Abstract :

The Rapid Growth Of Online Education Platforms Has Resulted In An Overwhelming Volume Of Digital Learning Resources, Courses, Instructors, Discussion Forums, And Assessments. While This Abundance Provides Learners With Numerous Choices, It Also Introduces A Significant Challenge In Identifying Content That Aligns With Individual Learning Goals, Interests, Skill Levels, And Career Aspirations. Traditional Recommendation Systems Used In E-learning Environments Largely Rely On Explicit User Ratings, Course Popularity, Or Basic Demographic Data, Which Often Fail To Capture The Nuanced Preferences And Contextual Learning Needs Of Students. This Research Proposes An Online Students Recommendation System Using Natural Language Processing (NLP) To Intelligently Analyze Unstructured Textual Data Generated By Learners, Such As Course Feedback, Discussion Posts, Assignment Submissions, Search Queries, And Learning Objectives. By Leveraging NLP Techniques Including Tokenization, Sentiment Analysis, Topic Modeling, Word Embeddings, And Semantic Similarity Analysis, The Proposed System Aims To Generate Personalized, Contextaware, And Adaptive Learning Recommendations. The System Processes Both Learner-generated Content And Course Metadata To Understand Semantic Relationships Between Student Interests And Educational Resources. This Approach Enables Dynamic Recommendations That Evolve With The Learner S Progress And Changing Interests. The Proposed NLP-based Recommendation Framework Enhances Learner Engagement, Improves Course Completion Rates, And Supports Informed Decision-making For Students Navigating Large-scale Online Education Platforms. The Research Highlights How Intelligent Text-based Analysis Can Significantly Outperform Conventional Recommendation Mechanisms, Contributing To A More Personalized, Efficient, And Learner-centric Online Education Ecosystem

Published:

01-5-2026

Issue:

Vol. 26 No. 5 (2026)

Page Nos:

30-35

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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