Artificial Intelligence Project Engineering Education: Research on Improving Legal Awareness, Financial Decision-Making and Management Control Capabilities Based on EPC Simulation
The integration of artificial intelligence (AI) into engineering education presents new opportunities for enhancing professional competencies through simulation-based learning. This study investigates the role of AI-driven EPC (Engineering-Procurement-Construction) project simulation in improving students' legal risk awareness, financial decision-making ability, and management control capability. Grounded in experiential learning theory and the Technology Acceptance Model (TAM), a conceptual framework was developed to analyze the impact of AI-enabled simulation modules on key learning outcomes. The research employed a quasi-experimental design involving 180 engineering management students, utilizing pre-and post-tests, structured questionnaires, and structural equation modeling (SEM) to assess changes in student competencies. Results reveal that AI-enhanced EPC simulation significantly improves participants' ability to recognize legal risks, make strategic financial decisions, and exercise effective project control. Additionally, the level of cognitive interaction with AI modules serves as a strong predictor of performance gains across all three domains. The findings provide empirical evidence for the pedagogical value of AI in project-based engineering education and offer actionable insights for curriculum innovation in the digital age.
Authors
- Xiajing Chen
- Fengzhen Wang (ORCID: https://orcid.org/0000-0002-5742-0482)
- Kyungwon An (ORCID: https://orcid.org/0000-0003-4142-6297)
- Bin Wang (ORCID: https://orcid.org/0000-0002-1464-3598)
- Rui Ye (ORCID: https://orcid.org/0009-0007-5998-8200)
- Yangwang Fang (ORCID: https://orcid.org/0000-0002-0184-7305)
Institutions
- Guizhou University (CN)
- Hainan University (CN)
- Xinyu University (CN)
- Cavite State University (PH)
- Fuzhou University (CN)
Publication Details
- Journal
- Education insights.
- Published
- 2025-05-31
- DOI
- https://doi.org/10.70088/9gwh0756
- Primary Topic
- Technology Assessment and Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00