Students’ Perceptions of Chatgpt Use in Vocational and Engineering Education Practicum: A Descriptive Qualitative Study
DOI:
https://doi.org/10.56806/jh.v7i2.454Keywords:
Engineering Education, Qualitative Study, Maxqda, Educational PracticumAbstract
The study is aimed at exploring students’ perception of using ChatGPT in the Multimedia and Internet practicum in vocational and engineering education context. The subjects of this study were 28 students of the Multimedia and Internet practicum course in Electronic Engineering Education Study Program of Universitas Negeri Padang. Data were collected through written open-ended responses and analyzed using thematic analysis using MAXQDA. The findings indicate that students viewed ChatGPT as a beneficial and practical learning aid that assisted them in searching for information, generating ideas, clarifying concepts, solving problems, and completing projects. However, students also identified a number of limitations i.e., limited responses, premium access, less accurate answers, confusing explanations and potential dependence on ChatGPT. The word-cloud analysis confirmed the thematic findings, showing dominant terms related to usefulness, ease, speed, project work, multimedia production, limitation, cost, and dependence. These results indicate that the potential of using the ChatGPT in project-based multimedia practicum needs to be accompanied by critical verification, lecturer guidance and integration with other learning resources such as modules, tutorials and hands-on practice.
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Alhazmi, A. A., & Kaufmann, A. (2022). Phenomenological Qualitative Methods Applied to the Analysis of Cross-Cultural Experience in Novel Educational Social Contexts. Frontiers in Psychology, 13(April). https://doi.org/10.3389/fpsyg.2022.785134
Almassaad, A., Alajlan, H., & Alebaikan, R. (2024). Student perceptions of generative artificial intelligence: Investigating utilization, benefits, and challenges in higher education. Systems, 12(10), 385. https://doi.org/10.3390/systems12100385
Blahopoulou, J., & Ortiz-Bonnin, S. (2025). Student perceptions of ChatGPT: benefits, costs, and attitudinal differences between users and non-users toward AI integration in higher education. Education and Information Technologies, 30(14), 19741–19764. https://doi.org/10.1007/s10639-025-13575-9
Caldwell, D., Johnson, C., Moore, M., Moore, A., Poush, M., & Franks, A. M. (2024). Teaching through the student lens: qualitative exploration of student evaluations of teaching. American Journal of Pharmaceutical Education, 88(3), 100672. https://doi.org/10.1016/j.ajpe.2024.100672
Chan, C. K. Y., & Hu, W. (2023). Students’ voices on generative AI: Perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20(1), 43.
Dai, Y., Xiao, J.-Y., Huang, Y., Zhai, X., Wai, F.-C., & Zhang, M. (2025). How generative AI enables an online project-based learning platform: An applied study of learning behavior analysis in undergraduate students. Applied Sciences, 15(5), 2369. https://doi.org/10.3390/app15052369
Das, S. R., & Madhusudan, J. V. (2024). Perceptions of Higher Education Students towards ChatGPT Usage. International Journal of Technology in Education, 7(1), 86–106. https://doi.org/10.46328/ijte.583
Garzón, J., Patiño, E., & Marulanda, C. (2025). Systematic review of artificial intelligence in education: Trends, benefits, and challenges. Multimodal Technologies and Interaction, 9(8), 84. https://doi.org/10.3390/mti9080084
Grassini, S. (2023). Shaping the future of education: Exploring the potential and consequences of AI and ChatGPT in educational settings. Education Sciences, 13(7), 692. https://doi.org/10.3390/educsci13070692
Hartmann, Y., De Carvalho, D. B. B., Zandonadi, R. P., Botelho, R. B. A., & Akutsu, R. de C. C. de A. (2025). Brazilian National School Feeding Program: A Review with Content Analysis of Social Documents Using MaxQda® Software. Nutrients, 17(21), 3436. https://doi.org/10.3390/nu17213436
Hasanein, A. M., & Sobaih, A. E. E. (2023). Drivers and consequences of ChatGPT use in higher education: Key stakeholder perspectives. European Journal of Investigation in Health, Psychology and Education, 13(11), 2599–2614. https://doi.org/10.3390/ejihpe13110181
