Users’ learning behavior patterns are crucial to their success in learning Chinese, however incorrect pattern placement is an issue. There is an issue with the learning behavior of Chinese language learning users that the classic particle swarm method cannot resolve, and the results are unsatisfactory. Hence, this work analyses the learning behavior pattern of Chinese language learning users and suggests a study based on enhanced fuzzy mean clustering to examine this pattern. First, the influencing elements are located using fuzzy theory, and then the indicators are split according to the learning behavior pattern’s criteria to decrease interference factors. Next, a scheme for better fuzzy mean clustering learning behavior pattern is developed using fuzzy theory. The outcomes of this learning behavior pattern are then thoroughly examined. Compared to the conventional particle swarm approach, the enhanced fuzzy mean clustering outperforms it under certain assessment criteria, particularly those pertaining to the timeliness and accuracy of learning behavior patterns.