Examining the Effects of Physical Variables in Classrooms on Students' Attention via the Internet of Things

Year 2023, Volume: 10 Issue: 1, 160 - 177, 30.01.2023

Abdulkerim Aydın Yüksel Göktaş

https://doi.org/10.17275/per.23.9.10.1

Abstract

This study aims to examine the effects of physical variables (temperature, humidity, air quality, light, and sound) and those pertaining to the monitoring these physical variables on a group of students in terms of attention, motivation, attitudes, and perceptions of academic achievement (POA). The students were provided with a chance to monitor the physical variables through the Internet of Things (IoT) technology. This study employed a causal comparative design, which is a quantitative research method. The sample chosen by convenience sampling consisted of 262 undergraduate students from five different educational environments in the faculty of education of a large state university located in the Northeast Turkey. A prototype measuring the physical variables of the educational environments and enabling to send these to the internet was developed in the context of an IoT application, and it was ensured that the students in the five different educational environments monitored the physical variables for six weeks. Data were collected by use of the prototype created in the framework of IoT and a questionnaire. Consequently, it was concluded that the physical variables did not have significant effects on attitudes, but temperature, air quality, light, and sound had significant effects on students’ attention, motivation, and perceptions of academic achievement. Furthermore, results showed that monitoring the physical variables caused a difference in the students’ motivation, attention, attitudes, and POA.

Keywords

internet of things, education, physical variables, learning environment, air quality, smart classroom

Supporting Institution

* This study was created from the master's thesis titled " Examining the influence of physical variables in classrooms on students via internet of things application “.

