Implementing advanced distribited learning : A case study from Vigorous Warrior 2024 and Clean Care 2024 excercises

Absztrakt

Multinational military exercises inherently bring together participants with diverse backgrounds, experience levels, and knowledge bases, creating challenges in achieving uniform preparedness. The pre-training phase plays a critical role in equipping participants for effective engagement in these exercises. Furthermore, the evolving nature of military operations—characterized by increasing multinational collaboration and operational complexity—necessitates innovative training approaches, rapid skill acquisition, and adaptability.1 Integrating Advanced Distributed Learning (ADL) into multinational exercises represents a critical step in meeting these demands.2 This case study focuses on the implementation of ADL in the Vigorous Warrior 2024 and Clean Care 2024 (VW24/CC24) joint multinational exercises. For the first time, these exercises incorporated an eLearning platform to support pre-training requirements and serve as an asset during and after the exercise. Designed to cater to both the Training Audience (TA) and Exercise Control (EXCON), the platform was accessible to civilian and military participants alike. The authors present key lessons identified from the operational integration of ADL into VW24/CC24 and analyze its impact on the exercises. The study also highlights insights derived from learning analytics, including data collected from eLearning courses, illustrating the potential of ADL to enhance preparedness, streamline training, and support knowledge retention in complex multinational contexts.