基于CDIO-OBE理念的人工智能赋能侦查学实践教学

Artificial‑Intelligence‑Empowered Practical Teaching of Criminal Investigation Based on the CDIO‑OBE Concept

摘要: 提升人工智能智能在侦查学课程教学体系中应用，推动侦查学拔尖人才培养是当前侦查学教学改革的现实需要。通过研究人工智能赋能侦查学实践教学的现状和背景，结合教学实践和实训经历，分析总结侦查学教学经验和案例数据，深度剖析了CDIO教学模式与OBE教学理念融合贯通的可能性、必要性。结论表明，CDIO-OBE理念是推进人工智能赋能侦查学实践教学的可行方式，对构建新时代公安学教学改革基本范式具有重要意义，同时还需重视适配性等现实问题。

Abstract: Enhancing the application of artificial intelligence within the teaching system of criminal investigation‑related courses and fostering top‑tier talents in criminal investigation represents a practical imperative for the ongoing teaching reform of criminal investigation. Based on an examination of the status quo and background of AI‑empowered practical teaching for criminal investigation, alongside frontline teaching and training experience, this paper summarizes relevant teaching practices and case data, and thoroughly explores the feasibility and necessity of integrating the CDIO teaching model with the OBE educational philosophy. The findings demonstrate that the CDIO‑OBE framework provides a viable pathway to advance AI‑empowered practical teaching in criminal investigation. It carries substantial implications for establishing a fundamental paradigm for public security teaching reform in the new era. Meanwhile, practical constraints including adaptability‑related challenges must be duly addressed.