面向2035的基础教育教师需求规模预测——基于BP神经网络模型
Forecast of the Scale of Demand for Basic Education Teachers towards 2035—Based on the BP Neural Network Model
高晓清 1吴敏1
作者信息
- 1. 湖南师范大学 教育科学学院,湖南 长沙 410081
- 折叠
摘要
基于 2003-2021 年基础教育教师规模及其影响因素的变动情况,采用BP神经网络模型对 2023-2035 年基础教育教师需求和师资盈缺情况进行预测,发现基础教育教师总体需求规模呈现不断缩小的趋势,其中学前教育和小学阶段教师需求持续下降,初中和普通高中阶段教师需求呈先增后减趋势.这一期间,师资需求振幅较大,学前教育和小学阶段师资需求将出现阶段性短缺或过剩,这对教师资源的供给弹性和适应性提出了更高要求.基于以上发现,管理部门应稳定部署师范生招生计划,推进教师供需均衡;加强教育体系内贯通协作,促进教师合理流动;催生社会需求新业态,激励教师多元就业.
Abstract
Based on the changes in the scale of basic education teachers and their influencing factors from 2003 to 2021,the BP neural network model is used to predict the demand for basic education teachers and the shortage of teachers from 2023 to 2035,and it is found that the overall demand for basic education teachers shows a decreasing trend,among which the demand for teachers in pre-school education and primary school continues to decline,and the demand for teachers in junior high school and general high school in-creases first and then decreases.During this period,the demand for teachers will fluctuate greatly,and there will be a shortage or sur-plus of teachers in pre-school education and primary school,which puts forward higher requirements for the supply elasticity and adapta-bility of teacher resources.Based on the above findings,the management department should steadily deploy the enrollment plan of student teachers and promote the balance between teacher supply and demand,strengthen the integration and coordination within the ed-ucation system to promote the rational mobility of teachers,promote the emergence of new forms of social demand and encourage teach-ers to diversify their employment.
关键词
基础教育/教师需求/师资盈缺/BP神经网络模型/2035Key words
basic education/teacher needs/shortage of teachers/BP neural network model/2035引用本文复制引用
基金项目
湖南省教科规划基地项目(XJK23AJD045)
出版年
2024
NETL
NSTL
万方数据