Design of Multimedia Education and Teaching Management System based on Artificial Intelligence and Computational Technology

Abstract

The multimedia education and teaching management system’s capacity to confront significant issues faced by conventional education systems is the fundamental justification for its relevance and significance. It is necessary to efficiently manage educational resources, accommodate to a variety of learning styles, and meet the expectations for highly personalised educational experiences. The system’s goal, enabled by artificial intelligence (AI), is to build a classroom that is more adaptable to each student’s individual requirements and interests. Personalised learning, efficient use of resources, and the ability to scale are common challenges faced by conventional educational institutions. Additionally, having scalable computing methods is crucial for making certain the system can handle different user needs and adapt to different classroom environments. The Intelligent Multimedia Teaching Tracking System (IMTTS) combines AI-based algorithms to track student interactions and enhance the transmission efficiency of multimedia content. Besides providing insights that teachers may put into practice, the system additionally provides a personalised learning route that is based on each student’s performance and preferences. The deployment of scalable computing ensures that the system can effectively handle large datasets and a large number of users under heavy load. A thorough simulation analysis is conducted to ascertain the effectiveness and productivity of the IMTTS. The analysis shows that the system can change educational management by providing reliable solutions that address present issues and meet evolving educational needs. Furthermore, it highlights the system’s capacity to handle compute needs that scale.