Simulation-Based Diagnostic Learning with Diagnostic Trouble Box (DTB): Enhancing Analytical Thinking Skills in Vocational Automotive Education

Authors

DOI:

https://doi.org/10.56294/saludcyt20251956

Keywords:

Automotive, Vocational Education, Simulation, Analytical Thinking, Diagnostic Trouble Box

Abstract

Introduction: Teaching automotive electrical systems in vocational education presents several challenges, including the abstract nature of the concepts covered and the conventional, non-interactive teaching methods. This study aims to describe analytical skills by introducing the Diagnostic Trouble Box (DTB). The research objective focuses on assessing the learning outcomes of the DTB in comparison to traditional methods.  
Methods: This study employed a quasi-experimental design with a pretest-posttest control group, involving 86 students in the 11th-grade automotive vocational class. Students were assigned to either an experimental group, which was taught using the DTB method, or a control group trained with conventional techniques. Data collection included analytical thinking tests, with data analyzed through paired and independent sample t-tests.  
Results: Learning with DTB significantly enhanced analytical thinking skills, especially off-set active electrical components based on diagnostics. The post-test mean score of the experimental group was 79.26 while the control group scored 68.41, resulting in a mean difference of 10.85 (p = .000). Improvement was most notable in the components of decision-making, systematic reasoning, and diagnostic accuracy. These findings demonstrate the reliability of DTBs for electrical diagnostics and suggest that the model may also be useful for developing other technical competencies based on data-driven problem-solving strategies.
Conclusion: The study highlights the vocational relevance of the DTB model for fostering critical and evaluative competencies in advanced automotive education. It enhances diagnostic preparedness by academically justifying the integration of simulation-based learning into vocational education.

References

1. Suyitno S, Jatmoko D, Ardiansyah N, Anitasar M. Automotive Electrical Learning Module to Improve Students Interest and Learning Achievement of Vocational School. In: ICSTI 2018. 2019. p. 1–5. doi: 10.4108/eai.19-10-2018.2281288. DOI: https://doi.org/10.4108/eai.19-10-2018.2281288

2. Et.al OC. The Development of aFlexibility-Project Based Learning Model on Vocational Education: A Need Analysis. Turkish J Comput Math Educ. 2021;12(3):2782–6. doi: 10.17762/turcomat.v12i3.1307. DOI: https://doi.org/10.17762/turcomat.v12i3.1307

3. Asef P, Padmanaban S, Lapthorn A. Modern Automotive Electrical Systems. wiley; 2023. 256 p. doi: 10.1002/9781119801078. DOI: https://doi.org/10.1002/9781119801078

4. Denton T. Automobile Mechanical and Electrical Systems. 2nd Edition. Routledge; 2017. 378 p. doi: 10.4324/9781315856636. DOI: https://doi.org/10.4324/9781315856636

5. Rahman RA, Suwandi A, Nurtanto M. Experimental investigation on the effect of thermophysical properties of a heat transfer fluid on pumping performance for a convective heat transfer system. Vol. 7, Journal of Thermal Engineering. 2021. p. 1628–39. doi: 10.18186/thermal.1025988. DOI: https://doi.org/10.18186/thermal.1025910

6. UNESCO. Global education Monitoring Report Summary 2023, Southeast Asia: Technology in education: A tool on whose terms? Global education Monitoring Report Summary 2023, Southeast Asia: Technology in education: A tool on whose terms? 2023. doi: 10.54676/esln1861. DOI: https://doi.org/10.54676/ESLN1861

7. Prianto E, Sunomo, Maryadi THT. Development of Power Electronic Practicum Units for Vocational Education. In Department of Electrical Engineering Education, Universitas Negeri Yogyakarta, Indonesia: IOP Publishing Ltd; 2021. doi: 10.1088/1742-6596/1737/1/012043 DOI: https://doi.org/10.1088/1742-6596/1737/1/012043

8. Nurtanto M. Designing ignition system based ergonomic teaching aid in vocational education: Minimizing fatigue factors during practice. Int J Sci Technol Res. 2019;8(11):300–3.

