Relevansi teori teknologi pendidikan dalam menjawab tantangan era industri 4.0 di pendidikan vokasi

Abstract

Revolusi Industri 4.0 membawa transformasi signifikan pada dunia kerja, yang pada gilirannya menuntut adaptasi dalam sistem pendidikan vokasi. Artikel ini bertujuan untuk mengeksplorasi tantangan pedagogis yang dihadapi pendidikan vokasi di era ini dan menganalisis relevansi teori teknologi pendidikan (EdTech) dalam meresponsnya. Melalui tinjauan pustaka sistematis dan analisis konseptual, penelitian ini mengidentifikasi tantangan kunci seperti kebutuhan rapid re-skilling, penyelesaian masalah kompleks, kolaborasi manusia-mesin, literasi data, dan pembelajaran mandiri. Hasil analisis menunjukkan bahwa teori EdTech tradisional seperti Behaviorisme, Kognitivisme, dan Konstruktivisme masih relevan namun tidak memadai jika diterapkan secara tunggal untuk menjawab seluruh kompleksitas tantangan tersebut. Sebaliknya, teori yang lebih baru seperti Konektivisme dan Heutagogy menawarkan pendekatan yang lebih sesuai untuk mendukung pembelajaran seumur hidup dan otonomi siswa. Sebagai novelty, artikel ini mengusulkan sebuah kerangka teoretis hibrid yang mengintegrasikan prinsip-prinsip dari teori lama dan baru untuk menciptakan pendekatan pedagogis yang lebih komprehensif dan adaptif. Implikasinya menekankan pergeseran peran guru menjadi fasilitator dan pentingnya landasan teori yang kuat dalam adopsi teknologi untuk memastikan efektivitas pembelajaran dan kesiapan kerja lulusan vokasi di tengah dinamika Industri 4.0

References
  1. Abdalla, H. (2022). A brief survey on big data: technologies, terminologies and data-intensive applications. https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-022-00659-3
  2. Acemoğlu, D., Anderson, G., Beede, D., Buffington, C., Childress, E., Dinlersoz, E., Foster, L., Goldschlag, N., Haltiwanger, J., Kroff, Z., Restrepo, P., & Zolas, N. (2023). Advanced Technology Adoption: Selection or Causal Effects?. https://doi.org/10.1257/pandp.20231037
  3. Agonács, N. & Matos, J. (2019). Heutagogy and self-determined learning: a review of the published literature on the application and implementation of the theory. https://doi.org/10.1080/02680513.2018.1562329
  4. Almulla, M. (2020). The Effectiveness of the Project-Based Learning (PBL) Approach as a Way to Engage Students in Learning. https://doi.org/10.1177/2158244020938702
  5. Ariansyah, K., Wismayanti, Y., Savitri, R., Listanto, V., Aswin, A., Ahad, M. P., & Cahyarini, B. (2024). Comparing labor market performance of vocational and general school graduates in Indonesia: insights from stable and crisis conditions. https://ervet-journal.springeropen.com/counter/pdf/10.1186/s40461-024-00160-6
  6. Balalle, H. (2025). Learning beyond realities: exploring virtual reality, augmented reality, and mixed reality in higher education—a systematic literature review. https://link.springer.com/content/pdf/10.1007/s44217-025-00559-7.pdf
  7. Bekkum, M., Boer, M., Harmelen, F., Meyer, A., & Teije, A. (2021). Modular design patterns for hybrid learning and reasoning systems. https://link.springer.com/content/pdf/10.1007/s10489-021-02394-3.pdf
  8. Berger, E., Fehr, E., Hermes, H., Schunk, D., & Winkel, K. (2024). The Impact of Working-Memory Training on Children’s Cognitive and Noncognitive Skills. https://doi.org/10.1086/732884
  9. Bettiol, M., Capestro, M., Maria, E., & Ganau, R. (2023). Is this time different? How Industry 4.0 affects firms’ labor productivity. https://link.springer.com/content/pdf/10.1007/s11187-023-00825-8.pdf
  10. Billett, S. (2020). Perspectives on enhancing the standing of vocational education and the occupations it serves. https://www.tandfonline.com/doi/pdf/10.1080/13636820.2020.1749483?needAccess=true
