Integration of Virtual Lab-Based Learning Media in Improving Practical Skills and Student Engagement in Computer Network Engineering
This study investigates the integration of learning media using virtual labs to improve practical skills and student engagement in Computer Network Engineering at Institut Teknologi dan Bisnis Bina Sarana Global. A quasi-experimental design was conducted in an experimental class using virtual labs and in a control class using the traditional practicum. Participants consisted of 62 students. Data were collected with pretest–posttest assessments of practicum skills and an evidence-rated engagement questionnaire. The results showed a great increase in the experimental class. Then, using a series of independent-samples t-tests, we compared the posttest practical skill scores between the experimental (M = 85.42, SD = 6.31) and control class practice (M = 78.11, SD = 7.04), t(60) = 4.21, p < .001, and a large effect size (d = 1.06). In addition, a comparison of the groups' mean scored on short-answer scoring revealed that students were more engaged with the material in the experimental group (M = 4.32, SD = 0.41) than compared to students in the control group (M = 3.87, SD = 0.46), t(60) = -3.78, p < .001. In general, they are effective in providing laboratory practice to master concepts, demonstrate bad practices, troubleshoot, and in encouraging active participation in learning. Implementation Read This Teaching Note: Virtual labs are recommended as an active research-based practicum model in engineering to enhance student learning outcomes.
Keywords: virtual laboratory, practical skills, student engagement, digital learning media.
Abdrabou, A., & Shakhatreh, W. (2021). On assessment and evaluation of teaching computer networks to electrical engineering students by the aid of a lab course. Journal of Technology and Science Education, 11(2), 388. https://doi.org/10.3926/jotse.1186
Aghaee, N., & Karunaratne, T. (2024). Digital tools in the thesis process: a case study from sweden. in f. moriera (Ed.), Proceedings of the European Conference on e-Learning, ECEL (Vol. 23, Number 1, pp. 1–8). Academic Conferences and Publishing International Limited. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85215701549&partnerID=40&md5=dae82e12dd07a723910fef76ac950f61
Allcoat, D., Hatchard, T., Azmat, F., Stansfield, K., Watson, D., & von Mühlenen, A. (2021). Education in the digital age: learning experience in virtual and mixed realities. Journal of Educational Computing Research, 59(5), 795–816. https://doi.org/10.1177/0735633120985120
Almasri, F. (2024). Exploring the impact of artificial intelligence in teaching and learning of science: a systematic review of empirical research. Research in Science Education, 54(5), 977–997. https://doi.org/10.1007/s11165-024-10176-3
Arango-Vasquez, S. I., & Manrique-Losada, B. (2022). Promoting communicative interactions in virtual environments: a methodological approach. In K. O. Villalba-Condori, C. S. Gonzalez-Gonzalez, A. Garcia-Holgado, A. Infante-Moro, J. C. Infante-Moro, J. Gallardo-Perez, & J. F. Garcia-Penalvo (Eds.), Proceedings - JICV 2022: 12th International Conference on Virtual Campus. Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/JICV56113.2022.9934278
Bauer, E., Greiff, S., Graesser, A. C., Scheiter, K., & Sailer, M. (2025). Looking beyond the hype: understanding the effects of ai on learning. Educational Psychology Review, 37(2). https://doi.org/10.1007/s10648-025-10020-8
Bird, J. M., Smart, P., Harris, D., Phillips, L., Giannachi, G., & Vine, S. J. (2022). A Magic leap in tourism: intended and realized experience of head-mounted augmented reality in a museum context. Journal of Travel Research, 62(7), 1427–1447. https://doi.org/10.1177/00472875221134031
