Pemanfaatan Arduino-IoT dalam Pengembangan STEMLAB Fisika: Studi Eksploratif terhadap Persepsi Mahasiswa
Abstract
This study aims to explore physics education students' perceptions of integrating Arduino and Internet of Things (IoT) technology in developing STEMLAB-based enrichment media. The research method used an exploratory qualitative approach with Technology Readiness Level (TRL) stages 1–3 conducted over 12 months. The research subjects were 30 students from the Physics Education Study Program at Jambi University in semesters 4. Research instruments included open questionnaires, semi-structured interview guides, and thematic analysis rubrics validated with an average validity of 87.3%. Results showed that 84% of students believed real-time data visualization could enhance concept understanding, 91% agreed technology integration makes learning more engaging, and 81% were interested in learning Arduino in physics experiment contexts. A prototype media based on Arduino Uno R3 and NodeMCU ESP8266 with TDS, EC, pH, and temperature sensors was developed and tested on 8 students with expert validation reaching 88.5% and user satisfaction rate of 87.5%. This research produced a validated media design responsive to student needs and ready for wider implementation.
References
Ahmed, U., Mumtaz, R., Anwar, H., Mumtaz, S., & Qamar, A. M. (2019). Water quality monitoring: From conventional to emerging technologies. Water Science & Technology: Water Supply, 20(1), 28–45. https://doi.org/10.2166/ws.2019.144
Arsela, R., Hendri, M., & Rasmi, D. P. (2025). Pengembangan Modul Ajar Terintegrasi STEAM-PjBL Untuk Meningkatkan Kemampuan Berpikir Kreatif Pada Materi Fluida Statis. JIIP - Jurnal Ilmiah Ilmu Pendidikan, 8(5), 4760-4767. https://doi.org/10.54371/jiip.v8i5.7837
Banna, M. H. Al, Ghosh, T., Taher, K. A., Kaiser, M. S., & Mahmud, M. (2022). IoT-based water quality monitoring and prediction system using machine learning. Sensors, 22(13), 4766. https://doi.org/10.3390/s22134766
Capraro, R. M., Capraro, M. M., & Morgan, J. R. (2013). STEM project-based learning: An integrated science, technology, engineering, and mathematics (STEM) approach (2nd ed.). Sense Publishers. https://doi.org/10.1007/978-94-6209-143-6
Ga, S.-H., Cha, H.-J., & Kim, C.-J. (2021). Adapting internet of things to Arduino-based devices for low-cost remote sensing in school science learning environments. International Journal of Online and Biomedical Engineering (iJOE), 17(02), 4–18. https://doi.org/10.3991/ijoe.v17i02.20089
Han, S., Yalvac, B., Capraro, M. M., & Capraro, R. M. (2015). In-service teachers' implementation and understanding of STEM project based learning. Eurasia Journal of Mathematics, Science and Technology Education, 12(6), 1417–1446. https://doi.org/10.12973/eurasia.2015.1306a
Hendri, M., Rasmi, D. P., Andika, N., & Wibisana, S. S. (2025). Integration of Arduino Uno and IoT concepts in the development of magnetic field learning media: A qualitative descriptive study. Jurnal Penelitian Pendidikan IPA, 11(8), 785–797. https://doi.org/10.29303/jppipa.v11i8.12178
Hong, J.-C., Chen, M.-Y., Wong, A., Hsu, T.-F., & Peng, C.-C. (2012). Developing physics concepts through hands-on problem solving: A perspective on a technological project design. International Journal of Technology and Design Education, 22(4), 473–487. https://doi.org/10.1007/s10798-011-9163-7
Ilić, V., Popadić, B., & Pešić, D. (2023). IoT in water quality monitoring—Are we really here? Sensors, 23(2), 960. https://doi.org/10.3390/s23020960
