Work

A System Dynamics Model for Simulating the Development of Postgraduate Innovation Capacity in Smart Learning Environments

Year: 2026

Type: article

Abstract: This study develops a system dynamics model to simulate the development of postgraduate innovation capacity in smart learning environments. Grounded in the system dynamics view that system behavior emerges from feedback structure, time delays, and nonlinear interaction rather than from isolated factor effects, the model represents postgraduate innovation capacity through three interrelated subsystems—summary ability, imagination, and transformative ability—and captures their interactions with learning support, learning assessment, learning resources, and data analysis. Based on data extracted from publicly available postgraduate education development quality reports, the relationships among variables were formulated, and the model was tested for dimensional consistency, numerical robustness, and behaviorally plausible performance. Simulation experiments were conducted to examine the dynamic evolution of postgraduate innovation capacity under different parameter perturbation scenarios. Scenario-based sensitivity comparisons were performed to identify the key factors influencing system behavior. The simulation results reveal several important system characteristics, including diminishing marginal returns in learning support, saturation effects in learning resources, delayed cumulative effects in learning assessment, and upper-range amplification in data analysis. In addition, the development of imagination exhibits an exponential growth pattern, while transformative ability is constrained by system feedback structures. These findings indicate that postgraduate innovation capacity development is governed by a nonlinear dynamic system rather than by linear factor relationships. From an applied mathematics perspective, the proposed model provides a quantitative simulation framework for examining the structural behavior of a complex educational system under feedback, delay, and scenario perturbations.

Source: Mathematics

DOI: 10.3390/math14091460

Authors: Jingshu Liu, Lei Zhang

Institutions: Air Force Engineering University, Xi'an Eurasia University

Language: English

Topic: Complex Systems and Decision Making

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

SDGs: Quality education, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $3,137