ADAPTIVE LEARNING SYSTEMS FOR MULTIMEDIA DESIGN EDUCATION

Abstract

Multimedia design education is currently changing at a fast pace due to the rapid development of digital technologies, which require a more personalized and flexible learning environment. The old model of teaching does not usually recognize any differences in learning between individuals in terms of speed, manner and understanding. The promising alternative offered by adaptive learning systems (ALS) is the idea that the instructional material will be customized and designed to meet the needs of a particular learner through the use of artificial intelligence, data analytics, and real-time feedback. This paper examines the construction and deployment of an adaptive learning system that is created specifically to serve as an education of multimedia design. The system architecture incorporates the following important technologies: Learning Management Systems (LMS), adaptive learning engines, and AI-driven analytics, which can evaluate the performance of the learners and dynamically modify the content. This study determines concepts of adaptive learning based on the depth of literature review, which identifies the basic building blocks and overall theoretical basis of the concept, and how such building blocks apply to multimedia education. The system architecture suggested is in line with the multimedia design curriculum in that it makes interactive learning, visual learning, and project-based learning easy. One case study on the performance of a system is carried out among a group of undergraduate design students, where the system is tested based on engagement, usability, and learning outcomes. The results have shown that adaptive learning is very important to student motivation, understanding the concepts and abilities to solve problems creatively as compared to the conventional classroom methods.