AI-Enabled Blended Teaching Innovation and Practice in Military Academy Engineering Education

Abstract

In the context of deep integration of artificial intelligence technology into the education field, blended teaching has become a key path to promote the transformation of teaching models and improve the quality of education. This paper takes the “Photoelectric Detection Technology for Space Targets” course in our university’s photoelectric information science and engineering program as an example to elaborate on the process of AI-enabled blended teaching innovation and practice in military academy engineering core courses. First, the basic course situation is introduced; second, based on the analysis of students’ and the course’s conditions, three major pain points in blended teaching are identified: disconnection between technology and operational requirements, separation of capability and value generation, and disconnection between teaching and strategic vision; then, focusing on four dimensions—teaching content, teaching model, teaching scenarios, and teaching evaluation—detailed AI-enabled blended teaching innovation measures are explained, achieving deep integration of “knowledge transmission - capability cultivation - value shaping” trinity; finally, the effectiveness of teaching innovation is summarized. This paper can provide ideas and references for AI-enabled blended teaching reform in engineering majors.