AI Based Course Suggestion Portfolio

The rapid expansion of online education platforms has fundamentally changed the way students engage with learning opportunities. Students now have access to a vast array of courses, offered by different institutions, in various fields of study, and at different levels. [1] However, with such an overwhelming selection, choosing the right courses that align with a student's academic path, interests, and career aspirations can be a daunting task. Traditional course recommendation systems, which have relied on simple rule-based or manual methods, often fall short of addressing the diverse and evolving needs of modern learners. [5] To solve these challenges, this paper proposes the development of an AI-powered course suggestion system that adapts to the individual needs of each student by using advanced machine learning techniques. Unlike traditional systems, which are confined to static rules or rigid structures, the AI-based system is designed to learn from each student's behaviour, interactions, and academic profile to offer personalized course recommendations that evolve over time.

Authors

Publication Details

Journal
International Journal of Innovative Research in Advanced Engineering
Published
2024-12-13
DOI
https://doi.org/10.26562/ijirae.2024.v1112.03
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
0.00
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AI Based Course Suggestion Portfolio

Dipansu Sahu, Pawan Mishra, Ritik Raushan, Sanskriti Singh et al.
International Journal of Innovative Research in Advanced Engineering
Online Learning and Analytics
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AI Based Course Suggestion Portfolio

Dipansu Sahu, Pawan Mishra, Ritik Raushan, Sanskriti Singh, Dr.Vikas Singhal, Swati Kumari
article en

Abstract

The rapid expansion of online education platforms has fundamentally changed the way students engage with learning opportunities. Students now have access to a vast array of courses, offered by different institutions, in various fields of study, and at different levels. [1] However, with such an overwhelming selection, choosing the right courses that align with a student's academic path, interests, and career aspirations can be a daunting task. Traditional course recommendation systems, which have relied on simple rule-based or manual methods, often fall short of addressing the diverse and evolving needs of modern learners. [5] To solve these challenges, this paper proposes the development of an AI-powered course suggestion system that adapts to the individual needs of each student by using advanced machine learning techniques. Unlike traditional systems, which are confined to static rules or rigid structures, the AI-based system is designed to learn from each student's behaviour, interactions, and academic profile to offer personalized course recommendations that evolve over time.

International Journal of Innovative Research in Advanced EngineeringVol. 11(12)
Quality Education
Openalex Percentile: Top 75%
Online Learning and Analytics
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