The potential of artificial intelligence in vocational education research and development: A bibliometric study
DOI:
https://doi.org/10.21831/jpv.v15i1.77873Keywords:
Artificial Intelligence, Bibliometric Analysis, Research Trends, Vocational Education, VOSviewerAbstract
Artificial Intelligence (AI) is emerging as a revolutionary force that is changing how we interact and work and redefining the global education landscape, especially Vocational Education (VE). AI is an opportunity to develop learning research and good vocational Education. However, this opportunity has not been correctly utilized because not all educators can develop research and AI-based learning content well. This article reveals opportunities for current and future research development related to AI and vocational Education through bibliometric analysis. The database comes from Scopus, and 159 articles were analyzed from 2014 to 2023. Bibliometric analysis of documents, including author name, journal network, country, and keywords, is visualized using the VOSviewer program. The findings reveal three key insights: (1) research remains concentrated in vocational health, with limited exploration in other sectors such as engineering, tourism, and agriculture; (2) international collaboration is still weak, despite strong potential between countries with high and emerging publication rates; and (3) keyword clusters highlight Apprenticeship, Students, Artificial Intelligence, and Engineering Education as the main thematic areas. These insights form a roadmap for future research that emphasizes diversifying AI applications across vocational sectors, fostering cross-border collaboration, and developing innovative themes around curricula, personalized learning, and simulation-based training. Despite limitations related to database and language scope, this study offers strategic directions for advancing AI in VE research and strengthening its contributions to global vocational education development.
References
Aggarwal, A., & Aggarwal, G. (2021). New Directions for Apprenticeships. In S. Ra, S. Jagannathan, & R. Maclean (Eds.), Powering a Learning Society During an Age of Disruption (Vol. 58, pp. 211–226). Springer Nature Singapore. https://doi.org/10.1007/978-981-16-0983-1_15
Ahn, C. (2023). Exploring ChatGPT for information of cardiopulmonary resuscitation. Resuscitation, 185, 109729. https://doi.org/10.1016/j.resuscitation.2023.109729
Avis, J. (2018). Socio-technical imaginary of the fourth industrial revolution and its implications for vocational education and training: A literature review. Journal of Vocational Education & Training, 1–27. https://doi.org/10.1080/13636820.2018.1498907
Bush, C. L., Blumberg, J. B., El-Sohemy, A., Minich, D. M., Ordovás, J. M., Reed, D. G., & Behm, V. A. Y. (2020). Toward the Definition of Personalized Nutrition: A Proposal by The American Nutrition Association. Journal of the American College of Nutrition, 39(1), 5–15. https://doi.org/10.1080/07315724.2019.1685332
Çapşek, M. F., & Karaci, A. (2022). Computer Control with Face and Eye Movements Using Deep Learning and Image Processing Methods. El-Cezeri Fen ve Mühendislik Dergisi. https://doi.org/10.31202/ecjse.1131377
Cheng, X., & Tang, Z. (2023). Research on the Promotion of Higher Vocational Labor Education Reform by Artificial Intelligence in the Era of Digitalization. 2023 13th International Conference on Information Technology in Medicine and Education (ITME), 829–832. https://doi.org/10.1109/ITME60234.2023.00170
Cheng, Y., & Liang, Y. S. (2023). The Development of Artificial Intelligence in Career Initiation Education and Implications for China. European Journal of Artificial Intelligence and Machine Learning, 2(4), 4–10. https://doi.org/10.24018/ejai.2023.2.4.32
Chiang, T. (2021). Estimating the Artificial Intelligence Learning Efficiency for Civil Engineer Education: A Case Study in Taiwan. Sustainability, 13(21), 11910. https://doi.org/10.3390/su132111910
Coelho, H., & Primo, T. T. (2017). Exploratory apprenticeship in the digital age with AI tools. Progress in Artificial Intelligence, 6(1), 17–25. https://doi.org/10.1007/s13748-016-0100-6
Squicciarini, M., & Nachtigall, H. (2021). Demand for AI skills in jobs: Evidence from online job postings. OECD Science, Technology and Industry Working Papers, 2021(3), 1-74.
Dewantara, K. A. K., Laksana, I. P. Y., Kartika, N. P. R. T. A., & Saraswati, H. (2024). A Systematic Review of AI-Powered Tools in English Language Learning for Vocational Students. International Journal of Natural Science and Engineering, 8(3), 201-214.