  11. Bozkurt, A. (2020). Educational Technology Research Patterns in the Realm of the Digital Knowledge Age. https://doi.org/10.5334/jime.570
  12. Brenner, C. (2022). Self-regulated learning, self-determination theory and teacher candidates’ development of competency-based teaching practices. https://slejournal.springeropen.com/counter/pdf/10.1186/s40561-021-00184-5
  13. Cai, J. & Kosaka, M. (2024). Conceptualizing Technical and Vocational Education and Training as a Service Through Service-Dominant Logic. https://journals.sagepub.com/doi/pdf/10.1177/21582440241240847
  14. Chandanani, M., Laidlaw, A., & Brown, C. (2025). Extended reality and computer-based simulation for teaching situational awareness in undergraduate health professions education: a scoping review. https://advancesinsimulation.biomedcentral.com/counter/pdf/10.1186/s41077-025-00343-5
  15. Consoli, T., Schmitz, M., Antonietti, C., Gonon, P., Cattáneo, A., & Petko, D. (2024). Quality of technology integration matters: Positive associations with students’ behavioral engagement and digital competencies for learning. https://doi.org/10.1007/s10639-024-13118-8
  16. Cullen, S. & Oppenheimer, D. (2024). Choosing to learn: The importance of student autonomy in higher education. https://www.science.org/doi/pdf/10.1126/sciadv.ado6759?download=true
  17. Damelang, A. & Otto, M. (2023). Who is Replaced by Robots? Robotization and the Risk of Unemployment for Different Types of Workers. https://journals.sagepub.com/doi/pdf/10.1177/07308884231162953
  18. Datta, A., Coates, S., Rossiter, A., & Krishnamoorti, R. (2024). Reskilling and Upskilling for Decarbonization: Analyzing Micro-Credential Programs for Energy Workforce Development. https://doi.org/10.1080/07377363.2024.2377777
  19. Douglas, D. (2025). Researchers’ perceptions of automating scientific research. https://doi.org/10.1007/s00146-025-02190-4
  20. Dron, J. & Anderson, T. (2023). Pedagogical Paradigms in Open and Distance Education. https://link.springer.com/content/pdf/10.1007/978-981-19-2080-6_9.pdf
  21. Duan, J., Xie, K., & Zhao, Q. (2024). A personal social knowledge network (PSKN) facilitates learners’ wayfinding and its differences in behavior patterns between high and low performers in connectivist learning. https://doi.org/10.1186/s41239-024-00454-5
  22. Ehlers, U. (2020). Future Skills. https://link.springer.com/content/pdf/10.1007/978-3-658-29297-3.pdf?pdf=button
  23. Elahi, M., Afolaranmi, S., Lastra, J. L., & García, J. A. (2023). A comprehensive literature review of the applications of AI techniques through the lifecycle of industrial equipment. https://link.springer.com/content/pdf/10.1007/s44163-023-00089-x.pdf
  24. Fishbach, A. & Woolley, K. (2021). The Structure of Intrinsic Motivation. https://www.annualreviews.org/doi/pdf/10.1146/annurev-orgpsych-012420-091122
  25. Frutos‐Belizón, J., García-Carbonell, N., Guerrero-Alba, F., & Sánchez‐Gardey, G. (2024). An empirical analysis of individual and collective determinants of international research collaboration. https://link.springer.com/content/pdf/10.1007/s11192-024-04999-0.pdf
  26. Gillaspy, E. & Vasilica, C. (2021). Developing the digital self-determined learner through heutagogical design. https://www.tandfonline.com/doi/pdf/10.1080/23752696.2021.1916981?needAccess=true
  27. Godsk, M. & Møller, K. (2024). Engaging students in higher education with educational technology. https://link.springer.com/content/pdf/10.1007/s10639-024-12901-x.pdf
  28. Goeritno, A., Prasetiya, Y., Yuhefizar, Y., Muhathir, M., Lestari, S., & Azama, I. (2023). Prototyping an IoT-Platform Embedded Device to Prevent the Failure of the Battery System at the Kedungbadak-Bogor Substation. https://www.iieta.org/download/file/fid/102959
