AI-Driven Interactive Multimedia Courseware: A Web- and Mobile-Responsive Platform for IT Specialist Certification Exam Preparation with an Adaptive Learning Algorithm

Abstract

This study designed, developed, and evaluated an AI-driven interactive multimedia courseware to support preparation for the IT Specialist (ITS) certification examination. Traditional review approaches often lack adaptive learning mechanisms and interactive resources, limiting their effectiveness in addressing diverse learner needs and tracking learning progress. To address this gap, the study employed a Design and Development Research (DDR) methodology guided by Agile Software Development Life Cycle principles. The development process began with the systematic identification of ITS exam objectives and topics based on official certification guidelines, which served as the foundation for the instructional design and content organization of the courseware. The system was implemented as a web- and mobile-responsive platform featuring multimedia lessons, interactive simulations, gamified activities, and practice examinations to promote active learning. The Bayesian Knowledge Tracing (BKT) algorithm was integrated as the adaptive learning engine to dynamically estimate learner knowledge states and personalize content delivery based on performance and progress. The developed system was evaluated by five IT experts and twenty prospective ITS examinees using the ISO/IEC 25010 software quality model. Results showed consistently high ratings across all criteria, with an overall weighted mean of 4.59 (“Strongly Agree”). These findings suggest that adaptive multimedia courseware can enhance certification readiness and provide institutions with an effective digital platform for technology-based exam preparation.