Factors Affecting Machining Competency in Vocational Education: A Path Analysis Approach

Chrisna Tri Harjanto, Wagiran Wagiran, Sutopo Sutopo, Dwi Rahdiyanta, Tri Adi Prasetya

Abstract

This study aims to analyze the direct influence of achievement motivation and workshop facilities, as well as the indirect influence through independent learning and practical machining learning on students' machining competency. A quantitative approach using path analysis, assisted by the SPSS program, was used to determine the causal relationships among variables. Before conducting the path analysis, the data met the prerequisite tests for normality, linearity, multicollinearity, and homoscedasticity, making it suitable for parametric analysis. The results show that achievement motivation and workshop facilities have a positive and significant influence on machining competency, both directly and indirectly through increasing independent learning and the effectiveness of practical machining learning. Overall, these findings confirm that both student and learning environment factors play an important role in the development of machining competency. The results of this study provide an empirical basis for the development of vocational learning strategies that are more effective and aligned with the needs of the modern manufacturing industry.

Keywords

Achievement Motivation, Workshop Facilities, Independent Learning, Practical Machining Learning, Machining Competence

Full Text:

PDF

References

Douma, J. C., & Shipley, B. (2021). A multigroup extension to piecewise path analysis. Ecosphere, 12(5). https://doi.org/10.1002/ecs2.3502 Guo, B., Qiang, B., Zhou, J., Yang, X., Qiu, X., Qiao, Z., Yang, Y., & Cao, D. (2021). The Relationship between Achievement Motivation and Job Performance among Chinese Physicians: A Conditional Process Analysis. BioMed Research International, 2021. https://doi.org/10.1155/2021/6646980 Kwak, S. (2023). Are Only p-Values Less Than 0.05 Significant? A p-Value Greater Than 0.05 Is Also Significant! Journal of Lipid and Atherosclerosis, 12(2), 89–95. https://doi.org/10.12997/jla.2023.12.2.89 Li, L. (2024). Reskilling and Upskilling the Future-ready Workforce for Industry 4.0 and Beyond. Information Systems Frontiers, 26(5), 1697–1712. https://doi.org/10.1007/s10796-022-10308-y Li, Y., & Leong, W. Y. (2025). Employment status analysis and response strategies of students majoring in mechanical manufacturing and automation in vocational colleges under the background of Industry 5.0. In Industry 5.0: Design, standards, techniques and applications for manufacturing (pp. 415–448). https://doi.org/10.1049/PBME026E_ch19 López, E. J., Leyva, P. A. L., López, A. A., Estrella, F. J. O., Vázquez, J. J. D., Velázquez, B. L., & Molina, V. M. M. (2024). Mechanics 4.0 and Mechanical Engineering Education. Machines, 12(5). https://doi.org/10.3390/machines12050320 López, F., Contreras, M., Nussbaum, M., Paredes, R., Gelerstein, D., Alvares, D., & Chiuminatto, P. (2023). Developing Critical Thinking in Technical and Vocational Education and Training. Education Sciences, 13(6), 590. https://doi.org/10.3390/educsci13060590 Sahli, A., Ebnou Abdem, S. A., Hanafi, M., & El Hadri, Z. (2025). Extending El-Hadri-Sahli-Hanafi procedure for path analysis with non standardized variables. Quality and Quantity, 59(1), 175–190. https://doi.org/10.1007/s11135-024-01932-8 Spöttl, G., & Windelband, L. (2021). The 4th industrial revolution–its impact on vocational skills. Journal of Education and Work, 34(1), 29–52. https://doi.org/10.1080/13639080.2020.1858230 Sutopo, S., Setiadi, B. R., Prasetya, T. A., Harjanto, C. T., Sasongko, B. T., & Saputri, V. H. L. (2024). Peer-Project-Based Learning in CNC Simulation Programming Courses. TEM Journal, 13(4), 3079–3085. https://doi.org/10.18421/TEM134-42 Sutopo, Setiadi, B. R., Nashir, I. M., Lutviana, V. H., Saputri, Arifin, A., Prasetya, T. A., Harjanto, C. T., Tri, B., & 1, S. (2024). Enhancing students ’ self-efficacy and creativity in computer numerical control machining through peer-assisted project-based learning. Jurnal Pendidikan Vokasi, 14(2), 232–243. Trinchera, L., Marie, N., & Marcoulides, G. A. (2018). A Distribution Free Interval Estimate for Coefficient Alpha. Structural Equation Modeling, 25(6), 876–887. https://doi.org/10.1080/10705511.2018.1431544 Van Nguyen, T., Nguyen, H. T., Cao, C. D., & Vu, H. T. T. (2023). Activities of the practice teaching organization and vocational teaching facilities in collaboration between the vocational school and units employing. Journal of Education and E-Learning Research, 10(2), 243–249. https://doi.org/10.20448/jeelr.v10i2.4588

Refbacks

  • There are currently no refbacks.