Computational Thinking, Object-Oriented Programming to Role-Based Collaboration
Ke Gong, Haibin Zhu, Tianshuo Yang · 2025
Computational Thinking (CT) promotes the systematic resolution of complex interdisciplinary problems through abstraction, decomposition, pattern recognition, and modularization. As an extension of scientific reasoning, CT enhances problem modeling, resource allocation, and decision-making efficiency across various domains. This paper examines the fundamental principles of CT and demonstrates its practical applications in Object-Oriented Programming (OOP) and the E-CARGO model. Furthermore, it presents a case study on immigration policy making, illustrating how abstraction and classification improve problem modeling, while divide-and-conquer techniques enable computation and task assignment. The experimental results validate the superiority of CT-driven methods over traditional approaches in speed, accuracy, and cost-effectiveness. By integrating human reasoning with computational methodologies, CT provides a fundamental methodology for addressing large-scale optimization challenges, advancing both scientific research and applied problem-solving.