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October 9, 2025Open Access

The Role Of Simulation Software In Enhancing Practical Skills For Students In Electrical Automation

Key Points

Simulation software significantly enhances practical skills like modeling and PLC skills in students of electrical automation.
Quantitative analysis showed that MATLAB/Simulink and Proteus were among the most effective, with modeling skills impacted by β=0.42.
Mixed-methods research incorporated quantitative and qualitative elements to assess practical skill development across various campuses.
Supporting factors like active learning and project-based learning are crucial for maximizing the impact of simulation software.

Abstract

The paper evaluates the role of simulation software in improving the practical skills of students of Electrical – Automation and explains the pedagogical mechanism that helps turn "software hours" into "measurable competence". Mixed-methods research with 309 participants (287 students, 22 lecturers) at three campuses (School of Electrical and Electronic Engineering, Hanoi University of Science and Technology; School of Electrical and Electronics, Hanoi University of Industry; University of Industry – Thai Nguyen University). The five core platforms include MATLAB/Simulink, Proteus VSM, Siemens TIA Portal, Beckhoff TwinCAT 3, and Factory I/O. The quantitative block uses a tested scale (Cronbach's α=0. 81–0. 89), EFA (KMO=0. 91; 6 factors; extraction variance 68. 4%), CFA (CFI=0. 94; TLI=0. 92; RMSEA=0. 048) and SEM for direct/indirect impact testing; 5, 000-sample bootstrap and multi-group analysis (MG-SEM) test for durability and differentiation by school year/campus. Topic-coded qualitative blocks (interviews/observations) to collate results. The results show that the direct impact is consistent with the pedagogical function of each software: MATLAB/Simulink → modeling skills (β=0. 42), Proteus → embedded skills (β=0. 37), TIA Portal → PLC skills (β=0. 34), TwinCAT → distributed control (β=0. 28), Factory I/O → system integration (β=0. 26). Three intermediate channels are significant: Active Learning (AL) is the strongest (βᵢndirect=0. 14), followed by interactive learning (0. 12) and project-based teaching – PBL (0. 10). R²=0. 29–0. 47 suggests that simulation is an important lever but still needs support from real labs, mentoring, and appropriate learning organization. MG-SEM confirms measurement invariance (ΔCFI=0. 004; ΔRMSEA=0. 003) and records year 4 over year 3 in TIA→PLC (+0. 08) and Factory I/O→integrated (+0. 07). Qualitative data indicate onboarding for the first 2–3 sessions, capstone attached to industrial situations, and mentoring is the key to amplifying the effect.

The Role Of Simulation Software In Enhancing Practical Skills For Students In Electrical Automation

Key Points

Abstract

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