Trends in the Use of AI-Based Multimedia Learning in Vocational Education: A Literature Review

Muhammad Akbar; Muhammad Ariqsyah; Nizwardi Jalinus; Ridwan Harun; Nurhasan Syah

doi:10.24036/voteteknika.v14i2.138837

Trends in the Use of AI-Based Multimedia Learning in Vocational Education: A Literature Review

Muhammad Akbar⁽¹⁾, Muhammad Ariqsyah⁽²⁾, Nizwardi Jalinus⁽³⁾, Ridwan Harun⁽⁴⁾, Nurhasan Syah⁽⁵⁾,
(1) Universitas Negeri Padang

Indonesia
(2) Universitas Negeri Padang

Indonesia
(3) Universitas Negeri Padang

Indonesia
(4) Universitas Negeri Padang

Indonesia
(5) Universitas Negeri Padang

Indonesia

Corresponding Author

DOI : https://doi.org/10.24036/voteteknika.v14i2.138837

Full Text:

Language : en

Abstract

Learning methods have been profoundly altered by the quick growth of artificial intelligence (AI), especially with regard to the creation of AI-based multimedia in vocational education. It is challenging to determine current research trends and future directions since the data is still dispersed across several fields, despite the growing quantity of linked studies. Thus, the purpose of this study is to discover new research issues, implementation trends, and research gaps by methodically reviewing the evolution of AI-based multimedia learning in vocational education. Using the ScienceDirect database, a Systematic Literature Review (SLR) was carried out in accordance with PRISMA 2020 standards. The Boolean search term ("Artificial Intelligence" OR "Machine Learning") AND ("Multimedia Learning" OR "Interactive Multimedia") AND ("Vocational Education") was used to obtain literature. 219 publications were found throughout the selection process; 17 empirical research papers that satisfied the predetermined inclusion criteria were subjected to descriptive and theme synthesis analysis. The findings indicate that recent studies increasingly emphasize competency-based vocational training, digital learning environments, manufacturing process design, and the integration of industrial standards with intelligent learning technologies. Furthermore, bibliometric mapping using VOSviewer reveals a transition from traditional vocational training toward AI-supported multimedia learning, virtual tutoring, gamification, and digital competency development. These findings demonstrate that AI-based multimedia learning has become a strategic approach to improving learning quality, learner engagement, and workforce readiness in vocational education. The study provides comprehensive insights into current research trends while highlighting future opportunities for integrating intelligent technologies into vocational teaching and learning practices.

Keywords - Artificial Intelligence, Machine Learning, Multimedia Learning, Interactive Multimedia, Vocational Education, Systematic Literature Review, VOSviewer.

References

M. P. Rojas dan A. Chiappe, “Artificial Intelligence and Digital Ecosystems in Education: A Review,” Technol. Knowl. Learn., vol. 29, no. 4, hal. 2153–2170, 2024, doi: 10.1007/s10758-024-09732-7.

K. Bayly-Castaneda, M. S. Ramirez-Montoya, dan A. Morita-Alexander, “Crafting personalized learning paths with AI for lifelong learning: a systematic literature review,” Front. Educ., vol. 9, no. August, hal. 1–12, 2024, doi: 10.3389/feduc.2024.1424386.

C. Halkiopoulos dan E. Gkintoni, “Leveraging AI in E-Learning: Personalized Learning and Adaptive Assessment through Cognitive Neuropsychology—A Systematic Analysis,” Electron., vol. 13, no. 18, 2024, doi: 10.3390/electronics13183762.

R. Sembey, R. Hoda, dan J. Grundy, “Emerging technologies in higher education assessment and feedback practices: A systematic literature review,” J. Syst. Softw., vol. 211, hal. 111988, Mei 2024, doi: 10.1016/j.jss.2024.111988.

Oyebola Olusola Ayeni, Nancy Mohd Al Hamad, Onyebuchi Nneamaka Chisom, Blessing Osawaru, dan Ololade Elizabeth Adewusi, “AI in education: A review of personalized learning and educational technology,” GSC Adv. Res. Rev., vol. 18, no. 2, hal. 261–271, 2024, doi: 10.30574/gscarr.2024.18.2.0062.

