Advancing NATO’s quality assurance education by implementing the ‘learn-watch-ask’ training model

Abstract

The paper introduces a detailed analysis and a method of implementing the “Learn-Watch-Ask” (LWA) training model, as a potential solution, to enhance quality assurance training within NATO. By addressing the fast-evolving demands of specialized domains, the LWA model integrates digital tools with traditional teaching methods to create a learning experience that is responsive to the student`s needs. The model is comprised of three interdependent components: the Learn module, represented by a structured online course; the Watch module, supported by a specialized YouTube channel for enhanced visual understanding; and the Ask module, created with an AI-driven chatbot for interactive learning. This innovative approach supports diverse learning styles, offering 24/7 accessibility and effectiveness. The paper further digs deeper into the identified shortcomings of traditional training models, emphasizing the need for practical, visual, and interactive elements in modern education. It explores the integration of the IBM WatsonX Assistant as a conversational AI chatbot in the LWA model, highlighting its advantages in providing consistent, accurate, and user-friendly interactions over Generative Pre-trained Transformer (GPT) AI models. Additionally, a 7-step process for adapting the LWA model to various domains is outlined, as well as the description of a comprehensive continuous improvement loop for the IBM WatsonX Assistant, ensuring its relevance and efficiency in the rapidly evolving educational landscape. The LWA model, with its unique approach to modern educational techniques, not only enhances the learning experience for NATO’s Quality Assurance Course (S7-137) but also has the potential to be adapted across various specialized domains, promising a more effective and efficient workforce.