RECAP: Rapid Educational Content Automation Platform Using Multimodal Large Language Models

This effort aims to develop RECAP, an AI-enabled, human-in-the-loop system designed to modernize legacy Marine Corps training content by transforming static instructional material into interactive, modular e-learning experiences. RECAP Leverages large language models (LLMs) such as GPT-4 and orchestration frameworks like LangChain to accelerate content conversion while preserving instructional integrity and enabling expert oversight. The system automates the generation of quizzes, decision-making exercises, and troubleshooting scenarios, all directly aligned with learning objectives extracted from authentic Marine Corps training documents.áBy incorporating prompt engineering templates and user-guided workflows, RECAP reduces the cognitive burden on instructional designers and addresses the common challenge of ôblank slateö hesitation. Early prototypes will demonstrate RECAPĺs ability to produce coherent course outlines with defined constraints, such as topic, duration, and learner level. Emphasizing a human-in-the-loop model, RECAP allows subject matter experts to iteratively review and refine AI-generated content to ensure operational relevance and pedagogical soundness. Ultimately, RECAP supports the rapid delivery of scalable, adaptive digital training solutions to meet the evolving educational needs for the Marine Corps.