Braun, V., & Clarke, V. (2023). Toward good practice in thematic analysis: Avoiding common problems and be(com)ing a knowing researcher. In International Journal of Transgender Health (Vol. 24, Number 1, pp. 1–6). Routledge. https://doi.org/10.1080/26895269.2022.2129597
Chans, G. M., & Portuguez Castro, M. (2021). Gamification as a strategy to increase motivation and engagement in higher education chemistry students. Computers, 10(10). https://doi.org/10.3390/computers10100132
Chawla, A., Panigrahi, B. K., & Bhalja, B. R. (2023). Deep-Learning-Based denial-of-service resilient framework for wide area situational awareness of power systems. IEEE Transactions on Industrial Informatics, 19(8), 9204–9216. https://doi.org/10.1109/TII.2022.3227726
Chen, H., Yohannes, A., & Hung, N. (2024). Effects of Escape Room Game‐based Civics Education on Junior High School Students’ Learning Motivation, Critical Thinking and Flow Experience. British Journal of Educational Technology, 56(3), 1170–1190. https://doi.org/10.1111/bjet.13519
Chen, Y., Hu, X., Zhu, Y., Liu, X., & Yi, B. (2024). Real-time non-invasive hemoglobin prediction using deep learning-enabled smartphone imaging. BMC Medical Informatics and Decision Making, 24(1). https://doi.org/10.1186/s12911-024-02585-1
Dai, C.-P., Ke, F., Dai, Z., & Pachman, M. (2023). Improving teaching practices via virtual reality-supported simulation-based learning: Scenario design and the duration of implementation. British Journal of Educational Technology, 54(4), 836–856. https://doi.org/10.1111/bjet.13296
Della Spina, L., & Viglianisi, A. (2021). Hybrid evaluation approaches for cultural landscape: The case of “riviera dei gelsomini” area in italy. In C. Bevilacqua, F. Calabrò, & D. S. L (Eds.), Smart Innovation, Systems and Technologies: 178 SIST (pp. 1369–1379). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-48279-4_128
Dodevska, M., Zdravevski, E., Chorbev, I., Kostoska, M., Branco, F., Coelho, P. J., Pires, I. M., & Lameski, P. (2025). Virtual reality as a learning tool: Evaluating the use and effectiveness of simulation laboratories in educational settings. In Social Sciences and Humanities Open (Vol. 12). Elsevier Ltd. https://doi.org/10.1016/j.ssaho.2025.101742
Enders, N., Gaschler, R., & Kubik, V. (2021). Online quizzes with closed questions in formal assessment: how elaborate feedback can promote learning. Psychology Learning and Teaching, 20(1), 91–106. https://doi.org/10.1177/1475725720971205
Garrard, A., & Beck, S. (2018). Pedagogical and cost advantages of a multidisciplinary approach to delivering practical teaching. In The Interdisciplinary Future of Engineering Education: Breaking through Boundaries in Teaching and Learning (pp. 33–48). Taylor and Francis. https://doi.org/10.4324/9781351060790-5
Huang, H.-W., Li, Y., & Cai, S. (2023). Best practices for integrating 360 vr videos into psychology teaching. 2023 9th International Conference on Virtual Reality, ICVR 2023, 447–451. https://doi.org/10.1109/ICVR57957.2023.10169358
Kang, H. Y., & Kim, H. R. (2021). Impact of blended learning on learning outcomes in the public healthcare education course: a review of flipped classroom with team-based learning. BMC Medical Education, 21(1). https://doi.org/10.1186/s12909-021-02508-y
Koçan, S., Kulakaç, N., Aktuğ, C., & Demirel, S. (2024a). The effect of video-based simulation training on nursing students’ motivation and academic achievement. Cin Computers Informatics Nursing, 42(6), 440–447. https://doi.org/10.1097/cin.0000000000001117
Koçan, S., Kulakaç, N., Aktuğ, C., & Demirel, S. (2024b). The effect of video-based simulation training on nursing students’ motivation and academic achievement. Cin Computers Informatics Nursing, 42(6), 440–447. https://doi.org/10.1097/cin.0000000000001117
