The invention belongs to the field of education data mining, and provides a knowledge and skill dynamic diagnosis method oriented to space-time evolution. The method comprises the following steps of: firstly, constructing a knowledge heterogeneous graph according to resource characteristics, and then dynamically updating the knowledge and skill state of a learner in time and space dimensions, therefore, the future performance of the learner is predicted, and the knowledge mastering condition of the learner is diagnosed. According to the method, a big data technology, deep learning and a natural language processing technology are comprehensively utilized, knowledge points of a learner are modeled from time and space, the knowledge state of the learner is influenced by introducing learning features and forgetting features, and a knowledge structure of the learner is updated by providing space-time cascade operation, the knowledge and skills of the learner can be diagnosed scientifically and comprehensively, future performance of the learner can be predicted, personalized recommendation practice can be performed on knowledge points with low skill mastery, and personalized teaching can be performed on knowledge points with poor performance in the future.