Determinant Factors of Edge Intelligence System Performance in E-learning: An Advanced Analysis Using Multilayer Perceptron Artificial Neural Networks

Abstract

The rapid adoption of e-learning in higher education has accelerated the integration of edge intelligence technologies to support intelligent, real-time, and adaptive learning environments. Ensuring the performance and effectiveness of edge intelligence systems has therefore become critical for delivering reliable, secure, and high-quality digital learning experiences. This study investigates the key determinants influencing the performance of edge intelligence systems within e-learning environments, focusing on three core dimensions: computational efficiency, security and trustworthiness, and system resilience. A multilayer perceptron (MLP) artificial neural network is employed to model the complex, nonlinear relationships among these dimensions and evaluate their collective impact on the overall performance of edge-enabled e-learning systems. Although previous studies have extensively examined edge computing and artificial intelligence independently, limited attention has been given to the simultaneous effects of computational, security, and resilience factors on the operational performance of edge intelligence in e-learning contexts. This study addresses this research gap by providing a comprehensive analysis of these determinant factors and generating practical insights for the design and optimization of robust, secure, and efficient edge intelligence infrastructures that support digital education. The findings offer valuable implications for system developers, educational institutions, and policymakers in improving resource allocation, strengthening system reliability, and implementing strategic interventions that enhance the quality and sustainability of edge-enabled e-learning services. By systematically examining computational efficiency, security and trustworthiness, and system resilience, this research contributes to advancing scalable, resilient, and learner-centered edge intelligence solutions that improve educational effectiveness and support the digital transformation of higher education.