9. Khwanda MN, Kriek J. An evaluation of student’s understanding of DC circuit concepts through students’ written explanations. J Phys Conf Ser [Internet]. 2020;1512(1):12020. Available from: https://dx.doi.org/10.1088/1742-6596/1512/1/012020 DOI: https://doi.org/10.1088/1742-6596/1512/1/012020

10. Muslim M, Saputra HD, Setiawan MY, Martias M, Nasir M. The Influence of Project Based Learning on Student’s Intrinsic Learning Motivation. Invotek J Inov Vokasional Dan Teknol. 2021;21(2):105–18. doi: 10.24036/invotek.v21i2.915. DOI: https://doi.org/10.24036/invotek.v21i2.915

11. Hernández-Chávez M, Cortés-Caballero JM, Pérez-Martínez ÁA, Hernandez-Quintanar L, Roa-Tort K, Rivera-Fernández JD, et al. Development of Virtual Reality Automotive Lab for Training in Engineering Students. Sustainability. 2021;13(17):9776. doi: 10.3390/su13179776. DOI: https://doi.org/10.3390/su13179776

12. Hidayati K, Rahmawati A, Wijayanto DS. Development of Learning Media to Improve Critical Thinking Skills and Creativity of Vocational Students. Int J Soc Serv Res. 2024;4(03):716–24. doi: 10.46799/ijssr.v4i03.741. DOI: https://doi.org/10.46799/ijssr.v4i03.741

13. Richardo R, Dwiningrum SIA, Wijaya A, Retnawati H, Wahyudi A, Sholihah DA, et al. The Impact of STEM Attitudes and Computational Thinking on 21st-Century via Structural Equation Modelling. Int J Eval Res Educ. 2023;12(2):571. doi: 10.11591/ijere.v12i2.24232. DOI: https://doi.org/10.11591/ijere.v12i2.24232

14. Handoyono N, Purnomo S, Rabiman R. The Needs for Teaching Factory Learning in Motorcycle Tune-Up Practices in Mechanical Engineering Education. In: Proceedings of the 1st International Conference on Science and Technology for an Internet of Things. Yogyakarta: EAI; 2019. doi: 10.4108/eai.19-10-2018.2282526. DOI: https://doi.org/10.4108/eai.19-10-2018.2282526

15. Kholifah N, Sofyan H, Pardjono P, Sudira P, Nurtanto M. Explicating the Experience of Beginner Vocational Teachers. TEM J. 2021;10(2):719–23. doi: 10.18421/TEM102-28. DOI: https://doi.org/10.18421/TEM102-28

16. Setiadi H, Mursid R. Project-Based Learning Interactive Multimedia: Improving Basic Electrical and Electronics Learning Outcomes. In: International Journal of Computer Applications Technology and Research. 2023. p. 13–20. doi: 10.7753/ijcatr1207.1003. DOI: https://doi.org/10.7753/IJCATR1207.1003

17. Sriadhi S, Hamid A, Siagian S, Sutopo A, Adhitya WR. Virtual Multimedia Assisted Learning with Assignment Models to Improve the Competence of Electrical Protection Systems. TEM J. 2023;12(2):1110–7. doi: 10.18421/TEM122-57. DOI: https://doi.org/10.18421/TEM122-57

18. Muskhir M, Luthfi A, Julian R, Fortuna A. Exploring iSpring Suite for Android-Based Interactive Instructional Media in Electrical Lighting Installation Subject. Int J Interact Mob Technol. 2023;17(22):67–84. doi: 10.3991/ijim.v17i22.42625. DOI: https://doi.org/10.3991/ijim.v17i22.42625

19. Hamid MA, Nurtanto M, Desmira D, Setiawan D, Hakiki M, Fadli R. Technological Support To Foster Students’ Learning Experience In Electrical Measurement Class: A Mobile Learning-Based Hypermedia Approach. In: 2024 International Conference on TVET Excellence & Development (ICTeD). 2024. p. 177–82. doi: 10.1109/ICTeD62334.2024.10844631. DOI: https://doi.org/10.1109/ICTeD62334.2024.10844631

20. Razali N, Sumarwati S, Ismail ME, Abdullah MAA, Hashim S, Nurtanto M. Academic Integrity Elements using Technological Media Tools in Peer Assessment Implementation: Fuzzy Delphi. J Adv Res Des. 2025;131(1):17–25. doi: 10.37934/ard.131.1.1725. DOI: https://doi.org/10.37934/ard.131.1.1725

