Natural Inspired Learning Path Recommendation System for Students in E-learning Platforms

Abstract: E-learning has emerged as one of the advanced and efficient methods of education, especially during the ongoing pandemic. While many learning platforms have integrated recommender systems to aid learners in understanding and improving their skills, it has been observed that this approach alone may not be sufficient for optimal learning outcomes. Therefore, this paper proposes a unique method and algorithm inspired by bird swarms to recommend an efficient learning path for learners. The effectiveness of the proposed model was evaluated using nearly three hundred and ninety-five student records, and qualitative evaluation metrics were used to assess its performance. Keywords: E-learning, Nature-inspired algorithms, Recommendation systems, Migrating birds optimization.