Durak, G., Çankaya, S., Özdemir, D., & Can, S. (2024). Artificial Intelligence in Education: A Bibliometric Study on Its Role in Transforming Teaching and Learning. The International Review of Research in Open and Distributed Learning, 25(3), 219-244. https://doi.org/ 10.19173/irrodl.v25i3.7757
Dziurka, M., Machul, M., Ozdoba, P., Obuchowska, A., Kotowski, M., Grzegorczyk, A., Pydyś, A., & Dobrowolska, B. (2022). Clinical Training during the COVID-19 Pandemic: Experiences of Nursing Students and Implications for Education. International Journal of Environmental Research and Public Health, 19(10), 6352. https://doi.org/10.3390/ijerph19106352
Fan, Y., Zheng, H., Ebonite, R. S., Asis, W. R. D., & Juanatas, R. A. (2024). Overview and developmental analysis of China’s technical and vocational education and training. International Journal of Innovative Research and Scientific Studies, 7(1), 251–260. https://doi.org/10.53894/ijirss.v7i1.2606
Galung, E. A. H., Sudira, P., Anwar, C., & Shodiq, S. (2024, July). Research trends of artificial intelligence in vocational education: A bibliometric analysis (2001-2023). In AIP Conference Proceedings (Vol. 3145, No. 1, p. 030030). AIP Publishing LLC.
Glänzel, W., & Schubert, A. (2004). Analyzing scientific networks through co-authorship. In H. F. Moed, W. Glänzel, & U. Schmoch (Eds.), Handbook of Quantitative Science and Technology Research (pp. 257–276). Springer. https://doi.org/10.1007/1-4020-2755-9_12
Hassan, R. H., Hassan, M. T., Naseer, S., Khan, Z., & Jeon, M. (2021). ICT Enabled TVET Education: A Systematic Literature Review. IEEE Access, 9, 81624–81650. https://doi.org/10.1109/ACCESS.2021.3085910
Heck, P., & Schouten, G. (2020). Turning Software Engineers into AI Engineers (Version 2). arXiv. https://doi.org/10.48550/ARXIV.2011.01590
Jiang, B. (2022). Research on The Application of Chinese Traditional Culture Teaching in Higher Vocational Education. Educational Sciences: Theory and Practice, 22(2). https://doi.org/10.12738/jestp.2022.2.0001
Kalpathy-Cramer, J., De Herrera, A. G. S., Demner-Fushman, D., Antani, S., Bedrick, S., & Müller, H. (2015). Evaluating performance of biomedical image retrieval systems—An overview of the medical image retrieval task at ImageCLEF 2004–2013. Computerized Medical Imaging and Graphics, 39, 55–61. https://doi.org/10.1016/j.compmedimag.2014.03.004
Kong, M., Yu, F., & Zhang, Z. (2024). Research on Artificial Intelligence Enabling High-Quality Development of Vocational Education. Applied Mathematics and Nonlinear Sciences, 9(1), 20231346. https://doi.org/10.2478/amns.2023.2.01346
Li, X., & Chen, Y. (2022). Mapping the knowledge domain of artificial intelligence in education: A bibliometric and co-citation analysis. Education and Information Technologies, 27, 1473–1495. https://doi.org/10.1007/s10639-021-10655-4
Mackey, B. P., Garabet, R., Maule, L., Tadesse, A., Cross, J., & Weingarten, M. (2024). Evaluating ChatGPT-4 in medical education: An assessment of subject exam performance reveals limitations in clinical curriculum support for students. Discover Artificial Intelligence, 4(1), 38. https://doi.org/10.1007/s44163-024-00135-2
Mulyana, E., Hakimi, R., & Hendrawan. (2018). Bringing Automation to the Classroom: A ChatOps-Based Approach. 2018 4th International Conference on Wireless and Telematics (ICWT), 1–6. https://doi.org/10.1109/ICWT.2018.8527810
Muttaqin, M. F., Sukrawan, Y., & Rosyadi, M. I. (2024). Exploring the Role of Artificial Intelligence in Learning Media for Vocational Education: A Systematic Literature Review. Journal of Vocational Education Studies, 7(2), 181-190. https://doi.org/10.12928/joves.v7i2.10364
Ni, L., Huang, Q., Ye, J., Hu, B., Zhang, N., Chang, X., & Su, Z. (2022). Vocational Education Development Model Based on Intelligent Management System. 2022 11th International Conference on Educational and Information Technology (ICEIT), 76–79. https://doi.org/10.1109/ICEIT54416.2022.9690746