  29. Gomes, A. & Dias, J. (2024). Digital Divide in the European Union: A Typology of EU Citizens. https://doi.org/10.1007/s11205-024-03452-2
  30. Guhl, D., Paetz, F., Wagner, U., & Wedel, M. (2024). Predicting and optimizing marketing performance in dynamic markets. https://link.springer.com/content/pdf/10.1007/s00291-024-00755-1.pdf
  31. Hemmer, P., Schemmer, M., Kühl, N., Vössing, M., & Satzger, G. (2024). Complementarity in Human-AI Collaboration: Concept, Sources, and Evidence. https://arxiv.org/pdf/2404.00029
  32. Hernández, E., Senna, P., Silva, D., Rebelo, R., Barros, A., & Toscano, C. (2019). Implementing RAMI4.0 in Production - A Multi-case Study. https://doi.org/10.1007/978-3-030-29041-2_6
  33. Hu, F., Zou, X., Hao, H., Hou, P., & Huang, Y. (2024). Research and application of simulation and optimization for CNC machine tool machining process under data semantic model reconstruction. https://doi.org/10.1007/s00170-024-13415-z
  34. Hummelsheim, S. & Baur, M. (2014). The German dual system of initial vocational education and training and its potential for transfer to Asia. https://doi.org/10.1007/s11125-014-9311-4
  35. Jamarani, A., Haddadi, S., Sarvizadeh, R., Kashani, M., Akbari, M., & Moradi, S. (2024). Big data and predictive analytics: A systematic review of applications. https://link.springer.com/content/pdf/10.1007/s10462-024-10811-5.pdf
  36. Jenssen, E. & Haara, F. (2024). High-quality practicum – according to teacher education students on their practicum at partnership schools. https://www.tandfonline.com/doi/pdf/10.1080/02619768.2024.2370892?needAccess=true
  37. Johnsen, M. M., Sjølie, E., & Johansen, V. (2023). Learning to Collaborate in a Project-based Graduate Course: A Multilevel Study of Student Outcomes. https://link.springer.com/content/pdf/10.1007/s11162-023-09754-7.pdf
  38. Kee, T., Zhang, H., & King, R. (2023). An empirical study on immersive technology in synchronous hybrid learning in design education. https://link.springer.com/content/pdf/10.1007/s10798-023-09855-5.pdf
  39. Kim, Y., Kim, D., Choi, J., Park, J., Oh, N., & Park, D. (2024). A survey on integration of large language models with intelligent robots. https://doi.org/10.1007/s11370-024-00550-5
  40. Knyazev, G. (2023). A Paradigm Shift in Cognitive Sciences?. https://doi.org/10.1007/s11055-023-01483-9
  41. Kumar, M., Manglani, H., & Jadhav, J. (2024). Unveiling Research Trends on the Sustainable Development Goals: A Systematic Bibliometric Review. https://iieta.org/download/file/fid/130522
  42. Kumar, S., Tiwari, P., & Zymbler, M. (2019). Internet of Things is a revolutionary approach for future technology enhancement: a review. https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-019-0268-2
  43. Labadze, L. & Grigolia, M. (2023). Role of AI chatbots in education: systematic literature review. https://doi.org/10.1186/s41239-023-00426-1
  44. Laskowski, R., Chybowski, L., & Gawdzińska, K. (2015). An Engine Room Simulator as a Tool for Environmental Education of Marine Engineers. https://doi.org/10.1007/978-3-319-16528-8_29
  45. Lee, S., Chae, J., Jeon, H., Kim, T., Hong, Y., Um, D., Kim, T., & Park, K. (2025). Cyber-Physical AI: Systematic Research Domain for Integrating AI and Cyber-Physical Systems. https://dl.acm.org/doi/pdf/10.1145/3721437
  46. Leeder, T. (2022). Behaviorism, Skinner, and Operant Conditioning: Considerations for Sport Coaching Practice. https://www.tandfonline.com/doi/pdf/10.1080/08924562.2022.2052776?needAccess=true