Hidayat, H., Anwar, M., Harmanto, D., Dewi, F. K., Orji, C. T., & Isa, M. R. M. (2024). Two Decades of Project-Based Learning in Engineering Education: A 21-Year Meta-Analysis. TEM Journal, 13(4), 3514–3525. https://doi.org/10.18421/TEM134-84
Jo, H., & Park, D. H. (2023). Mechanisms for successful management of enterprise resource planning from user information processing and system quality perspective. Scientific Reports, 13(1), 1–16. https://doi.org/10.1038/s41598-023-39787-y
Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., & Hüllermeier, E. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274
Kim, J., Klopfer, M., Grohs, J. R., Eldardiry, H., Weichert, J., Cox, L. A., & Pike, D. (2025). Examining faculty and student perceptions of generative AI in university courses. Innovative Higher Education, 50(4), 1281–1313. https://doi.org/10.1007/s10755-024-09774-w
Kohnke, L., Moorhouse, B. L., & Zou, D. (2023). ChatGPT for language teaching and learning. Relc Journal, 54(2), 537–550. https://doi.org/10.1177/00336882231162868
Me?e, ?., Ta?l?çay, C. A., Kuzan, B. N., Kuzan, T. Y., & Sivrio?lu, A. K. (2024). Educating the next generation of radiologists: a comparative report of ChatGPT and e-learning resources. Diagnostic and Interventional Radiology, 30(3), 163. https://doi.org/10.4274/dir.2023.232496
Michel-Villarreal, R., Vilalta-Perdomo, E., Salinas-Navarro, D. E., Thierry-Aguilera, R., & Gerardou, F. S. (2023). Challenges and opportunities of generative AI for higher education as explained by ChatGPT. Education Sciences, 13(9), 856. https://doi.org/10.3390/educsci13090856
Mikac, M., Horvati?, M., Logožar, R., & Dumi?, E. (2024). ChatGPT in Education-Use Cases in an Introductory Web Programming Course. INTED2024 Proceedings, 3173–3182. https://doi.org/10.21125/inted.2024.0853
Nyimbili, F., & Nyimbili, L. (2024). Types of Purposive Sampling Techniques with Their Examples and Application in Qualitative Research Studies. British Journal of Multidisciplinary and Advanced Studies, 5(1), 90–99. https://doi.org/10.37745/bjmas.2022.0419
Ooi, K. B., Tan, G. W. H., Al-Emran, M., Al-Sharafi, M. A., Capatina, A., Chakraborty, A., Dwivedi, Y. K., Huang, T. L., Kar, A. K., Lee, V. H., Loh, X. M., Micu, A., Mikalef, P., Mogaji, E., Pandey, N., Raman, R., Rana, N. P., Sarker, P., Sharma, A., … Wong, L. W. (2025). The Potential of Generative Artificial Intelligence Across Disciplines: Perspectives and Future Directions. Journal of Computer Information Systems, 65(1), 76–107. https://doi.org/10.1080/08874417.2023.2261010
Rafidi, T. J., & El Khatib, N. (2025). Students’ perceptions of ChatGPT use in higher education in Lebanon and Palestine: a comparative study. Discover Education, 4(1), 257. https://doi.org/10.1007/s44217-025-00721-1
Rahman, M. M., & Watanobe, Y. (2023). ChatGPT for education and research: Opportunities, threats, and strategies. Applied Sciences, 13(9), 5783. https://doi.org/10.3390/app13095783
Samala, A. D., Sokolova, E. V., Grassini, S., & Rawas, S. (2024). ChatGPT: a bibliometric analysis and visualization of emerging educational trends, challenges, and applications. International Journal of Evaluation and Research in Education, 12(4), 2375. https://doi.org/10.11591/ijere.v13i4.28119
Sok, S., & Heng, K. (2024). Opportunities, challenges, and strategies for using ChatGPT in higher education: A literature review. Journal of Digital Educational Technology, 4(1), ep2401. https://doi.org/10.30935/jdet/14027
Zheltukhina, M. R., Sergeeva, O. V, Masalimova, A. R., Budkevich, R. L., Kosarenko, N. N., & Nesterov, G. V. (2024). A bibliometric analysis of publications on ChatGPT in education: Research patterns and topics. Online Journal of Communication and Media Technologies, 14(1), e202405. https://doi.org/10.30935/ojcmt/14103
Zheng, T., Yuan, Q., Jiang, Y., Chen, S. Y., Wei, H., & Su, J. (2025). Institutional learning for safer and greener transitions: Embedding legal and process safety knowledge in China’s energy training systems. Process Safety and Environmental Protection, 204, 108054. https://doi.org/https://doi.org/10.1016/j.psep.2025.108054
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Copyright (c) 2026 Fitrika Kumala Dewi, Ambiyar Ambiyar, M Giatman, Nurhasan Syah, Fahmi Rizal, Reni kurnia

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