Autonomous learning is a hot issue in current research in learning. The article firstly constructs an autonomous learning model based on dynamic fuzzy logic (DFL) theory and describes the independent behavior rules in detail. Further, a learning algorithm for the independent learning subspace is proposed. To verify the effectiveness of the DFL-based autonomic learning model, the authors selected college students majoring in English for Tourism as experimental subjects, divided the students into experimental and control groups, and compared their test results before and after the autonomic learning teaching experiment. The study results show that in the six-month experiment, the experimental group significantly improved in three aspects: study time, independent learning ability, and learning achievement. Specifically, upper-middle and middle-level students excelled in independent learning ability. In contrast, students at the lower-middle level showed significant improvement in terms of study time and academic performance, and these differences reached the level of extreme significance (p<0.01). In addition, in terms of the level of learning autonomy, the experimental group has higher indicators of learning autonomy level than the control group in all six dimensions, especially in the dimension of learning environment, the difference between the experimental group and the control group is as high as 52.53%. The study proves the effectiveness of the autonomy learning model based on dynamic fuzzy logic in enhancing students’ autonomy learning ability, especially in promoting the learning development of students at different levels showing significant advantages.