S. I. Fuadi, “Literature Review Dampak Kecerdasan Buatan pada Pembelajaran yang Dipersonalisasi : Tinjauan Literatur Sistematis,” vol. 1, no. 3, hal. 401–414, 2024.

H. Farhood, M. Nyden, A. Beheshti, dan S. Muller, “Artificial intelligence-based personalised learning in education: a systematic literature review,” Discov. Artif. Intell., vol. 5, no. 1, 2025, doi: 10.1007/s44163-025-00598-x.

R. Parua dan W. Yang, “The driving logic of digital transformation in TVET,” Vocat. Technol. &Education, 2024, [Daring]. Tersedia pada: https://www.hksmp.com/journals/vte/article/view/590

W. Y. Leong, “Artificial Intelligence, Automation, and Technical and Vocational Education and Training: Transforming Vocational Training in Digital Era,” in ECEI 2025, Basel Switzerland: MDPI, Agu 2025, hal. 9. doi: 10.3390/engproc2025103009.

B. Tjahjono, D. Hermawan, S. Millah, dan R. Evans, “Bridging the Skills Gap Curriculum Transformation for Automation Industries and the Role of Digital Technopreneurship,” Aptisi Trans. Technopreneursh., vol. 7, no. 2, Sep 2025, doi: 10.34306/att.v7i2.620.

A. M. Irfan, “Jurnal MEKOM : Media Komunikasi Pendidikan Kejuruan A Meta-Synthesis On Industrial Competency Needs And Vocational Higher Education Curriculum Transformation In The Metaverse Era,” vol. 13, no. 2, hal. 1–17, 2026.

I. Gligorea, M. Cioca, R. Oancea, A.-T. Gorski, H. Gorski, dan P. Tudorache, “Adaptive Learning Using Artificial Intelligence in e-Learning: A Literature Review,” Educ. Sci., vol. 13, no. 12, hal. 1216, Des 2023, doi: 10.3390/educsci13121216.

J. Fernández-Herrero, “Evaluating Recent Advances in Affective Intelligent Tutoring Systems: A Scoping Review of Educational Impacts and Future Prospects,” Educ. Sci., vol. 14, no. 8, hal. 839, Agu 2024, doi: 10.3390/educsci14080839.

E. Karimi, J. Smith, R. Billard, dan B. Veitch, “AI-based adaptive instructional systems for maritime safety training: a systematic literature review,” Discov. Artif. Intell., vol. 4, no. 1, hal. 51, Jul 2024, doi: 10.1007/s44163-024-00153-0.

D. Mutlu-Bayraktar, “A systematic review of emotional design research in multimedia learning,” Educ. Inf. Technol., vol. 29, no. 18, hal. 24603–24626, Des 2024, doi: 10.1007/s10639-024-12823-8.

M. F. Muttaqin, Y. Sukrawan, dan M. I. Rosyadi, “Exploring the Role of Artificial Intelligence in Learning Media for Vocational Education: A Systematic Literature Review,” J. Vocat. Educ. Stud., vol. 7, no. 2, hal. 181–190, Nov 2024, doi: 10.12928/joves.v7i2.10364.

H. Bakri, “AI-Driven Adaptive Pathways in Virtual Learning Environments: A PRISMA-Based Systematic Literature,” Inf. Technol. Educ. J., hal. 571–581, Okt 2025, doi: 10.59562/intec.v4i3.10515.

S. H. Alshammari, A. E. A. Alshammari, B. A. Alghamdi, M. E. Alrashidi, M. S. Rosli, dan E. Risdianto, “Artificial Intelligence in Educational Technology: A Systematic Review of Pedagogical Opportunities, Implementation Challenges, and EtAlshammari, Sultan Hammad Alshammari, Ali Essa A. Alghamdi, hical Considerations,” Int. J. Stud. Educ., vol. 8, no. 1, hal. 17–37, Jan 2026, doi: 10.46328/ijonse.5974.

I. Saputra, M. Astuti, M. Sayuti, dan D. Kusumastuti, “Integration of Artificial Intelligence in Education: Opportunities, Challenges, Threats and Obstacles. A Literature Review.,” Indones. J. Comput. Sci., vol. 12, no. 4, Agu 2023, doi: 10.33022/ijcs.v12i4.3266.

