Optimization of Child Literature Curriculum Settings for Preschool Education Based on Numerical Analysis

Abstract

With the progress of society and economy, the optimization setting of child literature courses in preschool education major has become increasingly popular. Curriculum optimization setting provides support for the effective inheritance of child literature. Numerical analysis is used to optimize the setting of child literature courses for preschool education majors, mainly by using the obtained data for the input of numerical analysis, collecting data from the “similar dataset” according to children’s daily language, and calculating the adjacent data in the dataset and evaluating child literature in preschool education while predicting the accuracy of curriculum optimization settings and making personalized recommendations for children’s interests according to the children’s numerical analysis results that are modified with the change of children’s interest over time. Finally, the results of the experiment indicate that the proposed algorithm for numerical analysis requires less time than other algorithms in the process of optimization for setting of child literature courses for preschool education majors, thereby ensuring more effective optimization of curriculum settings. Finally, the case study results suggest that the proposed method is effective in enhancing students’ interdisciplinary teacher skills, cultivating interdisciplinary teacher talents, improving students’ application and innovation capabilities, driving the development of disciplines, and serving the national cultural development strategy.