# Development of Digital Training Twins in the Aircraft Maintenance Ecosystem
## 1 Introduction  
The increasing digitalization of aircraft systems and the corresponding shift in aviation maintenance practices have transformed the skill requirements for future technicians. With growing fleets, evolving regulatory frameworks, and the proliferation of data-rich onboard systems, the training environment must adapt to develop highly responsive, context-aware, and audit-ready learning environments. Traditional training methods, including static courseware and generic simulations, often fail to reflect the dynamic operational realities and individualized learning trajectories required for modern aviation maintenance professionals. Recent advancements in immersive simulation [1, 2] and cyber-physical modeling [3, 4] have introduced digital twin concepts into education. However, most implementations to date emphasize system representation rather than learner dynamics or intelligent training orchestration. The potential of digital twins to model not just physical assets but also cognitive development and skill progression remains underutilized, particularly when it comes to applying algorithmic personalization and optimization within regulated training environments. This paper proposes a novel training ecosystem based on the concept of digital training twins (DTTs), which integrates the learner's evolving skill state, the pedagogical logicgoverning scenario progression, and the operational complexity of real-world aircraft systems. Unlike prior digital twin-based educational frameworks, the proposed approach is structured around algorithmic decision-making engines that dynamically adapt learning content, pathway selection, and competence evaluation based on multi-dimensional feedback from virtual training activities. The emergence of digital twin technology has introduced new opportunities for transforming educational methodologies. By enabling learners to interact simultaneously with both physical objects and their digital representations within digital twin-based educational environments, students gain hands-on experience that mirrors real-world contexts, thereby deepening their understanding and enhancing the application of knowledge [5; 6]. However, many existing studies remain at the stage of conceptual frameworks or early implementations, and the widespread practical impact of digital twin adoption in education still requires further validation [7]. To facilitate robust interactivity, learners can employ wearable devices to engage directly with digital twin components or participate as virtual avatars within immersive digital twin educational platforms [8]. This capability supports pervasive, geographically distributed learning and fosters productive team-based collaboration [9]. Despite these advantages, numerous challenges remain in fully integrating digital twin technologies into educational practice while ensuring tangible learning outcomes for students [10]. As computational capabilities continue to advance, research has increasingly focused on developing digital twin educational environments and instructional support systems [11]. Such developments include the creation of intelligent digital twin learning spaces [12], digital twin systems for education [13], and immersive architectural prototype twin environments [14]. Through real-time interaction, integration of virtual and physical learning elements, and dynamic system adaptability, digital twin technologies provide learners with flexible environments where materials can be observed, manipulated, tested, and iteratively refined [15]. The evolution of cognitive digital twins [16] and digital-twin-supported instructional systems [17] has further enabled personalized learning strategies and adaptive educational designs that respond continuously to learners' progress, improving both instructional quality and learning outcomes. In aviation, digital twin technology is being actively explored across multiple domains.