In order to analyze the effect of labor education (LE) for college students in college education, this paper combines big data technology to analyze the effectiveness of LE for college students. Moreover, this paper classifies the constraints of clustering effectiveness indicators and analyzes the characteristics and applications of various criteria in detail. In addition, this paper compares the effectiveness criteria of several commonly used fuzzy clustering based on relative criteria and compares and analyzes the performance and evaluation effect of these criteria. On this basis, this paper proposes an improved effectiveness criterion. Through the controlled experiment, it can be seen that the LE for college students can effectively improve the various abilities of college students, and it has a certain auxiliary effect on the learning and growth of college students.