21. Azid N, Nur AHB, Md-Ali R, Isa ZC, Heong YM, Kiong TT. Curriculum Key-Players’ and Industries’ Thoughts: The Relevance of Automotive Case-Based Simulation Apps. Sage Open. 2024;14(3). doi: 10.1177/21582440241260558. DOI: https://doi.org/10.1177/21582440241260558

22. Placklé I, Könings KD, Jacquet W, Struyven K, Libotton A, Merriënboer JJG van, et al. Students’ Preferred Characteristics of Learning Environments in Vocational Secondary Education. Int J Res Vocat Educ Train. 2014;1(2):107–24. doi: 10.13152/ijrvet.1.2.2. DOI: https://doi.org/10.13152/IJRVET.1.2.2

23. Hamid MA, Permata E, Aribowo D, Darmawan IA, Nurtanto M, Laraswati S. Development of cooperative learning based electric circuit kit trainer for basic electrical and electronics practice. In: Journal of Physics: Conference Series. 2020. doi: 10.1088/1742-6596/1456/1/012047. DOI: https://doi.org/10.1088/1742-6596/1456/1/012047

24. Jatmoko D, Suyitno S, Rasul MS, Nurtanto M, Kholifah N, Masek A, et al. The Factors Influencing Digital Literacy Practice in Vocational Education: A Structural Equation Modeling Approach. Eur J Educ Res. 2023;12(2):1109–21. doi: 10.12973/eu-jer.12.2.1109. DOI: https://doi.org/10.12973/eu-jer.12.2.1109

25. Schwendimann BA, Wever B De, Hämäläinen R, Cattaneo AAP. The State-of-the-Art of Collaborative Technologies for Initial Vocational Education: A Systematic Literature Review. Int J Res Vocat Educ Train [Internet]. 2018 Jun 18;5(1):19–41. Available from: https://journals.sub.uni-hamburg.de/hup2/ijrvet/article/view/283 DOI: https://doi.org/10.13152/IJRVET.5.1.2

26. Rabiman R, Sudira P, Sofyan H, Nurtanto M. Practical Learning Media in Subject Maintenance of Chassis and Power (MCP) Based Online: Simple Learning Using Videos on YouTube. Int J Interact Mob Technol. 2021;15:130–45. doi: https://doi.org/10.3991/ijim.v15i03.14943. DOI: https://doi.org/10.3991/ijim.v15i03.14943

27. Ruslan R, Simanjuntak RR, Hidayat MA. Energy Efficiency Through Solar Panelled Mobile Workshop for Vocational Education Teaching Factory. In: Iop Conference Series Earth and Environmental Science. 2024. p. 12099. doi: 10.1088/1755-1315/1324/1/012099. DOI: https://doi.org/10.1088/1755-1315/1324/1/012099

28. Asplund S-B, Kilbrink N. Learning How (And How Not) to Weld: Vocational Learning in Technical Vocational Education. Scand J Educ Res. 2016;62(1):1–16. doi: 10.1080/00313831.2016.1188147. DOI: https://doi.org/10.1080/00313831.2016.1188147

29. Hussain S, Khan MQ. Student-Performulator: Predicting Students’ Academic Performance at Secondary and Intermediate Level Using Machine Learning. Ann Data Sci. 2021;10(3):637–55. doi: 10.1007/s40745-021-00341-0. DOI: https://doi.org/10.1007/s40745-021-00341-0

30. Zhou X. A conceptual review of the effectiveness of flipped learning in vocational learners’ cognitive skills and emotional states. Front Psychol. 2023;13(1039025). doi: 10.3389/fpsyg.2022.1039025. DOI: https://doi.org/10.3389/fpsyg.2022.1039025

31. Nurtanto M, Mutohhari F, Rozaq F, Suyitno S, Masek A. The Application of Innovation Visual Animation Media (VAM) at Electrical in Automotive Vocational Education. Vol. 2111, Journal of Physics: Conference Series. 2021. p. 12007. DOI: https://doi.org/10.1088/1742-6596/2111/1/012007

32. Saputro IN, Hamid MA, Nurtanto M, Majid NWA, Rohmantoro D. An Investigation of the Influence of the 5E-LC Model on The Learning Outcome and Practical Performance of Vocational School Students. J Tech Educ Train. 2025;17(1 Special Issue):32–44. doi: 10.30880/jtet.2025.17.01.003.

