the design of a platform architecture for data acquisition, preparation, and utilization in dynamically adjusting course content.