A. Mouta, A. M. Pinto-Llorente, dan E. M. Torrecilla-Sánchez, “Uncovering Blind Spots in Education Ethics: Insights from a Systematic Literature Review on Artificial Intelligence in Education,” Int. J. Artif. Intell. Educ., vol. 34, no. 3, hal. 1166–1205, Sep 2024, doi: 10.1007/s40593-023-00384-9.

B. Karan dan G. R. Angadi, “Potential Risks of Artificial Intelligence Integration into School Education: A Systematic Review,” Bull. Sci. Technol. Soc., vol. 43, no. 3–4, hal. 67–85, Des 2023, doi: 10.1177/02704676231224705.

L. Tang dan Y. Sheng Su, “Ethical Implications and Principles of Using Artificial Intelligence Models in the Classroom: A Systematic Literature Review.,” Int. J. Interact. Multimed. Artif. Intell., vol. 8, no. 5, hal. 25–36, Mar 2024, doi: 10.9781/ijimai.2024.02.010.

Y. Fu dan Z. Weng, “Navigating the ethical terrain of AI in education: A systematic review on framing responsible human-centered AI practices,” Comput. Educ. Artif. Intell., vol. 7, hal. 100306, Des 2024, doi: 10.1016/j.caeai.2024.100306.

M. I. Rosyadi, I. Kustiawan, E. O. Tetehfio, dan Q. Joshua, “The Role of AI In Vocational Education: A Systematic Literature Review,” J. Vocat. Educ. Stud., vol. 6, no. 2, hal. 244–263, Nov 2023, doi: 10.12928/joves.v6i2.9032.

M. J. Page et al., “The PRISMA 2020 statement: An updated guideline for reporting systematic reviews,” J. Clin. Epidemiol., vol. 134, hal. 178–189, Jun 2021, doi: 10.1016/j.jclinepi.2021.03.001.

Elsevier, . “https://www.sciencedirect.com/,” Sciencedirect. [Daring]. Tersedia pada: https://www.sciencedirect.com/

H. Snyder, “Literature review as a research methodology: An overview and guidelines,” J. Bus. Res., vol. 104, hal. 333–339, Nov 2019, doi: 10.1016/j.jbusres.2019.07.039.

M. J. Page et al., “The PRISMA 2020 statement: an updated guideline for reporting systematic reviews,” Syst. Rev., vol. 10, no. 1, hal. 89, Des 2021, doi: 10.1186/s13643-021-01626-4.

F. Zheng, H. Wang, X. Gu, dan G. Wang, “The impact of generative artificial intelligence literacy on higher-order thinking skills in Chinese higher vocational college students: Integrating variable-centered and person-centered approaches,” Acta Psychol. (Amst)., vol. 268, no. January, hal. 107190, 2026, doi: 10.1016/j.actpsy.2026.107190.

A. Sorgatz, J. Schuldt, dan S. Gröger, “Virtual-tutoring-supported teaching for Geometrical Product Specification,” Procedia CIRP, vol. 129, hal. 216–221, 2024, doi: 10.1016/j.procir.2024.10.038.

S. Rahmawati, S. Prestridge, A. G. Abdullah, dan I. Widiaty, “Unpacking the digital competence challenge in vocational education: A case from Indonesia,” Soc. Sci. Humanit. Open, vol. 12, no. January, hal. 101803, 2025, doi: 10.1016/j.ssaho.2025.101803.

A. C. Asuncion, A. de Vera Asuncion, J. G. Macalipis, C. M. T. Borromeo, J. C. Rivera, dan M. R. Limon, “Weaving gaps in garments education technology: Crafting a skill-based E-toolkit based on Taba’s curriculum development model,” Soc. Sci. Humanit. Open, vol. 8, no. 1, hal. 100656, 2023, doi: 10.1016/j.ssaho.2023.100656.

H. Qin, J. Yan, X. Liu, dan Z. Zhu, “An AI-Driven Learning Analytics Model for Evaluating Digital Competence of Vocational Teachers,” Array, hal. 100995, 2026, doi: 10.1016/j.array.2026.100995.

