Design and implementation of an intelligent virtual simulation experimental system for financial decision-making
Feifei Tang
School of Artificial Intelligence, Jingchu University of Technology
Jiawen Shi
School of Artificial Intelligence, Jingchu University of Technology
Haonan Wan
School of Artificial Intelligence, Jingchu University of Technology
Xuerong Liu
School of Artificial Intelligence, Jingchu University of Technology
Wenzhi Zhang
School of Economics and Management, Jingchu University of Technology
Yunxia Yu
Intelligent Information Technology Research Center, Jingchu University of Technology/Jingmen Cryptometry Application Technology Research Center
DOI: https://doi.org/10.59429/esta.v13i3.15554
Keywords: financial decision-making; virtual simulation; intelligent experimental system; decision support; experimental teaching
Abstract
Financial decision-making experiments should connect accounting evidence with investment, financing, budgeting, and risk choices, yet conventional exercises often use static datasets, isolate analytical steps, and provide delayed feedback. This paper presents the design and implementation framework of an intelligent virtual simulation experimental system for financial decision-making intended for students in finance, accounting, economics, management, and related business programmes. The proposed system adopts a five-layer architecture comprising presentation, business service, intelligent analysis, data, and infrastructure layers. Nine coordinated modules support scenario configuration, task management, financing and investment simulation, budget and cost management, rule-based analysis, process tracking, assessment, visualization, and administration. A closed-loop workflow links financial data acquisition, student analysis, decision submission, simulation calculation, feedback, performance evaluation, and strategy adjustment. The current study focuses on system architecture, functional design, implementation methodology, and a prototype-level evaluation framework. Empirical performance and classroom effectiveness are reserved for prototype deployment and controlled classroom studies under appropriate governance.
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