UNSTRUCTURED
Traditional medical education is facing significant challenges, particularly since the onset of the COVID-19 pandemic. Extensive research has highlighted the limitations imposed by resource, time, and space constraints, coupled with the often poor relationships between teaching subjects in medical education. This paper presents the architecture of a multimodal teaching interaction model combining both technological phenomenology and multimodal theory and its potential applications. In this study, we successfully constructed a teaching method involving multimodal virtual experience and describe the overall conceptual framework of learning scenarios. Based on the behavioral education model, situational learning, and human-computer interaction theory as the theoretical framework, the model uses the current medical education model as background and combines it with cutting-edge virtual reality, haptic feedback, gesture interaction, and other technologies. This is based on a multi-level application architecture, involving both physical and perceptual layers, and has obvious potential for application in three types of virtual medical education scenarios, namely, "theoretical knowledge learning", "operational skill learning", and "practical experiential learning". This establishes a cross-spatial connection between the virtual and the real using model immersion, collaboration, dynamic feedback, and other characteristics, overcoming the limitations of spatial scenes. If leveraged, the multimodal teaching interaction model (MTIM) will expand the application scenarios of teaching and will effectively enhance the sense of reality and experience of situational teaching, resulting in improved interactive feedback between medical education subjects and meeting teaching and learning needs in the post-epidemic era. Overall, the model proposed in this paper has significant potential for promoting reform in medical education, together with providing feasible ideas and suggestions for the future development of artificial intelligence in medical education.