V. Candido dan A. Cattaneo, “Applying cognitive theory of multimedia learning principles to augmented reality and its effects on cognitive load and learning outcomes,” Comput. Hum. Behav. Reports, vol. 18, no. October 2024, hal. 100678, 2025, doi: 10.1016/j.chbr.2025.100678.

C. Larmuseau, L. De Leersnijder, T. Rotsaert, C. Boel, J. Demanet, dan T. Schellens, “Beyond realism: Rethinking VR design for optimal learning in technical and vocational secondary education,” Comput. Educ. X Real., vol. 6, no. May, hal. 100098, 2025, doi: 10.1016/j.cexr.2025.100098.

N. Wu, Y. Qiu, dan G. Li, “Design and Data Visualization Technology in 3D Virtual Art Design,” Procedia Comput. Sci., vol. 243, hal. 140–147, 2024, doi: 10.1016/j.procs.2024.09.019.

L. Zhou dan D. Zhao, “Design and Implementation of an Network Traffic Classification System Based on Machine Learning,” Procedia Comput. Sci., vol. 259, hal. 969–976, 2025, doi: 10.1016/j.procs.2025.04.050.

J. J. Zhu, “Electrical control technology and PLC course teaching reform strategy,” Procedia Comput. Sci., vol. 166, hal. 301–304, 2020, doi: 10.1016/j.procs.2020.02.095.

S. Ghimire et al., “Explainable artificial intelligence-machine learning models to estimate overall scores in tertiary preparatory general science course,” Comput. Educ. Artif. Intell., vol. 7, no. November, hal. 100331, 2024, doi: 10.1016/j.caeai.2024.100331.

A. A. P. Cattaneo, C. Antonietti, dan M. Rauseo, “How digitalised are vocational teachers? Assessing digital competence in vocational education and looking at its underlying factors,” Comput. Educ., vol. 176, no. October 2021, hal. 104358, 2022, doi: 10.1016/j.compedu.2021.104358.

J. Hou, “Intelligent Educational Information Resource Sharing Platform Based on Zope/Plone,” Procedia Comput. Sci., vol. 247, no. C, hal. 638–646, 2024, doi: 10.1016/j.procs.2024.10.077.

K. (Ke) Li, J. Mukundan, dan V. Vasodavan, “Reducing listening anxiety in blended learning: The role of AI-driven feedback and strategy in EFL education,” Acta Psychol. (Amst)., vol. 267, no. October 2025, 2026, doi: 10.1016/j.actpsy.2026.107105.

Y. Wang dan Y. Luo, “Research on Computer Aided Interaction Design based on Virtual reality Technology,” Procedia Comput. Sci., vol. 228, hal. 619–628, 2023, doi: 10.1016/j.procs.2023.11.072.

N. T. Arpa dan M. J. Alam, “Significance of skill-based secondary education in Bangladesh: The case of an innovative curriculum,” Soc. Sci. Humanit. Open, vol. 12, no. August, hal. 101918, 2025, doi: 10.1016/j.ssaho.2025.101918.

J. Radianti, T. A. Majchrzak, J. Fromm, dan I. Wohlgenannt, “A systematic review of immersive virtual reality applications for higher education: Design elements, lessons learned, and research agenda,” Comput. Educ., vol. 147, hal. 103778, Apr 2020, doi: 10.1016/j.compedu.2019.103778.

O. Zawacki-Richter, V. I. Marín, M. Bond, dan F. Gouverneur, “Systematic review of research on artificial intelligence applications in higher education – where are the educators?,” Int. J. Educ. Technol. High. Educ., vol. 16, no. 1, hal. 39, Des 2019, doi: 10.1186/s41239-019-0171-0.

L. Chen, P. Chen, dan Z. Lin, “Artificial Intelligence in Education: A Review,” IEEE Access, vol. 8, hal. 75264–75278, 2020, doi: 10.1109/ACCESS.2020.2988510.

R. Luckin dan M. Cukurova, “Designing educational technologies in the age of AI: A learning sciences‐driven approach,” Br. J. Educ. Technol., vol. 50, no. 6, hal. 2824–2838, Nov 2019, doi: 10.1111/bjet.12861.

