Modeling the Rate of Adaptation of Teachers to a New Teaching Method as a Stochastic Logistic Adaptation Model

Abstract

This study develops and analyzes a stochastic logistic adaptation model to describe the rate at which a population of teachers adjusts to a newly introduced teaching method. Using a stochastic differential equation with multiplicative noise, the model captures both deterministic growth and random fluctuations in adaptation. The Euler-Maruyama scheme is employed for numerical simulation, with convergence and stability rigorously established. Simulation results provide insight into the dynamics of adaptation under uncertainty, supported by mean-variance analysis and visualizations. This framework offers a realistic tool for understanding adaptation processes in educational interventions.