INNOVATION AND DIFFUSION OF THE SWANSOFT CNC SIMULATOR IN CNC LEARNING AND THE POTENTIAL DEVELOPMENT OF VIRTUAL REALITY
Keywords:
CNC Learning, Swansoft CNC Simulator, Diffusion of Innovation, Virtual Reality, Vocational EducationAbstract
The advancement of manufacturing technology has increased the importance of Computer Numerical Control (CNC) competencies in engineering and vocational education. However, limited access to physical CNC machines and high operational costs remain significant challenges in CNC learning. The Swansoft CNC Simulator has emerged as an innovative solution that enables students to learn CNC programming and machine operation in a safe, flexible, and virtual learning environment. This study employed a quantitative approach using a survey method. Data were collected through a questionnaire administered to 32 students who had experience using the Swansoft CNC Simulator in CNC learning activities. The research instrument was developed based on Rogers’ Diffusion of Innovation Theory, encompassing five key attributes: Relative Advantage, Compatibility, Complexity, Trialability, and Observability. The collected data were analyzed descriptively using frequencies, percentages, and mean scores. The results revealed that most students perceived the Swansoft CNC Simulator as highly beneficial in improving their understanding of CNC programming and machine operation. The findings also indicated a high level of technology adoption among students, although several challenges related to compatibility with individual learning preferences and perceived complexity were identified. Furthermore, the study demonstrated that Virtual Reality (VR) technology has considerable potential to enhance the effectiveness of CNC learning, as most students expressed strong interest in integrating VR into CNC simulation environments. The study concludes that the Swansoft CNC Simulator contributes positively to learning effectiveness, reduces the risk of errors during CNC training, and enriches students’ learning experiences. The integration of Virtual Reality is recommended as an innovative approach to support more realistic, immersive, and effective simulation-based CNC learning
References
Arsenal, A., Leni, D., & Muchlisinalahuddin. (2025). OPTIMIZATION OF CNC MILLING MACHINING PARAMETERS ON PROCESSING TIME AND SURFACE QUALITY USING NANJING SWANSOFT SIMULATION. The Fifth International Conference on Innovations Social Sciences Education and Engineering, 5, 137–137. https://conference.loupiasconference.org/index.php/ICoISSEE-5/article/view/782
Berner, B. (2009). Learning Control: Sense-Making, CNC Machines, and Changes in Vocational Training for Industrial Work. Vocations and Learning 2009 2:3, 2(3), 177–194. https://doi.org/10.1007/S12186-009-9023-8
Bond, M., Bedenlier, S., Marín, V. I., & Händel, M. (2021). Emergency remote teaching in higher education: mapping the first global online semester. International Journal of Educational Technology in Higher Education 2021 18:1, 18(1), 50-. https://doi.org/10.1186/S41239-021-00282-X
Chen, J., Xiao, X., Fan, M., & Cai, Y. (2026). Learn manufacturing together: research on mixed reality group teaching of CNC machine tools. The International Journal of Advanced Manufacturing Technology 2026, 1–17. https://doi.org/10.1007/S00170-025-17259-Z
Chernikova, O., Heitzmann, N., Stadler, M., Holzberger, D., Seidel, T., & Fischer, F. (2020). Simulation-Based Learning in Higher Education: A Meta-Analysis. Review of Educational Research, 90(4), 499–541. https://doi.org/10.3102/0034654320933544;SUBPAGE:STRING:FULL
Chiang, F. K., Shang, X., & Qiao, L. (2022). Augmented reality in vocational training: A systematic review of research and applications. Computers in Human Behavior, 129, 107125. https://doi.org/10.1016/J.CHB.2021.107125
Feng, J., Yu, B., Tan, W. H., Dai, Z., & Li, Z. (2025). Key factors influencing educational technology adoption in higher education: A systematic review. PLOS Digital Health, 4(4). https://doi.org/10.1371/JOURNAL.PDIG.0000764