Lee, C. A., Gamino, D., Lore, M., Donelson, C., & Windsor, L. C. (2023). Use of research electronic data capture (REDCap) in a sequential multiple assignment randomized trial (SMART): a practical example of automating double randomization. BMC Medical Research Methodology, 23(1). https://doi.org/10.1186/s12874-023-01986-6
Li, J., & Liang, W. (2024). Effectiveness of virtual laboratory in engineering education: A meta-analysis. PLoS ONE, 19(12). https://doi.org/10.1371/journal.pone.0316269
Li, J., Shumei, Z., Peng, Q., Wu, W., Lv, L. F., Yue, L., & Zhong, H. J. (2025). Development of an Interpretable Machine Learning Model for Frailty Risk Prediction in Older Adult Care Institutions: A Mixed-Methods, Cross-Sectional Study in China. BMJ Open, 15(7), e095460. https://doi.org/10.1136/bmjopen-2024-095460
Li, T. (2025). AI-Driven multi-modal interactive learning environment using deep learning and chain-of-thought reasoning. International Journal of Pattern Recognition and Artificial Intelligence, 39(3n04). https://doi.org/10.1142/S0218001425520019
Li, W. (2024). Factors influencing student engagement and behavioral differences based on k-means cluster analysis. Journal of Computational Methods in Sciences and Engineering, 25(2), 1835–1844. https://doi.org/10.1177/14727978241305758
Lim, S., Turner, J., Tang, D., Sherman, K. A., Sinha, K., Chawla, S., Carney, A. S., Shekhawat, G. S., & Gopinath, B. (2025). Understanding hearing health‐care access in australia: users’ perspectives. Australasian Journal on Ageing, 44(2). https://doi.org/10.1111/ajag.70029
Limanto, S., Kartikasari, F. D., & Oeitheurisa, M. (2020). Improved learning outcomes of descriptive statistics through the test room and data processing features in the mobile learning model. 139–142. https://doi.org/10.1109/ICIEE49813.2020.9277408
Osher, D., Cantor, P., Berg, J., Steyer, L., & Rose, T. (2020). Drivers of human development: How relationships and context shape learning and development. Applied Developmental Science, 24(1), 6–36. https://doi.org/10.1080/10888691.2017.1398650
Rakhmawati, L., Agung, A. I., & Rohman, M. (2022). Virtual laboratory-based student worksheets development for computational thinking practices. 2022 5th International Conference on Vocational Education and Electrical Engineering: The Future of Electrical Engineering, Informatics, and Educational Technology Through the Freedom of Study in the Post-Pandemic Era, ICVEE 2022 - Proceeding, 221–225. https://doi.org/10.1109/ICVEE57061.2022.9930462
Rana, S., Sheshadri, T., Malhotra, N., & Mahabub Basha, S. (2024). Creating digital learning environments: Tools and technologies for success. In Transdisciplinary Teaching and Technological Integration for Improved Learning: Case Studies and Practical Approaches (pp. 1–21). IGI Global. https://doi.org/10.4018/979-8-3693-8217-2.ch001
Rudhumbu, N. (2022). Applying the UTAUT2 to predict the acceptance of blended learning by university students. Asian Association of Open Universities Journal, 17(1), 15–36. https://doi.org/10.1108/AAOUJ-08-2021-0084
Sakkas, K., Ntagka, N. E., Spyridakis, M., Miltiadous, A., Glavas, E., Tzallas, A. T., & Giannakeas, N. (2025). Multiplayer virtual labs for electronic circuit design: a digital twin-based learning approach. Electronics (Switzerland), 14(16). https://doi.org/10.3390/electronics14163163
Sharma, S., Tuli, N., & Mantri, A. (2022). Augmented reality in educational environments: a systematic review. In Journal of Engineering Education Transformations (Vol. 36, Number 2, pp. 7–19). Rajarambapu Institute Of Technology. https://doi.org/10.16920/jeet/2022/v36i2/22149
Shkilev, R., Kozachek, A., Abdullayevna, B. I., Abdullayeva, F. S., Toshboyeva, L. J., Inagamova, N. A., & Abdullayev, S. S. O. (2024). Augmented reality in mobile learning: enhancing interactive learning experiences. International Journal of Interactive Mobile Technologies, 18(20), 4–15. https://doi.org/10.3991/ijim.v18i20.50795
