Particle swarm optimization algorithm (PSO) is a global optimization algorithm based on swarm intelligence, which originated from the simulation of the collective behavior of birds and fish flocks. In the education field, the PSO algorithm can be applied to solve complex problems, such as curriculum arrangement optimization, educational resource allocation, and student learning path planning, etc. Its advantage lies in the ability to deal with complex optimization problems with multi-objective and multi-constraint, and has the characteristics of high computational efficiency and easy to achieve. In recent years, PSO algorithm has gradually emerged in the design of educational evaluation system, which is used to build a more fair and comprehensive teaching quality evaluation model, so as to improve the scientificity and accuracy of educational decision-making. MATLAB simulations show the quality of PSO algorithms for higher education entrepreneurship under certain evaluation criteria The evaluation accuracy and quality evaluation time were better than the CDIO education model.