The Republic of Korea Armed Forces are implementing various scientific training systems to prepare for future warfare and are seeking advanced integration with AI - driven scientific military innovation. This study proposes the Synthetic Training Environment (STE) as a future-oriented model designed to overcome current limitations in military training. STE provides the foundation for evolving into an integrated, combined arms training system. In addition, the study introduces a data integration framework based on the Defense Training Management System (DTMS). This framework aims to standardize and unify training data across service branches, thereby enabling effective AI interoperability. Future tasks include real-time integration of synthetic and live training, 24/7 data access via the Metaverse, and the establishment of a cyclic system of learning, operation, and evolution. To that end, this research ultimately proposes the CJDSW-MST model - a comprehensive framework linking STE, DTMS, and unmanned combat systems for future-ready, intelligent military training.

1. 서 론
    1.1 연구 배경 및 목적
    1.2 연구 범위 및 방법
2. 이론적 논의 및 분석의 틀
3. 현 실태 진단
    3.1 과학화훈련체계(시뮬레이터) 진단
    3.2 군(軍) 데이터 활용성 진단
4. 미래 과학화훈련과 데이터 융합체계 구축
    4.1 메타버스형 협동훈련체계( STE )
    4.2 데이터 융합체계
    4.3. ‘미래 유․무인복합전투체계’와의 연동방안
5. CJDSW-MST 모델 정립
6. 연구성과 및 시사점
References

• Seongjong Kim(Department of Military Science, Konyang University) | 김성종 (건양대학교 군사학과)
• Myoungjin Choi(Department of Military Science, Konyang University) | 최명진 (건양대학교 군사학과) Corresponding author