Authors : Navin Kumar Sehgal

Volume/Issue : Volume 10 - 2025, Issue 12 - December

Google Scholar : https://tinyurl.com/2htvkw5h

Scribd : https://tinyurl.com/me6t3c76

DOI : https://doi.org/10.38124/ijisrt/25dec961

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Abstract : This study proposes an integrated Intelligent Learning Platform that combines recommendation algorithms, learner interaction analysis, collaboration mechanisms, and continuous performance feedback to deliver adaptive and personalized learning experiences. The platform addresses limitations in existing digital learning environments where recommendation, analytics, and feedback systems typically operate in isolation, reducing their effectiveness in supporting diverse learners. The proposed method unifies these components within a continuous improvement loop: a hybrid recommendation engine generates personalized learning pathways; an interaction analyzer captures behavioral signals such as navigation patterns, quiz attempts, and engagement levels; a collaboration engine recommends peer and tutor support; and a performance analyzer updates learner mastery estimates to refine future recommendations. To evaluate system efficiency, the study uses a real educational dataset and applies machine-learning models to predict learner adaptability, achieving high accuracy and low RMSE. Analysis further illustrates how contextual factors—such as device type, internet quality, and class duration tolerance—inform adaptive pathway selection. These results demonstrate that integrating recommendation logic with behavioral analytics and performance-driven feedback significantly enhances personalization and decision quality in learning systems. The findings provide evidence for a unified, data-driven framework capable of improving learner support, optimizing content sequencing, and enabling more responsive and engaging online education environments.

Keywords : Intelligent Learning Systems, Educational Recommender Systems, Adaptive Learning, Interaction Analytics, Collaborative Learning, Performance Feedback, Learning Pathway Personalization, Learning Analytics, Context-Aware Recommendation, Online Education.

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