Reconstruction of University Art Education in the Era of Artificial Intelligence and Mixed Reality: A Curriculum Design Framework Based on the ASSURE Model

Abstract

Generative artificial intelligence (AI) and mixed reality (MR) technologies are driving the transformation of university art education from traditional skills training and work appreciation to digital creation, immersive experience, and cross-media expression. However, current applications mostly remain at the tool level, lacking a systematic and transferable teaching design framework. Based on the ASSURE instructional design model, this paper integrates the concept of "borderless learning" and extends the LeSMaT (Borderless) framework to the field of art education, proposing "Learning Science and Arts Together in a Borderless World" (LeSAT (Borderless)), and constructs an AI-MR enhanced university art course framework. This framework unfolds around six stages: learner analysis, goal setting, medium selection, teaching implementation, learning participation, and evaluation. Taking university art courses as an example, a four-stage progressive teaching process is designed: interest stimulation, skill training, immediate feedback, and digital creation, and a five-dimensional course goal is constructed, covering physical skills, artistic creation, digital literacy, individual empowerment, and social collaboration. From the perspective of educational psychology, this framework helps to reduce technology anxiety, enhance self-efficacy, increase learning persistence, and promote the development of higher-order thinking. As a conceptual study, this paper provides a structured and transferable theoretical path for the reconstruction of university art courses driven by technology. In addition, the flexibility of this framework makes it potentially applicable to special education settings, where learner-centered design and multimodal technology integration can address diverse sensory, motor, and cognitive needs.