Exploration of college teacher education path based on cognitive multi-method integration for innovation and entrepreneurship ability cultivation

Abstract

Abstract In this paper, a cognitive multi-method integration-based approach combined with a genetic algorithm for optimization is used to set the random variables as Bayesian network nodes, and the joint probability distribution is obtained by analyzing the strength of association between the nodes. An independently distributed observation data set with random variables is used to determine the log-likelihood function. After generating the random data, the roulette wheel is used to select the individuals with higher fitness values for transformation, and the excellence of the individuals in the population is improved through cyclic iteration. 20 points improved the educational practice’s 4th test score compared to the pre-training score after the innovation and entrepreneurship training. Therefore, the method of cultivating innovation and entrepreneurial abilities based on cognitive multi-method integration has a positive effect on improving the education level and talent cultivation quality of college teachers.