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

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 (β_indirect=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.

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Publication Details

Journal
International Journal of Environmental Sciences
Published
2025-10-07
DOI
https://doi.org/10.64252/aqhga020
Primary Topic
Experimental Learning in Engineering
Type
article
Field-Weighted Citation Impact
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article

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

Vu Huy Hoa
International Journal of Environmental Sciences
Experimental Learning in Engineering
article

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

Vu Huy Hoa
article en

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 (β_indirect=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.

International Journal of Environmental Sciences
Openalex Percentile: Top 60%
Experimental Learning in Engineering
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