Volume 9 • Issue 2 • PP: 28-36 • 2024
An Adaptive Optimization Algorithm for Personalized Learning Pathways in E-Learning
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This paper presents an adaptive optimization algorithm for personalized learning pathways in e-learning environments. The proposed algorithm dynamically adjusts the learning path for each student based on their performance, preferences, and learning behavior. By integrating machine learning techniques with a rule-based system, the algorithm optimizes content delivery and ensures a tailored learning experience that aligns with individual needs. The system continuously monitors learners’ progress, adapts to their evolving knowledge levels, and suggests the most relevant resources and activities to enhance engagement and comprehension. Experimental results demonstrate significant improvements in learning outcomes, reduced time to completion, and enhanced user satisfaction, making the approach a promising solution for personalized e-learning systems.
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References
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