A proposed AI/ML algorithm for optimizing the selection of educational resources

Interactive Technology and Smart Education 2026

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Authors: Amin H. Al Ka'bi, Khaled AbuJbara, Hamzeh Aljarajreh, Kais Al-Abdullah, Reem T. Akasha
DOI: 10.1108/itse-07-2025-0203
Cited by: 0
References: 21

Abstract

Purpose This paper aims to propose an AI/AL Bi-LSTM algorithm with Feature Weighting (FW) model to optimize educational resource recommendations. It addresses challenges like data sparsity, information loss and inefficient filtering in online learning platforms. The model integrates channel awareness and compressed interactive networks to refine data, assign feature weights and enhance relevance. Validated on Tencent Classroom, it achieves 98% categorization accuracy,

Fields of Study & Subjects

Recommender Systems and Techniques Online Learning and Analytics Artificial Intelligence in Education

Publication details

Journal / source
Interactive Technology and Smart Education
Volume
23
Issue
3
Pages
497–513
Publication date
29 January 2026
Language
EN