To enhance the labor literacy of college students, this paper examines big data in labor education. Firstly, it visualizes and preprocesses labor education big data and designs a method to analyze labor education big data based on an improved ant colony clustering algorithm. Secondly, it examines the labor education of higher vocational colleges in the new era and establishes an evaluation index system for higher vocational labor education in the new era. Finally, labor education is examined using the improved ant colony clustering algorithm, and the practical effects of labor education are examined. Practice shows that ant colony clustering clusters labor education in higher vocational colleges into three categories, in which the proportion of category 1 is 0.28, the proportion of category 2 is 0.41, the proportion of category 3 is 0.31, and the effects of labor concepts, labor knowledge, labor skills, labor qualities, and labor literacy have been improved by 0.27, 0.29, 0.29, 0.26, and 0.24, respectively. Higher vocational colleges and universities of the new era of labor education can improve the labor literacy of working college students.