33. Hudin NS, Yi LK. Impacts of Service-Learning on Cultural Adaptation, Analytical Thinking, and Communication Skills of University Students. Cjmbe. 2022;1(1):29–39. doi: 10.53797/cjmbe.v1i1.7.2022. DOI: https://doi.org/10.53797/cjmbe.v1i1.7.2022

34. Prawita W, Prayitno BA, Sugiyarto S. Effectiveness of a Generative Learning-Based Biology Module to Improve the Analytical Thinking Skills of the Students With High and Low Reading Motivation. Int J Instr. 2019;12(1):1459–76. doi: 10.29333/iji.2019.12193a. DOI: https://doi.org/10.29333/iji.2019.12193a

35. Sudibyo E, Jatmiko B, Wıdodo W. The Effectiveness of CBL Model to Improve Analytical Thinking Skills the Students of Sport Science. Int Educ Stud. 2016;9(4):195. doi: 10.5539/ies.v9n4p195. DOI: https://doi.org/10.5539/ies.v9n4p195

36. Kamid K, Kurniawan DA, Nawahdani AM. Scientific Learning Model: Analytical Thinking and Process Skills in Mathematics. J Educ Res Eval. 2022;6(3):238–49. doi: 10.23887/jere.v6i3.49159. DOI: https://doi.org/10.23887/jere.v6i3.49159

37. Ismayati E, Muslim S, Kusumawati N, Rahmadyanti E, Hilmi MA, Wrahatnolo T. Critical Study of Research Results About TVET and TEFA’s Role in Social, Economic, and Education Development in the Country. Jetl (Journal Educ Teach Learn. 2020;5(1):106. doi: 10.26737/jetl.v5i1.1823. DOI: https://doi.org/10.26737/jetl.v5i1.1823

38. Basori B, Sajidan S, Akhyar M, Wiranto W. Analysis of Vocational Students’ Critical Thinking Skills Using the OER-Assisted Blended Learning. J Innov Educ Cult Res. 2023;4(2):264–70. doi: 10.46843/jiecr.v4i2.566. DOI: https://doi.org/10.46843/jiecr.v4i2.566

39. Nurtanto M, Widjanarko D, Sofyan H, Rabiman R, Triyono MB. Learning by creating: Transforming automotive electrical textual material into visual animation as a creative learning products (clp). Int J Sci Technol Res. 2019;8(10):1634–42.

40. Walid A, Sajidan S, Ramli M, Kusumah RGT. Construction of the Assessment Concept to Measure Students’ High Order Thinking Skills. J Educ Gift Young Sci. 2019;7(2):237–51. doi: 10.17478/jegys.528180. DOI: https://doi.org/10.17478/jegys.528180

41. Tong W, Zhang X, Zeng H, Pan J, Gong C, Zhang H. Reforming China’s Secondary Vocational Medical Education: Adapting to the Challenges and Opportunities of the AI Era. Jmir Med Educ. 2024;10:e48594–e48594. doi: 10.2196/48594. DOI: https://doi.org/10.2196/48594

42. Bryce D, Goldman RP, DeHaven M, Beal J, Bartley B, Nguyen T, et al. Round Trip: An Automated Pipeline for Experimental Design, Execution, and Analysis. Acs Synth Biol. 2022;11(2):608–22. doi: 10.1021/acssynbio.1c00305. DOI: https://doi.org/10.1021/acssynbio.1c00305

43. Drovandi C, Holmes C, McGree J, Mengersen K, Richardson S, Ryan E. Principles of Experimental Design for Big Data Analysis. Stat Sci. 2017;32(3). doi: 10.1214/16-sts604. DOI: https://doi.org/10.1214/16-STS604

44. Јаnkovic S, Kapo B, Sukalo A, Mašić I. Evaluation of Published Preclinical Experimental Studies in Medicine: Methodology Issues. Med Arch. 2019;73(5):298. doi: 10.5455/medarh.2019.73.298-302. DOI: https://doi.org/10.5455/medarh.2019.73.298-302