  47. Likovič, A. & Rojko, K. (2022). E-Learning and a Case Study of Coursera and edX Online Platforms. https://sciendo.com/pdf/10.2478/rsc-2022-0008
  48. Liu, X., Park, J., Hymer, C., & Thatcher, S. M. (2018). Multidimensionality: A Cross-Disciplinary Review and Integration. https://doi.org/10.1177/0149206318807285
  49. Masrifah, N. & Sudira, P. (2020). Redesign of Vocational Education Curriculum in Industrial Digitalization 4.0. https://doi.org/10.1145/3401861.3401865
  50. Mella-Norambuena, J., Chiappe, A., & Quintana, M. G. (2024). Theoretical and empirical models underlying the teaching use of LMS platforms in higher education: a systematic review. https://doi.org/10.1007/s40692-024-00336-9
  51. Michelene, T. & Wylie, R. (2014). The ICAP Framework: Linking Cognitive Engagement to Active Learning Outcomes. https://doi.org/10.1080/00461520.2014.965823
  52. Mol, M., Belfi, B., & Bakk, Z. (2024). Unravelling the skills of data scientists: A text mining analysis of Dutch university master programs in data science and artificial intelligence. https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0299327&type=printable
  53. Mudiyanselage, S., Nguyen, P., Rajabi, M., & Akhavian, R. (2021). Automated Workers’ Ergonomic Risk Assessment in Manual Material Handling Using sEMG Wearable Sensors and Machine Learning. https://www.mdpi.com/2079-9292/10/20/2558/pdf?version=1634728859
  54. Niu, Q., Liu, J., Bi, Z., Feng, P., Peng, B., Chen, K., & Li, M. (2024). Large Language Models and Cognitive Science: A Comprehensive Review of Similarities, Differences, and Challenges. https://arxiv.org/pdf/2409.02387
  55. Paramitasari, N., Khoirunurrofik, K., Mahi, B., & Hartono, D. (2024). Charting vocational education: impact of agglomeration economies on job–education mismatch in Indonesia. https://doi.org/10.1007/s41685-024-00333-x
  56. Purohit, M., Svitkina, Z., & Kumar, R. (2024). Improving Online Algorithms via ML Predictions. https://arxiv.org/pdf/2407.17712
  57. Ravasi, D., Zhu, J., Wan, W., Dorobantu, S., & Gruber, M. (2024). What Makes Research Collaborations Successful? Advice from AMJ Authors. https://doi.org/10.5465/amj.2024.4003
  58. Rawat, D., alami, H., & Hagos, D. (2024). Metaverse Survey & Tutorial: Exploring Key Requirements, Technologies, Standards, Applications, Challenges, and Perspectives. https://arxiv.org/pdf/2405.04718
  59. Rijwani, T., Kumari, S., Srinivas, R., Abhishek, K., Iyer, G., Vara, H., Dubey, S., Revathi, V., & Gupta, M. (2024). Industry 5.0: a review of emerging trends and transformative technologies in the next industrial revolution. https://doi.org/10.1007/s12008-024-01943-7
  60. Rudolph, M., Kurz, S., & Rakitsch, B. (2024). Hybrid modeling design patterns. https://mathematicsinindustry.springeropen.com/counter/pdf/10.1186/s13362-024-00141-0
  61. Sasaki, H. (2022). Special feature: economic dynamics—growth, capital, labor, technology, and money. https://link.springer.com/content/pdf/10.1007/s40844-022-00241-9.pdf
  62. Sauer, P. & Seuring, S. (2023). How to conduct systematic literature reviews in management research: a guide in 6 steps and 14 decisions. https://link.springer.com/content/pdf/10.1007/s11846-023-00668-3.pdf
  63. Shih, C., Chou, J., Reijers, N., & Kuo, T. (2016). Designing CPS/IoT applications for smart buildings and cities. https://doi.org/10.1049/iet-cps.2016.0025
  64. Siam, M. S., Ahn, H., Liu, L., Alam, S., Shen, H., Cao, Z., Shroff, N., Krishnamachari, B., Srivastava, M., & Zhang, M. (2024). Artificial Intelligence of Things: A Survey. https://dl.acm.org/doi/pdf/10.1145/3690639
  65. Subiyantoro, H., Tarziraf, A., & Asmara, A. (2023). The Role of Vocational Education as the Key to Economic Development in Indonesia. http://eudl.eu/pdf/10.4108/eai.28-10-2023.2341745
