The integration and promotion of intelligent technology in the education industry has led to the introduction of more and more intelligent assistive teaching tools and platforms into the classroom, and the traditional classroom mode and teaching form are undergoing significant changes. This paper utilizes a university teaching and quality evaluation system to design the teaching evaluation module. Improving the particle swarm optimization algorithm and combining it with the K-Means algorithm has resulted in the construction of a teaching evaluation model based on the PSKA algorithm. The model is incorporated into the English teaching and quality evaluation system in colleges and universities. The PSKA algorithm is used to cluster students’ learning situations and divide four categories of students with different learning levels. Targeted guidance for each category of students’ learning problems can effectively improve the quality of teaching. The questionnaire survey revealed that 61.07% of English teachers understood the model, with 47.25% saying they actively use it and recommend it to other teachers. It is evident that the teaching evaluation model based on the PSKA algorithm is recognized by most English teachers.