Jan, F., Min-Allah, N., & Düştegör, D. (2021). IoT-based smart water quality monitoring: Recent techniques, trends, and challenges for domestic applications. Water, 13(13), 1729. https://doi.org/10.3390/w13131729
Kelley, T. R., Knowles, J. G., Holland, J. D., & Han, J. (2020). Increasing high school teachers' self-efficacy for integrated STEM instruction through a collaborative community of practice. International Journal of STEM Education, 7(14), 1–18. https://doi.org/10.1186/s40594-020-00211-w
Kuo, H.-C., Tseng, Y.-C., & Yang, Y.-T. C. (2019). Promoting college students' learning motivation and creativity through a STEM interdisciplinary PBL human-computer interaction system design and development course. Thinking Skills and Creativity, 31, 1–10. https://doi.org/10.1016/j.tsc.2018.09.001
Kusumaningtyas, D. A. (2024). STEM-project based learning in physics concept of measurement to enhance high school students' scientific literacy. Jurnal Penelitian & Pengembangan Pendidikan Fisika, 10(2), 295–306. https://doi.org/10.21009/1.10217
Marín-Marín, J., Lázaro-Pérez, C., Usart, M., & Gisbert-Cervera, M. (2024). Computational thinking and programming with Arduino in education: A systematic review for secondary education. Heliyon, 10(8), e29177. https://doi.org/10.1016/j.heliyon.2024.e29177
Petryshyn, O., Kotsur, V., & Dudnik, O. (2024). Using Arduino to develop research competencies of students in school physics education. CTE Workshop Proceedings, 11, 200–212. https://doi.org/10.55056/cte.663
Rahman, M. M., Dey, K. K., Islam, M. T., & Al Azad, A. K. (2024). Critical review on water quality analysis using IoT and machine learning models. International Journal of Information Technology, 16, 1205–1222. https://doi.org/10.1007/s41870-023-01605-2
Rasmi, D. P., Wibisana, S. S., & Hendri, M. (2025a). The Integrating STEM in Hooke's Law and Elasticity Worksheets: Enhancing Student Collaboration and Learning Outcomes. Jurnal Penelitian Pendidikan IPA, 11(2), 573–581. https://doi.org/10.29303/jppipa.v11i2.10166
Rasmi, D. P., Hendri, M., & Mardatila, A. (2025b). Development of STEAM-Based Assessment Instrument for Creative Thinking on Static Fluid Material. Jurnal Pijar Mipa, 20(2), 316–325. https://doi.org/10.29303/jpm.v20i2.8615
Sari, R. M., Hendri, M., & Rasmi, D. P. (2025c). Pengembangan Modul Ajar Terintegrasi STEAM-PjBL untuk mengingkatkan Keterampilan Komunikasi Pada Materi Suhu dan Kalor. JIIP - Jurnal Ilmiah Ilmu Pendidikan, 8(5), 4768-4776. https://doi.org/10.54371/jiip.v8i5.7836
Sengupta, P., Ghosh, A., Patra, S., & Ghosh, B. (2023). Advances in machine learning and IoT for water quality monitoring: A comprehensive review. Environmental Monitoring and Assessment, 195(11), 1356. https://doi.org/10.1007/s10661-023-11916-4
Sulaiman, F., Ching, G. S., Rosales Jr., J. J., & Uden, L. (2023). Integrated science, technology, engineering, and mathematics project-based learning for physics learning from neuroscience perspectives. Frontiers in Psychology, 14, 1136246. https://doi.org/10.3389/fpsyg.2023.1136246
Tamim, S. R., & Grant, M. M. (2013). Definitions and uses: Case study of teachers implementing project-based learning. Interdisciplinary Journal of Problem-Based Learning, 7(2), 72–101. https://doi.org/10.7771/1541-5015.1323
Zhang, L., & Ma, Y. (2023). A study of the impact of project-based learning on student learning effects: A meta-analysis study. Frontiers in Psychology, 14, 1202728. https://doi.org/10.3389/fpsyg.2023.1202728
