Journal of System Simulation
Iterative Evolution and Innovation of Simulation-based Experimental Teaching in Software Engineering
Abstract
In view of the structural disconnection between talent training and industry needs caused by the limitations of traditional computer experiment teaching in scenario authenticity, technological frontier, interdisciplinary integration, and student subjectivity, this paper proposed and practiced a new simulation-based experimental teaching system deeply integrating Chinese educational wisdom. Taking "incremental progress and learning by guided inquiry" as the core philosophy, through a four-in-one paradigm transformation of "task modularization, scenario virtualization, technological frontier, and integration deepening", this paper promoted the teaching to shift from closed skill verification to open engineering innovation and constructed a complete implementation path including "closed-loop iterative teaching process", "co-construction of dual-qualified and dual-capable teachers", and "open collaborative resource ecosystem". The system promotes the leapfrog development of students' engineering practice and innovation abilities, is recognized by important teaching achievements, builds high-level courses and platforms, and forms significant cross-institutional radiation and effects of industry-education integration.
Recommended Citation
Guo, Jun; Liu, Yixian; Ma, Lianbo; Liu, Jian; and Xu, Chunyan
(2026)
"Iterative Evolution and Innovation of Simulation-based Experimental Teaching in Software Engineering,"
Journal of System Simulation: Vol. 38:
Iss.
6, Article 4.
DOI: 10.16182/j.issn1004731x.joss.26-0131
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol38/iss6/4
First Page
1509
Last Page
1518
CLC
TP391.9
Recommended Citation
Guo Jun, Liu Yixian, Ma Lianbo, et al. Iterative Evolution and Innovation of Simulation-based Experimental Teaching in Software Engineering[J]. Journal of System Simulation, 2026, 38(6): 1509-1518.
DOI
10.16182/j.issn1004731x.joss.26-0131
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Artificial Intelligence and Robotics Commons, Computer Engineering Commons, Numerical Analysis and Scientific Computing Commons, Operations Research, Systems Engineering and Industrial Engineering Commons, Systems Science Commons