  66. Sui-Ni, N. (2023). Peran Pemerintah Pusat dan Daerah dalam Menyediakan Pendidikan Dasar Bermutu untuk Mewujudkan Visi Indonesia 2045. https://arxiv.org/pdf/2302.12837
  67. Suleiman, Z., Shaikholla, S., Dikhanbayeva, D., Shehab, E., & Türkyılmaz, A. (2022). Industry 4.0: Clustering of concepts and characteristics. https://www.tandfonline.com/doi/pdf/10.1080/23311916.2022.2034264?needAccess=true
  68. Szukits, Á. & Móricz, P. (2023). Towards data-driven decision making: the role of analytical culture and centralization efforts. https://link.springer.com/content/pdf/10.1007/s11846-023-00694-1.pdf
  69. Tong, D., Wu, L., & Evans, J. (2021). Low-skilled Occupations Face the Highest Upskilling Pressure. https://arxiv.org/pdf/2101.11505
  70. Tour, E. (2016). Teachers' personal learning networks (PLNs): exploring the nature of self‐initiated professional learning online. https://doi.org/10.1111/lit.12101
  71. Tynchenko, Y., Gantimurov, A., Кукарцев, В., Gladkov, A., & Бородулин, А. (2024). Data Analysis Methods: Comparative Review and Selection of the Best Approach. https://doi.org/10.1007/978-3-031-70595-3_18
  72. Vogel, O. & Hunecke, M. (2023). Fostering knowledge integration through individual competencies: the impacts of perspective taking, reflexivity, analogical reasoning and tolerance of ambiguity and uncertainty. https://link.springer.com/content/pdf/10.1007/s11251-023-09653-5.pdf
  73. Widayati, A., MacCallum, J., & Woods‐McConney, A. (2021). Teachers’ perceptions of continuing professional development: a study of vocational high school teachers in Indonesia. https://www.tandfonline.com/doi/pdf/10.1080/13664530.2021.1933159?needAccess=true
  74. Wijnia, L., Noordzij, G., Arends, L., Rikers, R. M. J., & Loyens, S. M. (2024). The Effects of Problem-Based, Project-Based, and Case-Based Learning on Students’ Motivation: a Meta-Analysis. https://link.springer.com/content/pdf/10.1007/s10648-024-09864-3.pdf
  75. Xu, Y. & Xu, R. (2022). Research on Interpolation and Data Fitting: Basis and Applications. https://arxiv.org/pdf/2208.11825
  76. Xue, Y., Rehman, S., Altalbe, A., Rehman, E., & Shahiman, M. (2024). Digital literacy as a catalyst for academic confidence: exploring the interplay between academic self-efficacy and academic procrastination among medical students. https://bmcmededuc.biomedcentral.com/counter/pdf/10.1186/s12909-024-06329-7
  77. Yang, F. & Gu, S. (2021). Industry 4.0, a revolution that requires technology and national strategies. https://link.springer.com/content/pdf/10.1007/s40747-020-00267-9.pdf
  78. Yang, C., Zhang, J., Hu, Y., Yang, X., Chen, M., Shan, M., & Li, L. (2024). The impact of virtual reality on practical skills for students in science and engineering education: a meta-analysis. https://stemeducationjournal.springeropen.com/counter/pdf/10.1186/s40594-024-00487-2
  79. Yao, D. & Lin, J. (2025). Cognitive enhancement through competency-based programming education: a 12-year longitudinal study. https://link.springer.com/content/pdf/10.1007/s10639-025-13582-w.pdf
  80. Ying, W., Xu, Z., Lou, J., & Chen, K. (2023). Factors influencing the complex problem-solving skills in reflective learning: results from partial least square structural equation modeling and fuzzy set qualitative comparative analysis. https://bmcmededuc.biomedcentral.com/counter/pdf/10.1186/s12909-023-04326-w
  81. Yu, T., Yan, X., & Jin, Y. (2024). Vocational Education in China. https://doi.org/10.1007/978-981-97-7415-9_8
  82. Zheng, D., Du, L., Su, J., Tian, Y., Zhu, Y., Zhang, J., Lei, W., Zhang, N., & Chen, H. (2025). Knowledge Augmented Complex Problem Solving with Large Language Models: A Survey. https://arxiv.org/pdf/2505.03418.