45. Alinaghi M, Bertram HC, Brunse A, Smilde AK, Westerhuis JA. Common and distinct variation in data fusion of designed experimental data. Metabolomics. 2020;16(1). doi: 10.1007/s11306-019-1622-2. DOI: https://doi.org/10.1007/s11306-019-1622-2

46. Jensen SM, Schaarschmidt F, Onofri A, Ritz C. Experimental Design Matters for Statistical Analysis: How to Handle Blocking. Pest Manag Sci. 2017;74(3):523–34. doi: 10.1002/ps.4773. DOI: https://doi.org/10.1002/ps.4773

47. Gu C, Liu W, Cui Y, Hanley N, OrNeill M, Lombardi F. A Flip-Flop Based Arbiter Physical Unclonable Function (APUF) Design With High Entropy and Uniqueness for FPGA Implementation. Ieee Trans Emerg Top Comput. 2021;9(4):1853–66. doi: 10.1109/tetc.2019.2935465. DOI: https://doi.org/10.1109/TETC.2019.2935465

48. Akhir M, Siburian J, Hasibuan MHE. A Study Comparison the Application of Discovery Learning and Problem Based Learning Models on the Critical Thinking Ability. Integr Sci Educ J. 2023;4(2):84–9. doi: 10.37251/isej.v4i2.390. DOI: https://doi.org/10.37251/isej.v4i2.390

49. Samadun S, Dwikoranto D. Improvement of Student’s Critical Thinking Ability Sin Physics Materials Through the Application of Problem-Based Learning. Ijorer Int J Recent Educ Res. 2022;3(5):534–45. doi: 10.46245/ijorer.v3i5.247. DOI: https://doi.org/10.46245/ijorer.v3i5.247

50. Bahri, Junaeda S, Misnah, Rahmatullah R, Asmunandar, Tati ADR, et al. Application of Problem-Based Learning Model at the State of 2 Majene First Middle School. SHS Web Conf. 2022;149:1008. doi: 10.1051/shsconf/202214901008. DOI: https://doi.org/10.1051/shsconf/202214901008

51. Azid N, Nur AHB, Md-Ali R, Isa ZC. Conceptualizing Case-Based Simulation Framework: Evidence From Electrical Technology in TVET Case Study. Int J Instr. 2023;16(1):1079–98. doi: 10.29333/iji.2023.16159a. DOI: https://doi.org/10.29333/iji.2023.16159a

52. Meier JM, Hesse P, Abele S, Renkl A, Glogger-Frey I. Video-based modeling examples and comparative self-explanation prompts for teaching a complex problem-solving strategy. J Comput Assist Learn. 2024;40(4):1852–70. doi: 10.1111/jcal.12991. DOI: https://doi.org/10.1111/jcal.12991

53. Anis SK, Masek A, Nurtanto M, Kholifah N. Nominal group technique application towards design of components and elements of non-digital game framework. Int J Eval Res Educ. 2022;11(1):213. doi: 10.11591/ijere.v11i1.22164. DOI: https://doi.org/10.11591/ijere.v11i1.22164

54. Widjanarko D, Khumaedi M, Kurniawan A, Santosa T. Effectiveness of Question-Based Instructional Video (QBIV) for an Automotive Engineering Study Program. Int J Emerg Technol Learn. 2024;19(03):56–66. doi: 10.3991/ijet.v19i03.47785. DOI: https://doi.org/10.3991/ijet.v19i03.47785

55. Warju W, Ariyanto SR, Soeryanto S, Hidayatullah RS, Nurtanto M. Practical Learning Innovation: Real Condition Video-Based Direct Instruction Model in Vocational Education. Vol. 6, Journal of Educational Science and Technology (EST). 2020. p. 79–91. DOI: https://doi.org/10.26858/est.v6i1.12665

56. Nurtanto M, Sofyan H, Fawaid M, Rabiman R. Problem-Based Learning (PBL) in Industry 4.0: Improving learning quality through character-based literacy learning and life career skill (LL-LCS) [Internet]. Vol. 7, Universal Journal of Educational Research. 2019. p. 2487–94. DOI: https://doi.org/10.13189/ujer.2019.071128