Siddiqui, N., Gorard, S., Bulsari, S., See, B., Dixon, P., Saeed, S., Safaraz, H., & Pandya, K. (2025). Does school matter for children’s cognitive and non-cognitive learning? Findings from a natural experiment in Pakistan and India. British Educational Research Journal. https://doi.org/10.1002/berj.4147
Teng, L., Tang, Y. M., Wu, R. P. H., Tsui, G. C. P., Tsang, Y. P., & Tang, C. Y. (2024). Exploring the efficacy of collaborative learning in a remote robotics laboratory: a comparative analysis of performance and pedagogical approaches. Smart Learning Environments, 11(1). https://doi.org/10.1186/s40561-024-00305-w
Tokatlidis, C., Tselegkaridis, S., Rapti, S., Sapounidis, T., & Papakostas, D. (2024). Hands-On and virtual laboratories in electronic circuits learning—knowledge and skills acquisition. Information (Switzerland), 15(11). https://doi.org/10.3390/info15110672
Tuli, N., Singh, G., Mantri, A., & Sharma, S. (2022). Augmented reality learning environment to aid engineering students in performing practical laboratory experiments in electronics engineering. Smart Learning Environments, 9(1). https://doi.org/10.1186/s40561-022-00207-9
Venn, E., Park, J., Andersen, L. P., & Hejmadi, M. (2023). How do learning technologies impact on undergraduates’ emotional and cognitive engagement with their learning? Teaching in Higher Education, 28(4), 822–839. https://doi.org/10.1080/13562517.2020.1863349
Wahyudi, M. N. A., Budiyanto, C. W., Widiastuti, I., Hatta, P., & Bakar, Mohd. S. Bin. (2024). Understanding virtual laboratories in engineering education: a systematic literature review. International Journal of Pedagogy and Teacher Education, 7(2), 102. https://doi.org/10.20961/ijpte.v7i2.85271
Wang, Y., Jabrealy, M., & Izadpanah, S. (2026). Immediate and sustained effects of song‐based language learning on english as a foreign language learners’ academic development, cognitive engagement, and motivation. Brain and Behavior, 16(6). https://doi.org/10.1002/brb3.71532
Wang, Y., Zuo, M., He, X., & Wang, Z. (2025). Exploring students online learning behavioral engagement in university: factors, academic performance and their relationship. Behavioral Sciences, 15(1), 78. https://doi.org/10.3390/bs15010078
Wastira, J., & Tekad, E. (2025). Integrating technology into teaching to foster student engagement and interaction. Jurnal Teknologi Pendidikan, 27(2), 464–486. https://doi.org/10.21009/JTP2001.6
Weis, P., Smetanka, L., Hrček, S., & Vereš, M. (2024). Interactive application as a teaching aid in mechanical engineering. Computers, 13(7). https://doi.org/10.3390/computers13070170
Wekerle, C., Daumiller, M., Janke, S., Dickhäuser, O., Dresel, M., & Kollar, I. (2024). Putting ICAP to the test: how technology-enhanced learning activities are related to cognitive and affective-motivational learning outcomes in higher education. Scientific Reports, 14(1). https://doi.org/10.1038/s41598-024-66069-y
Wut, T. ming, & Xu, J. (2021). Person-to-person interactions in online classroom settings under the impact of COVID-19: a social presence theory perspective. Asia Pacific Education Review, 22(3), 371–383. https://doi.org/10.1007/s12564-021-09673-1
Zhang, J. (2026). Effects of Gamification on the Engagement and Translation Proficiency of the Chinese EFL Learners: A Case of Quizizz. Frontiers in Psychology, 17. https://doi.org/10.3389/fpsyg.2026.1813663
Zhu, J.-Y., He, Z.-M., Huang, C., Zeng, J., Lin, H.-C., Chen, F.-C., Yu, C.-Q., Li, Y., Zhang, Y.-T., Chen, H.-T., & Pu, J.-X. (2024). Deep learning-assisted common temperature measurement based on visible light imaging. Chinese Physics B, 33(8). https://doi.org/10.1088/1674-1056/ad4cd9
Refbacks
- There are currently no refbacks.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.


