Empowering business students through culturally responsive Internet of Things education: insights from a modular biomedical circuit curriculum

  • Yu-Ming Fei Graduate Institute of Business Intelligence and Innovation, Chihlee University of Technology, Taipei, Taiwan https://orcid.org/0000-0001-8184-3250
  • Wen-Chiang Liu Department of Business Administration, Chihlee University of Technology, Taipei, Taiwan
DOI: https://doi.org/10.25304/rlt.v33.3545
Keywords: IoT education, business students, biomedical circuits, qualitative research, responsive pedagogy, blended learning, innovation projects

Abstract

This research investigates the design and application of a culturally appropriate, modular Internet of Things (IoT) learning module for undergraduate business students, responding to the demand for interdisciplinary education merging technology and business expertise. By blending modular biomedical circuits, IoT power management and a blended learning approach, this course sought to promote student engagement, technological confidence and relevant innovation. Students assembled biomedical sensor circuits, like heart-rate and temperature monitors, which connected to IoT dashboards for data visualisation, to experience tangible links between physical computing and business. The course included 128 students from two groups, ending with individual projects and team contests. Data for this qualitative study came from student journals, focus groups and project artefacts. Four major results were found by the thematic analysis: learner motivation increased via modular practice, comprehension improved through contextualised applications, interdisciplinary collaboration skills grew and competitive innovation outcomes benefited from successful knowledge transfer. Five student teams’ projects earned national recognition; they involved smart poultry farming and energy-efficient hospitality systems. These findings emphasise how IoT education can enable non–Science, Technology, Engineering, and Mathematics (non- STEM) learners.

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References


Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa




Cavanagh, M. (2011). Students’ experiences of active engagement through cooperative learning activities in lectures. Active Learning in Higher Education, 12(1), 23–33. https://doi.org/10.1177/1469787410387724




Cheng, M.-M. et al. (2021). Culturally responsive teaching in technology-supported learning environments in marine education for sustainable development. Sustainability, 13(24), 13922. https://doi.org/10.3390/su132413922




Ciampa, K. (2014). Learning in a mobile age: An investigation of student motivation. Journal of Computer Assisted Learning, 30(1), 82–96. https://doi.org/10.1111/jcal.12036




Gay, G. (2002). Preparing for culturally responsive teaching. Journal of Teacher Education, 53(2), 106–116. https://doi.org/10.1177/0022487102053002003




Gay, G. (2018). Culturally responsive teaching: Theory, research, and practice (3rd ed.). Teachers College Press.




Graham, C. R., Allen, S., & Ure, D. (2005). Benefits and challenges of blended learning environments. In, Encyclopedia of Information Science and Technology. IGI Global, 253–259. https://doi.org/10.4018/978-1-59140-553-5.ch047




Howard, T. C. (2001). Telling their side of the story: African-American students’ perceptions of culturally relevant teaching. The Urban Review, 33(2), 131–149. https://doi.org/10.1023/A:1010393224120




Junco, R., Heiberger, G., & Loken, E. (2011). The effect of Twitter on college student engagement and grades. Journal of Computer Assisted Learning, 27(2), 119–132. https://doi.org/10.1111/j.1365-2729.2010.00387.x




Krüger-Ross, M. J., Waters, R. D., & Farwell, T. M. (2013). Exploring students’ social media use and perceptions during a university course: A qualitative study. Journal of Online Learning and Teaching, 9(2), 244–254.




Ladson-Billings, G. (1995). Toward a theory of culturally relevant pedagogy. American Educational Research Journal, 32(3), 465–491. https://doi.org/10.3102/00028312032003465




Mohanty, A. K. et al. (2024). Enhancing classroom engagement through IoT-enabled smart learning environments. ShodhKosh: Journal of Visual and Performing Arts, 5(1), 1003–1010. https://doi.org/10.29121/shodhkosh.v5.i1.2024.2591




Ramohalli, N., & Adegbija, T. (2018). Modular electronics for broadening non-expert participation in STEM innovation: An IoT perspective. In ISEC 2018: Proceedings of the 8th IEEE Integrated STEM Education Conference (pp. 167–174). Institute of Electrical and Electronics Engineers (IEEE).




Roberts, L. D., & Rajah-Kanagasabai, C. J. (2013). The role of perceived privacy and perceived anonymity in the use of self-disclosure on the internet. Computers in Human Behavior, 29(6), 2481–2490. https://doi.org/10.1016/j.chb.2013.06.007




Roschelle, J. et al. (2000). Changing how and what children learn in school with computer-based technologies. The Future of Children, 10(2), 76–101. https://doi.org/10.2307/1602690




Rothstein, D., & Santana, L. (2011). Make just one change: Teach students to ask their own questions. Harvard Education Press.




Sarmiento-Rojas, J., Aya-Parra, P. A., & Perdomo, O. J. (2022). Proposal of design and innovation in the creation of the Internet of Medical Things based on the CDIO model through the methodology of problem-based learning. Sensors, 22(22), 8979. https://doi.org/10.3390/s22228979




Thorne, K. (2003). Blended Learning: How to Integrate Online and Traditional Learning. Kogan Page.




Tosiron, A. (2018). Modular electronics for broadening non-expert participation in the Internet of Things. In, IEEE Integrated STEM Education Conference (ISEC). https://doi.org/10.1109/ISECon.2018.8340507




University of North Dakota. (n.d.). Biomedical Internet of Things Devices. Retrieved from https://und.edu/programs/biomedical-internet-of-things-devices/index.html




University of Tasmania. (2023, April 27). UTAS tops global list for climate action, second overall for educational impact. The Mercury. Retrieved from https://www.themercury.com.au/news/tasmania/utas-tops-global-list-for-climate-action-second-overall-for-educational-impact/news-story/9902c5c3284db34cd11e58fd3484b601




Zhou, C., & Brown, D. (2020). Engaging non-STEM majors in digital technology: Lessons from interdisciplinary design education. Journal of Learning Design, 13(1), 44–56. https://doi.org/10.5204/jld.v13i1.640
Published
2025-12-15
How to Cite
Fei , Y.-M., & Liu , W.-C. (2025). Empowering business students through culturally responsive Internet of Things education: insights from a modular biomedical circuit curriculum. Research in Learning Technology, 33. https://doi.org/10.25304/rlt.v33.3545
Issue
Vol. 33 (2025)
Section
Original Research Articles
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