Peeken, J. C., Bernhofer, M., Wiestler, B., Goldberg, T., Cremers, D., Rost, B., Wilkens, J. J., Combs, S. E., & Nüsslin, F. (2018). Radiomics in radiooncology – Challenging the medical physicist. Physica Medica, 48, 27–36. https://doi.org/10.1016/j.ejmp.2018.03.012
Permana, A. A. J., & Pradnyana, G. A. (2019). Recommendation Systems for internship place using artificial intelligence based on competence. Journal of Physics: Conference Series, 1165, 012007. https://doi.org/10.1088/1742-6596/1165/1/012007
Rafiq, A. A., Triyono, M. B., Djatmiko, I. W., & Anggraeni, P. (2024). Engineering Education’s Potential for Virtual Reality Research and Development from 2012-2022: A Bibliometric Study. Journal of Scientometric Research, 13(1), 317–332. https://doi.org/10.5530/jscires.13.1.26
Ran, Q., & Han, D. (2023). Application of Artificial Intelligence to Deep Learning in Vocational Education. 2023 IEEE International Conference on Electrical, Automation and Computer Engineering (ICEACE), 1024–1028. https://doi.org/10.1109/ICEACE60673.2023.10442721
Rosyadi, M. I., Kustiawan, I., Tetehfio, E. O., & Joshua, Q. (2023). The role of AI in vocational education: A systematic literature review. Journal of Vocational Education Studies, 6(2), 244-263. https://doi.org/10.12928/joves.v6i2.9032
Santos, S., & S. Junior, G. (2024). Opportunities and Challenges of AI to Support Student Assessment in Computing Education: A Systematic Literature Review: Proceedings of the 16th International Conference on Computer Supported Education, 15–26. https://doi.org/10.5220/0012552500003693
Sarbadhikari, S. N., & Pradhan, K. B. (2020). The Need for Developing Technology-Enabled, Safe, and Ethical Workforce for Healthcare Delivery. Safety and Health at Work, 11(4), 533–536. https://doi.org/10.1016/j.shaw.2020.08.003
Shi, R., & Wan, X. (2024). A bibliometric analysis of knowledge mapping in Chinese education digitalization research from 2012 to 2022. Humanities and Social Sciences Communications, 11(1), 505. https://doi.org/10.1057/s41599-024-03010-8
Shiva Krishna Reddy V. & Kathiravan M. (2024). Virtual Reality Technology and Artificial Intelligence for Television and Film Animation. Journal of Advanced Research in Applied Sciences and Engineering Technology, 43(1), 263–273. https://doi.org/10.37934/araset.43.1.263273
Song, J., Zhang, L., Yu, J., Peng, Y., Ma, A., & Lu, Y. (2022). Paving the Way for Novices: How to Teach AI for K-12 Education in China. Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 12852–12857. https://doi.org/10.1609/aaai.v36i11.21565
Wang, L.-M., Zhong, Y.-F., Zheng, D.-F., Sun, A.-P., Zhang, Y.-S., Dong, R.-F., & Pan, Y. (2014). Intraneural perineurioma affecting multiple nerves: A case report and literature review. International Journal of Clinical and Experimental Pathology, 7(6), 3347–3354.
Wolf, R. R., & Wolf, A. (2023). Using AI to Evaluate a Competency-Based Online Writing Course in Nursing. Online Learning, 27(3). https://doi.org/10.24059/olj.v27i3.3974
Xu, Y. (2023). Research on the application of Artificial Intelligence tools in higher vocational education. Applied and Computational Engineering, 22(1), 265–272. https://doi.org/10.54254/2755-2721/22/20231227
Yang, X., Gao, G., & Chi, M. (2023). Hierarchical Apprenticeship Learning for Disease Progression Modeling. Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2388–2396. https://doi.org/10.24963/ijcai.2023/265
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education–where are the educators?. International journal of educational technology in higher education, 16(1), 1-27.
Zhang, J., Yu, S., & Tang, L. (2021). A scientometric review of artificial intelligence in education research. International Journal of Educational Technology in Higher Education, 18, 1–25.
DOI: 10.1186/s41239-021-00274-x
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