JoWUA

Abstract

Despite the remarkable shifts brought about by modern digital education, mobile learning systems are still limited in making students feel immersed in the learning process, limited in dynamic personalization, and lacking in support for real-time multi-sensory interaction. These restrictions limit learning engagement and make it difficult for learners to understand the instructions, especially in complex and spatially intensive subjects. To cope with these challenges, a Holographic Adaptive Learning System (HALS) for mobile devices is proposed, which adapts dynamically and integrates multi-sensory feedback to ensure immersive, real-time, context-aware learning experiences. It is proposed that the system combines holographic visualization, intelligent learner modeling, and edge-assisted processing to provide adaptive content according to cognitive load, attention, and environment. The system constantly observes human interactions and automatically adapts the level of difficulty and sensory feedback (visual, auditory, and haptic) to improve understanding and participation. This adaptive loop provides for personalization and optimization of learning content in real-time, while reducing overload for the learner. Experimental validation shows that HALS improves the performance of a conventional mobile and AR learning system in several performance measures. The accuracy of the proposed system is 93.7%, while the traditional systems and cloud-based adaptive systems are 78.2% and 88.9%, respectively. It also reduces system latency to 98 ms, which is a significant boost in responsiveness when interacting with a system in real time. Moreover, the energy consumption drops by about 35% from AR-based systems, and the user Engagement Scores have been raised to 0.91, which is a high level of interaction. The results of cognitive load analysis indicate that adaptive content modulation is effective in preventing learner overload, with a 55.8% reduction. Overall, the outcome confirms that the holographic approach, together with intelligent and multi-sensory feedback, is highly effective in improving the mobile learning experience. The proposed framework provides a scalable platform for the next generation of educational technologies in ubiquitous mobile environments.