Deep Learning Oriented to Disciplinary Education: Generation Mechanisms and Practical Logics

Deep learning is a learning ecology that couples the cognitive process and the knowledge production process with the participation of students' thinking. Disciplinary education is a discipline function design that integrates the discipline knowledge system, the logic system, and the cultural system into the core competencies of people. Deep learning is highly compatible with the operation mechanism of disciplinary education in three aspects: excavating curriculum resources, developing the knowledge system and promoting the formation of people's competency. Based on the comprehensive processing of curriculum resources, the deep learning of disciplinary education leads students to construct the subjectivity of the knowledge system and guides exploration and generation of students' thinking logic. Therefore, taking disciplinary education as the logical backbone, designing situational discipline practice activities, building a discipline learning community, and connecting the "teaching-learning-evaluation" education link, are the internal requirements and practical paths for cultivating a deep learning ecology and realizing the purpose of disciplinary education.