57. Zhao Y, Ko J. How Do Teaching Quality and Pedagogical Practice Enhance Vocational Student Engagement? A Mixed-Method Classroom Observation Approach. Int J Educ Manag. 2020;34(6):987–1000. doi: 10.1108/ijem-11-2019-0393. DOI: https://doi.org/10.1108/IJEM-11-2019-0393

58. Wang Y, Liang C, Li S, Yang P, Hu Y. How Does the Quality of Education Affect the Employment Quality of Secondary Vocational School Graduates? Adv Soc Behav Res. 2024;6(1):1–14. doi: 10.54254/2753-7102/6/2024043. DOI: https://doi.org/10.54254/2753-7102/6/2024043

59. Nurtanto M, Nurhaji S, Widjanarko D, Wijaya MBR, Sofyan H. Comparison of scientific literacy in engine tune-up competencies through guided problem-based learning and non-integrated problem-based learning in vocational education. In: Journal of Physics: Conference Series. 2018. p. 1–7. doi: 10.1088/1742-6596/1114/1/012038. DOI: https://doi.org/10.1088/1742-6596/1114/1/012038

60. Omar MK, Bakar A, Rashid AM. Employability Skill Acquisition Among Malaysian Community College Students. J Soc Sci. 2012;8(3):472–8. doi: 10.3844/jssp.2012.472.478. DOI: https://doi.org/10.3844/jssp.2012.472.478

61. Samani M, Sunwinarti S, Putra BAW, Rahmadian R, Rohman JN. Learning Strategy to Develop Critical Thinking, Creativity, and Problem-Solving Skills for Vocational School Students. J Pendidik Teknol dan Kejuru. 2019;25(1):36–42. doi: 10.21831/jptk.v25i1.22574. DOI: https://doi.org/10.21831/jptk.v25i1.22574

62. Sule SY, Lare OJ, Oguntokun JE. Exploring the Efficacy of Vocational Training Programs in Motor Vehicle and Mechanic Works Trade: A Case Study of Science and Technical Colleges in Northeast Nigeria. Int J Of Educ Manag Technol. 2024;2(1):63–80. doi: 10.58578/ijemt.v2i1.2859. DOI: https://doi.org/10.58578/ijemt.v2i1.2859

63. Shakour K, Ransom T, Gallagher E, Johnson K, Short R, Beck JS, et al. Learning From the COVID‐19 Pandemic: Improving Academic Continuity in Workforce Development Programs. New Dir Community Coll. 2024;2024(205):143–51. doi: 10.1002/cc.20619. DOI: https://doi.org/10.1002/cc.20619

64. Kholifah N, Kurdi MS, Nurtanto M, Mutohhari F. The role of teacher self-efficacy on the instructional quality in 21st century : A study on vocational teachers, Indonesia. Int J Eval Res Educ. 2023;12(2):998–1006. doi: 10.11591/ijere.v12i2.23949. DOI: https://doi.org/10.11591/ijere.v12i2.23949

65. Nurtanto M, Adyani A, Aziz MKNA, Umar N, Sutrisno VLP, Nawanksari S, et al. Educational Strategies for Addressing Student Anxiety and Depression through Artificial Intelligence: A Bibliometric and Conceptual Analysis. Salud, Cienc y Tecnol. 2025;5(1669):1–15. doi: 10.56294/saludcyt20251669. DOI: https://doi.org/10.56294/saludcyt20251669

66. Parr JV V, Wright DJ, Uiga L, Marshall B, Mohamed MO, Wood G. A Scoping Review of the Application of Motor Learning Principles to Optimize Myoelectric Prosthetic Hand Control. Prosthet Orthot Int. 2021;46(3):274–81. doi: 10.1097/pxr.0000000000000083. DOI: https://doi.org/10.1097/PXR.0000000000000083

Downloads

Published

2025-07-29

How to Cite

1.
Perdana Sutrisno VL, Pardjono P, Wagiran W, Nurtanto M, Ratnawati D, Marganingsih A, et al. Simulation-Based Diagnostic Learning with Diagnostic Trouble Box (DTB): Enhancing Analytical Thinking Skills in Vocational Automotive Education. Salud, Ciencia y Tecnología [Internet]. 2025 Jul. 29 [cited 2025 Nov. 28];5:1956. Available from: https://sct.ageditor.ar/index.php/sct/article/view/1956