94% of researchers rate our articles as excellent or good
Learn more about the work of our research integrity team to safeguard the quality of each article we publish.
Find out more
ORIGINAL RESEARCH article
Front. Psychol.
Sec. Quantitative Psychology and Measurement
Volume 16 - 2025 | doi: 10.3389/fpsyg.2025.1536476
This article is part of the Research TopicMethodological and Statistical Advances in Educational AssessmentView all 9 articles
Predicting the Demand for Preschool Teachers in China under the Three-Child Policy: A Comparative Analysis between Guangdong Province and Jilin Province
Provisionally accepted- Faculty of Education, Northeast Normal University, Changchun, Jilin Province, China
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
The implementation of fertility policies can lead to changes in population size, thereby affecting the supply pattern and spatial distribution of teacher resources. Under the context of the three-child policy, this study constructs Long Short-Term Memory (LSTM) neural network models to predict the scale of preschool children in kindergartens and the demand for full-time teachers in Guangdong Province and Jilin Province from 2023 to 2035. Based on the prediction results, it explores the differences between the two provinces and their causes. The study finds that the scale of preschool children in kindergartens and the demand for full-time teachers in Guangdong Province exhibit an overall upward trend, while in Jilin Province, both exhibit an overall downward trend, with the two provinces moving in opposite directions. Additionally, in the future pursuit of high-quality development of preschool education, both Guangdong and Jilin Provinces need to further expand the number of full-time teachers. These findings provide data references and decision-making support for the local governments to plan the preschool education sector and adjust the allocation of teacher resources.
Keywords: three-child policy, Population prediction, Preschool teacher demand, LSTM neural network models, kindergartens
Received: 29 Nov 2024; Accepted: 09 Apr 2025.
Copyright: © 2025 Xu, Wang and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Jiwei Zhang, Faculty of Education, Northeast Normal University, Changchun, 130024, Jilin Province, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.