Freeman, S., Eddy, S. L., McDonough, M., Smith, M. K., Okoroafor, N., Jordt, H., & Wenderoth, M. P. (2014). Active learning increases student performance in science, engineering, and mathematics. Proceedings of the National Academy of Sciences of the United States of America, 111(23), 8410–8415. https://doi.org/10.1073/PNAS.1319030111;WGROUP:STRING:PUBLICATION
Greeves, S., & Oz, M. (2023). YouTube in higher education: comparing student and instructor perceptions and practices. Frontiers in Education, 8, 1330405. https://doi.org/10.3389/FEDUC.2023.1330405/TEXT
Guo, G. (2025). Enhancing Project-Based Manufacturing Education With Integrated Engineering Software Tools. Computer Applications in Engineering Education, 33(2), e70012. https://doi.org/10.1002/CAE.70012;REQUESTEDJOURNAL:JOURNAL:10990542;PAGE:STRING:ARTICLE/CHAPTER
Hariyanto, D., Yatmono, S., Khairudin, M., & Kí¶hler, T. (2022). Students e-learning readiness towards education 4.0: Instrument development and validation. Jurnal Pendidikan Vokasi, 12(3), 236–244. https://doi.org/10.21831/JPV.V12I3.51798
Huang, F. (2025). Exploring a new model of undergraduate vocational education. Vocation, Technology & Education, 2(1), e3–e3. https://doi.org/10.54844/VTE.2025.0869
Hussain, S., & Khan, P. (2024). Enhancing Spatial Skills through Immersive Virtual Reality: An Empirical Study on Educational Outcomes and Cognitive Engagement. Frontiers in Computational Spatial Intelligence, 2(3), 124–132. https://journal.xdgen.com/index.php/FCSI/article/view/321
Kubat Assoc, U. (2025). IMPACTS OF PRACTICAL TEACHING IN ENGINEERING EDUCATION. European Journal of Education Studies, 12(11). https://doi.org/10.46827/EJES.V12I11.6324
Liang, D. Y. (Danni), Chen, D. S., Abeysekera, D. R., O’Sullivan, D. H., Bray, D. J., & Keevill-Savage, I. (2024). Examining the adoption of technology-enhanced learning in universities and its effects on student performance, satisfaction, and motivation. Computers and Education Open, 7, 100223. https://doi.org/10.1016/J.CAEO.2024.100223
Scager, K., Boonstra, J., Peeters, T., Vulperhorst, J., & Wiegant, F. (2016). Collaborative Learning in Higher Education: Evoking Positive Interdependence. CBE Life Sciences Education, 15(4), ar69. https://doi.org/10.1187/CBE.16-07-0219
Siryono, R., Santosa, B., & Susatya, E. (2023). The Effect of Using a CNC Simulator in Learning the Mechanical Engineering Skills Program. International Journal of Social Health, 2(10), 799–815. https://doi.org/10.58860/IJSH.V2I10.117
Soori, M., Karimi, F., Jough, G., Dastres, R., & Arezoo, B. (n.d.). ROBOTICAL AUTOMATION IN CNC MACHINE TOOLS: A REVIEW. https://doi.org/10.2478/ama-2024-0048
Talan, T. (2020). The Effect of Simulation Technique on Academic Achievement: A Meta-Analysis Study. International Journal of Technology in Education and Science, 5(1), 17–36. https://doi.org/10.46328/IJTES.141
Yang, C., Zhang, J., Hu, Y., Yang, X., Chen, M., Shan, M., & Li, L. (2024a). The impact of virtual reality on practical skills for students in science and engineering education: a meta-analysis. International Journal of STEM Education, 11(1), 28-. https://doi.org/10.1186/S40594-024-00487-2/TABLES/3
Yang, C., Zhang, J., Hu, Y., Yang, X., Chen, M., Shan, M., & Li, L. (2024b). The impact of virtual reality on practical skills for students in science and engineering education: a meta-analysis. International Journal of STEM Education, 11(1), 28-. https://doi.org/10.1186/S40594-024-00487-2/TABLES/3
Yip-Hoi, D. M. (n.d.). Using simulation to improve the efficiency of CAM and CNC instruction. ASEE Annual Conference and Exposition, Conference Proceedings, 2013. https://doi.org/10.18260/1-2--22721
Yip-Hoi, D. M. (2013). Using Simulation to Improve the Efficiency of CAM and CNC Instruction. ASEE Annual Conference and Exposition, Conference Proceedings. https://doi.org/10.18260/1-2--22721
Zheng, P., Yang, J., Lou, J., & Wang, B. (2024). Design and application of virtual simulation teaching platform for intelligent manufacturing. Scientific Reports 2024 14:1, 14(1), 12895-. https://doi.org/10.1038/s41598-024-62072-5
Downloads
Published
How to Cite
Issue
Section
Citation Check
License

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors submitting a manuscript do so on the understanding that if accepted for publication, the copyright of the article shall be assigned to Jurnal Dinamika Vokasional Teknik Mesin

