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In view of a series of problems such as weak sense of presence and low participation of students in online education, this project starts to reconstruct online courses from game elements, game strategies and incentive mechanisms, and designs a gamified online course framework based on knowledge structure embedding to support explicit knowledge embedded and implicitly knowledge embedded. The difficulty of the game was adaptively adjusted according to the student's learning basis, the mixed game rules were set, and the learning process was recorded and evaluated. Through the specific teaching practice in the past semester, we use machine learning algorithms to perform cluster analysis on the collected data, and it is proved that the frameworl can effectively reduce the cognitive load of learners in the application of online teaching and enable learners to obtain a good flow experience.