Measuring the Importance of Smart E-learning education system

Abstract

Advances in information technology facilitate new (or improved) educational and training practices, creating opportunities for new methods and tools; while also, these technologies are changing the educational paradigm. In the past, smart education frameworks were mostly qualitative studies, describing the conceptual framework (and its connotations) of smart educational systems. Although these conceptually structured smart education systems can promote student learning, peer and teacher interaction, and teaching practice, which assist in understanding students’ status and needs in multiple ways and providing students with real-time synchronous/asynchronous guidance and help, unfortunately, many qualitative studies in the past still lack quantitative data to verify the priority of E-Education planning. The experts surveyed by AHP in this article are selected from E-learning and information technology, with a total of 14 people. The results from the software, Expert Choice, found that in the planning of the smart education system, the importance order of the main criteria, from the most important to the least were smart classroom function, technology-based learning system (IoT, Metaverse), teaching monitoring system, conceptual elements of smart learning, respectively. The sub-criteria weight values showed the key factors of E-Learning Education Planning, which in order were educational resources optimization, teaching is differentiated from person to person, students’ cooperation learning, course completion rate, reliable wireless connection (Wi-Fi, IoT apps, Wearable technology). Finally, the least important were smart pedagogies based on learning theory, learning attention detection, and system data backup. In terms of contribution, to our knowledge, very few studies have used the AHP model and hierarchical design method presenting in the current research to quantitatively demonstrate smart education planning and lecture design, to identify and verify the feasibility model of smart education.