The Influence of Wearable Device Technology on Enhancing Student Learning Outcomes: A Comprehensive Study
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Published:
Dec 30, 2024
Keywords:
Wearable Devices, Student Learning Outcomes, Educational Technology, Self-Regulated Learning, Digital Engagement
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Articles
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Abstract
The rapid advancement of wearable device technology has introduced new opportunities to enhance educational practices and student learning outcomes. This research investigates the impact of wearable device usage on improving students' academic performance, engagement, and self-regulation. Through a mixed-method approach involving surveys and observational studies, the findings reveal that wearable devices positively influence learning by promoting time management, providing real-time feedback, and encouraging active participation. However, challenges such as accessibility, potential distractions, and data privacy concerns also emerged. Comparisons with previous research confirm the consistent benefits of wearable technologies while highlighting the need for careful implementation and policy development. The study concludes that with strategic integration, wearable devices can serve as valuable tools to foster improved learning experiences, suggesting further longitudinal research and inclusive practices to maximize their potential in diverse educational settings.
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How to Cite
Hanif, N. K., & Nova, E. (2024). The Influence of Wearable Device Technology on Enhancing Student Learning Outcomes: A Comprehensive Study. Journal of Education Innovation and Curriculum Development, 2(3), 82–89. Retrieved from https://journals.iarn.or.id/index.php/educur/article/view/443
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Bower, M., & Sturman, D. (2015). What are the educational affordances of wearable technologies? Computers & Education, 88, 343–353.
Caballé, S., Xhafa, F., & Barolli, L. (2010). Using mobile devices to support online collaborative learning. Mobile Information Systems, 6(1), 27–47.
Capaccio, M. M. (2017). The Impact of Personal Media Devices on Undergraduate College Student Engagement. Point Park University.
Cho, I., Kaplanidou, K., & Sato, S. (2021). Gamified wearable fitness tracker for physical activity: a comprehensive literature review. Sustainability, 13(13), 7017.
Datnow, A., & Park, V. (2014). Data-driven leadership. John Wiley & Sons.
Evmenova, A. S., Graff, H. J., Genaro Motti, V., Giwa-Lawal, K., & Zheng, H. (2019). Designing a wearable technology intervention to support young adults with intellectual and developmental disabilities in inclusive postsecondary academic environments. Journal of Special Education Technology, 34(2), 92–105.
Gresham, G., Hendifar, A. E., Spiegel, B., Neeman, E., Tuli, R., Rimel, B. J., Figlin, R. A., Meinert, C. L., Piantadosi, S., & Shinde, A. M. (2018). Wearable activity monitors to assess performance status and predict clinical outcomes in advanced cancer patients. NPJ Digital Medicine, 1(1), 27.
Henrie, C. R. (2016). Measuring student engagement in technology-mediated learning environments. Brigham Young University.
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.
Kaisler, S., Armour, F., Espinosa, J. A., & Money, W. (2013). Big data: Issues and challenges moving forward. 2013 46th Hawaii International Conference on System Sciences, 995–1004.
Keus, K., Grunwald, J., & Haave, N. (2019). A Method to the Midterms: The Impact of a Second Midterm on Students’ Learning Outcomes. Bioscene: Journal of College Biology Teaching, 45(1), 3–8.
Koutromanos, G., & Kazakou, G. (2020). The Use of Smart Wearables in Primary and Secondary Education: A Systematic Review. Themes in ELearning, 13, 33–53.
Lee, J., Kim, D., Ryoo, H.-Y., & Shin, B.-S. (2016). Sustainable wearables: Wearable technology for enhancing the quality of human life. Sustainability, 8(5), 466.
Loncar-Turukalo, T., Zdravevski, E., da Silva, J. M., Chouvarda, I., & Trajkovik, V. (2019). Literature on wearable technology for connected health: scoping review of research trends, advances, and barriers. Journal of Medical Internet Research, 21(9), e14017.
Macklem, G. L. (2015). Boredom in the classroom: Addressing student motivation, self-regulation, and engagement in learning (Vol. 1). Springer.
Meadows, M. (2017). 365 Days with Self-discipline: 365 Life-altering Thoughts on Self-control, Mental Resilience, and Success (Vol. 5). Meadows Publishing.
Park, S., & Jayaraman, S. (2003). Enhancing the quality of life through wearable technology. IEEE Engineering in Medicine and Biology Magazine, 22(3), 41–48.
Pietilä, A.-M., Nurmi, S.-M., Halkoaho, A., & Kyngäs, H. (2019). Qualitative research: Ethical considerations. In The application of content analysis in nursing science research (pp. 49–69). Springer.
Ribeiro, J. (2018). Wearable technology spending: A strategic approach to decision-making. In Wearable Technologies: Concepts, Methodologies, Tools, and Applications (pp. 517–537). IGI Global.
Sano, A., Phillips, A. J., Amy, Z. Y., McHill, A. W., Taylor, S., Jaques, N., Czeisler, C. A., Klerman, E. B., & Picard, R. W. (2015). Recognizing academic performance, sleep quality, stress level, and mental health using personality traits, wearable sensors and mobile phones. 2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN), 1–6.
Shroff, R. H., & Vogel, D. R. (2009). Assessing the factors deemed to support individual student intrinsic motivation in technology supported online and face-to-face discussions. Journal of Information Technology Education: Research, 8(1), 59–85.
Solomon, J. (2021). Using Wearable Assistive Technology to Improve Time Management of Students with Disabilities in a School-Based Employment Training Setting.
Viana, P., Ferreira, T., Castro, L., Soares, M., Pinto, J. P., Andrade, T., & Carvalho, P. (2018). GymApp: A real time physical activity trainner on wearable devices. 2018 11th International Conference on Human System Interaction (HSI), 513–518.
Wagner, D. T., Rice, A., & Beresford, A. R. (2013). Device analyzer: Understanding smartphone usage. International Conference on Mobile and Ubiquitous Systems: Computing, Networking, and Services, 195–208.
Winne, P. H., & Perry, N. E. (2000). Measuring self-regulated learning. In Handbook of self-regulation (pp. 531–566). Elsevier.
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