Teacher Workforce Planning in South Korea using System Dynamics Modeling

• In Event: AI & Big Data based Future Education Policy in Korea

Proposal

Recently, teacher workforce planning has become a crucial issue in South Korea because of the rapid decline in the total fertility rate. The total fertility rate is defined as the expected number of children per woman. In 2020, South Korea’s total fertility rate fell to 0.84, the lowest rate among over 180 member countries of the World Bank. The unprecedented level of fertility rate forces policymakers and researchers in South Korea to actively seek reliable forecasting models for teacher workforce planning in order to prepare the expected rapid decline of school-aged children.
However, when developing forecasting models for teacher workforce, most of the previous work in South Korea focused on the future demand for teacher based on the forecasting on the total population and the OECD average class size. However, the forecasting models that only focus on the future demand on teacher have failed to consider another important aspect of workforce planning, which is the need for the teachers. Thus, the goal of this study is to develop forecasting models for teacher workforce planning using system dynamics modeling by considering both the demand and need for teachers.
Workforce planning is a mature discipline where various analytic methods have been developed to predict future workforce in order to help organizations examine many different factors for a prognostic purpose. The models in the workforce planning can be categorized into three groups: supply-based, demand-based, and need-based models. Future supply, demand, and need are defined as the volume of services that can be provided, that is requested, and that is required to provide a desired standard of services, respectively.
In our study, we will first set different scenarios for the desired educational environments, which will serve as the need for our education in the future. Various factors will be considered for the desired educational environment: the expected population, class size, utilization of artificial intelligence in school, online education, high school credit system, innovation in pedagogy, budget constraints and so on. Then, using the system dynamics modeling, we will predict the number of teachers necessary to build the educational environments in each of the scenarios. To maximally mimic the real world, we will fully utilize the open datasets in the government open data portal.
System dynamics modeling was first proposed in the mid-1950s. System dynamic modeling aim to understand the behavior of complex systems by simulating systems as a series of stocks, flows, and feedback loops. System dynamic modeling has been widely used in the field of workforce planning and is considered as one of the most powerful method in the field.
Considering the urgent need for the reliable prediction for the teacher workforce in South Korea, we believe that our study has a potential for drawing meaningful implications for policymakers and researchers by simulating various factors based on both demand and need perspectives using system dynamics modeling.

Authors

• Sunbok Lee, Dept. of Education, Ewha Womans University

• Suyeon Jang, EWHA WOMANS UNIVERSITY