Construction of Labor Education Evaluation Mechanism and Analysis of Implementation Path Based on Fuzzy Clustering Algorithm

The evaluation of labor education under the modernization of education should establish a long-term evaluation mechanism of labor education to achieve the goal of educating people by labor to build morality, labor to enhance intelligence, labor to strengthen the body, labor to cultivate beauty, and labor to innovate.In this paper, we use fuzzy clustering algorithm to construct labor education evaluation mechanism based on teacher evaluation standard.The results of this model for labor education evaluation are basically the same as those of manual evaluation, and can be used for the evaluation of the quality status of labor education.Based on this, the study plans in detail the preimplementation preparation, specific implementation steps and continuous optimization process of the evaluation mechanism.It also analyzes the implementation path of the labor education evaluation mechanism based on the fuzzy clustering algorithm by taking the example of Z elementary school in city A. The overall evaluation score of the quality of labor education in Z elementary school is 4.013, and there are still many areas that need to be improved.The evaluation mechanism of labor education based on fuzzy clustering algorithm was run in this school for 8 weeks, and the educational effect was continuously optimized through the incentive mechanism.Finally, the second-level fuzzy judgment method is introduced to further optimize the mechanism.Based on the new evaluation mechanism of labor education, individual student development can be evaluated, curriculum quality can be assessed, and operable solutions can be provided for the improvement of the quality of school labor education.