C. Dinata, I. L. Milansari, M. B. Triyono, dan G. N. I. P. Pratama, “The potential of artificial intelligence in vocational education research and development: A bibliometric study,” J. Pendidik. Vokasi, vol. 15, no. 1, hal. 59–74, Feb 2025, doi: 10.21831/jpv.v15i1.77873.

A. J. Lakshmi, A. Kumar, M. S. Kumar, S. I. Patel, dan ..., “Artificial intelligence in steering the digital transformation of collaborative technical education,” J. High …, 2023, [Daring]. Tersedia pada: https://www.sciencedirect.com/science/article/pii/S1047831023000172

H. Thomann, J. Zimmermann, dan V. Deutscher, “How effective is immersive VR for vocational education? Analyzing knowledge gains and motivational effects,” Comput. Educ., vol. 220, no. July, hal. 105127, 2024, doi: 10.1016/j.compedu.2024.105127.

C. Wang, “Application of AI Intelligent Learning System in Multimedia Demonstration,” Procedia Comput. Sci., vol. 228, hal. 71–78, 2023, doi: 10.1016/j.procs.2023.11.010.

J. Lu, X. Wan, dan M. Chen, “Optimization logic and paradigm construction of digital transformation of technical skill training model under the perspective of social media communication and …,” Int. J. New …, 2023, [Daring]. Tersedia pada: https://www.francis-press.com/uploads/papers/zedCiiNENvF2XWy5HGbCBOfLEhxZL6dQifTlCmob.pdf

D. D. Dolean dan N. Prodan, “Let’s eat grandma: Awareness of punctuation and capitalization rules’ violations predicts the development of reading comprehension,” Learn. Instr., vol. 86, hal. 101780, Agu 2023, doi: 10.1016/j.learninstruc.2023.101780.

H. Huang, A. M. Karim, J. Adaikalam, dan Z. Chen, “Study on the Factors Affecting University Graduates Unemployment Problem in China: Literature Review Approach,” Int. J. Acad. Res. Bus. Soc. Sci., vol. 14, no. 1, Jan 2024, doi: 10.6007/IJARBSS/v14-i1/20474.

D. Kablitz, M. Conrad, dan S. Schumann, “Immersive VR-based instruction in vocational schools: effects on domain-specific knowledge and wellbeing of retail trainees,” Empir. Res. Vocat. Educ. Train., vol. 15, no. 1, hal. 9, Sep 2023, doi: 10.1186/s40461-023-00148-8.

R. Samuelsson, “Learning beyond instructionist/constructionist divides: A mixed methods exploration of three learning designs for 1-2-year-old children,” Comput. Educ., vol. 218, hal. 105089, Sep 2024, doi: 10.1016/j.compedu.2024.105089.

I. Inayat, R. ul Amin, Z. Inayat, dan S. S. Salim, “Effects of Collaborative Web Based Vocational Education and Training (VET) on Learning Outcomes,” Comput. Educ., vol. 68, hal. 153–166, Okt 2013, doi: 10.1016/j.compedu.2013.04.027.

A. Metreveli, X. Chen, A. Hedman, dan A. Sergeeva, “‘Who will be left behind?’: A Swedish case of learning AI in vocational education,” Int. J. Educ. Res., vol. 133, hal. 102697, 2025, doi: 10.1016/j.ijer.2025.102697.

E. Petridou dan L. Lao, “Identifying challenges and best practices for implementing AI additional qualifications in vocational and continuing education: a mixed methods analysis,” Int. J. Lifelong Educ., vol. 43, no. 4, hal. 385–400, Jul 2024, doi: 10.1080/02601370.2024.2351076.

A. Habibi, S. Sofyan, dan A. Mukminin, “Factors affecting digital technology access in vocational education,” Sci. Rep., vol. 13, no. 1, hal. 5682, Apr 2023, doi: 10.1038/s41598-023-32755-6.

W. Q. Lin, “Enhancing personalised learning with artificial intelligence - Implementation challenges from educators’ perspective in vocational education and training,” Res. Pract. Technol. Enhanc. Learn., vol. 21, hal. 033, Nov 2025, doi: 10.58459/rptel.2026.21033.