Title: Case-based reasoning methodology for eLearning recommendation system

Authors: Swati Shekapure; Dipti D. Patil

Addresses: Department of Computer Engineering, Marathwada Mitra Mandal's College of Engineering, Pune, Maharashtra – 411052, India ' Department of Information Technology, MKSSS's Cummins College of Engineering for Women, Pune, Maharashtra – 411052, India

Abstract: Increasingly, eLearning has become a leading development trend in the industry. It has been observed that traditional learning methods have turned to modern and innovative learning. Due to a revolution in technology, everyone started learning by using the internet. They have been using online material for gaining instructions. So, while they procure the learning they admit certain records, which are not significant to answer all their exploratory questions. Ultimately, there was a huge delay while scrutinising the essential material on the internet, so there was an extremity to customise the search by acquiring certain information of a user to improve the search quality and save time. The recommended eLearning system is a case based system using a case-based reasoning approach and a distinct classification algorithmic rule to categorise the students' learning interest. This system assembles student's learning preferences from a distinct discussion and systematically categorises that characteristic into a learning standard.

Keywords: adaptive system; case-based reasoning; case-based library; eLearning; K nearest neighbour; learning style; learning objects; learning path; recommendation system; retrieval process.

DOI: 10.1504/IJAIP.2025.144976

International Journal of Advanced Intelligence Paradigms, 2025 Vol.30 No.1, pp.22 - 35

Received: 15 Jun 2019
Accepted: 15 Feb 2020
Published online: 17 Mar 2025 *

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