In the epoch of intellectualization, intelligent technologies have been widely utilized in the education field. This not only brings opportunities for the progress of education and teaching but also puts forward totally new demands for talent cultivation under the background of the intelligent age. In this paper, we quantitatively represent learning resources from different directions in the context of human-machine symbiosis, and then use the hybrid collaborative recommendation algorithm in artificial intelligence technology to construct a personalized learning resource recommendation model based on human-machine symbiosis, and carry out experimental investigations on the model. After the model has obtained validation, a specially-made teaching model which centers on human-computer symbiosis is developed, this model acts as the technological foundation. After that, the practical teaching meaning of this teaching pattern is researched from four aspects: knowledge, skills, comprehensive using abilities, and cognitive abilities. Our research finds that the algorithm which this paper puts forward has a performance that is higher than the performance of the other three algorithms, with precision rate, recall rate and F1 value of 0.808, 0.728, 0.7659, respectively, which demonstrates the superiority of the hybrid recommender algorithm in the recommendation of teaching resources. In addition, the teaching mode of this paper is significantly different from the traditional teaching mode in four dimensions, P=0.005<0.05, P=0.026<0.05, P=0.007<0.05, P=0.005<0.05, proving the actual teaching effect of personalized teaching mode based on human-machine symbiosis. The research in this paper helps to improve the level of various abilities of college students, and also provides reference for the innovation of college teaching mode in the context of human-computer symbiosis.