References

• Airasian, P. W., & Gay, L. R. (2003). Educational research: Competencies for analysis and application. Prentice Hall. https://doi.org/10.37074/jalt.2018.1.2.1
• Atzori, L., Iera, A., & Morabito, G. (2010). The internet of things: A survey. Computer networks. 54(15), 2787-2805. https://doi.org/10.1016/j.comnet.2010.05.010
• Bako-Biro, Z., Clements-Croome, D. J., Kochhar, N., Awbi, H. B., & Williams, M. J. (2012). Ventilation rates in school sand pupils’ performance. Building and Environment, 48, 215-223. https://doi.org/10.1016/j.buildenv.2011.08.018
• Barrett, P. S., Zhang, Y., Davies, F., & Barrett, L. C. (2015). Clever classrooms: Summary report of the HEAD project. University of Salford. http://usir.salford.ac.uk/id/eprint/35221
• Başaran, I. E. (1996). Eğitim Psikolojisi. Ankara: Gül Yayınevi.
• Belissent, J. (2010). Getting clever about smart cities: new opportunities require new business models. Cambridge, Massachusetts, USA.
• Cech, P. (2016). Smart Classroom Study Design for Analysing the Effect of Environmental Conditions on Students’ Comfort. Intelligent Environments, 21, 14–23. https://doi.org/10.3233/978-1-61499-690-3-14
• Choi, K., & Suk, H. J. (2016). Dynamic lighting system for the learning environment: performance of elementary students. Optics express, 24(10), A907-A916. https://doi.org/10.1364/OE.24.00A907
• Daisey, J. M., Angell, W. J., & Apte, M. G. (2003). Indoor air quality, ventilation and health symptoms in schools: an analysis of existing information. Indoor air, 13(1), 53-64. https://doi.org/10.1034/j.1600-0668.2003.00153.x
• Driscoll, M. P. (2000). Psychology of learning for instruction. Needham Heights, MA: A Division of Paramount Publishing.
• Emmons, M., &Wilkinson, F. C. (2001). Designing the electronic classroom: Applying learning theory and ergonomic design principles. Library hi tech, 19(1), 77-87. https://doi.org/10.1108/07378830110384610
• Evans, D. (2011). The internet of things: How the next evolution of the internet is changing everything. CISCO whitepaper, 1(2011), 1-11. http://www.cisco.com/c/dam/en_us/about/ac79/docs/innov/IoT_IBSG_0411FINAL.pdf. Fraenkel, J. R., Wallen, N. E., &Hyun, H. H. (2011). How to design and evaluate research in education. McGraw-Hill.
• Gay, L. R., & Airasian, P. (2000). Educational research: Competencies for. Analysis and application (6th edition). Ohio: Prentice Hall.
• Grove (2017). Retrieved June 27, 2020, from http://wiki.seeed.cc/Grove_Starter_Kit_v3/.
• Gubbi, J., Buyya, R., Marusic, S., & Palaniswami, M. (2013). Internet of Things (IoT): A vision, architectural elements, and future directions. Future Generation Computer Systems, 29(7), 1645-1660. https://doi.org/10.1016/j.future.2013.01.010
• Guntha, R., Hariharan, B., & Rangan, P. V. (2016). Analysis of Echo Cancellation Techniquesin Multi-Perspective Smart Classroom. International Conference On Advances In Computing, Communications And Informatics (ICACCI), 1135-1140. https://doi.org/10.1109/ICACCI.2016.7732197
• Illeris, K. (Ed.). (2009). Contemporary theories of learning: learning theorists in their own words. Routledge.
• Johnson, E. (2001). Let’s hear it for learning: Improving classroom acoustics can maximize student productivity at a minimal cost. American School and University, 73(11), 28–30.
• Kaur, A., Bhatia, M., & Stea, G. (2022). A Survey of Smart Classroom Literature. Education Sciences, 12(2), 86. https://doi.org/10.3390/educsci12020086
• Lau, J., & Ng, K. M. (2014). Conceptualizing the counselling training environment using Bronfenbrenner’s ecological theory. International Journal for the Advancement of Counselling, 36(4), 423-439. https://doi.org/10.1007/s10447-014-9220-5
• Lei, S. A. (2010). Classroom physical design influencing student learning and evaluations of college instructors: A review of literature. Education, 131(1), 128-135.
• McMillan, J. H., & Schumacher, S. (2010). Research in education. Evidence-based research (7th ed.) London: Pearson.
• Orosa, J. A., Costa, Á. M., Rodríguez-Fernández, Á., &Roshan, G. (2014). Effect of climate change on outdoor thermal comfort in humid climates. Journal of Environmental Health Science and Engineering, 12(1), 46. https://doi.org/10.1186/2052-336X-12-46
• Palau, R., & Mogas, J. (2019). Systematic literature review for a characterization of the smart learning environments. In A. M. Cruz & A. I. Aguilar (Eds.), Propuestas multidisciplinares de innovación e intervención educativa. Universidad Internacional de Valencia.
• Recalde, J. M., Palau, R., Galés, N. L., & Gallon, R. (2020). Developments for smart classrooms: School perspectives and needs. International Journal of Mobile and Blended Learning (IJMBL), 12(4), 34-50. https://doi.org/10.4018/ijmbl.2020100103
• Schunk, D. H. (2009). Öğrenme teorileri. (Çev. Muzaffer Şahin) Ankara: Nobel Yayıncılık.
• Seppanen, O., Fisk, W. J., & Lei, Q. H. (2006). Effect of temperature on task performance in office environment. Lawrence Berkeley National Laboratory.
• Solso, R. L., Maclin, M. K., &Maclin, O. H. (2007). Bilişsel psikoloji (Çev. A. Ayçiçeği-Dinn). İstanbul: Kitabevi.
• Şimşek, A. (2009). Öğretim tasarımı. Nobel Yayın Dağıtım.
• Tanner, C. K. (2009). Effects of school design on student outcomes. Journal of Educational Administration, 47(3), 381-399. https://doi.org/10.1108/09578230910955809
• Uzelac, A., Gligoric, N., & Krco, S. (2015). A comprehensive study of parameters in physical environment that impact students’ focus during lecture using Internet of Things. Computers in Human Behavior, 53, 427-434. https://doi.org/10.1016/j.chb.2015.07.023
• Wargocki, P., & Wyon, D. P. (2007). The effects of moderately raised classroom temperatures and classroom ventilation rate on the performance of school work by children (RP-1257). Hvac & RResearch, 13(2), 193-220. https://doi.org/10.1080/10789669.2007.10390951
• Wells, V. K., & Daunt, K. L. (2016). Eduscape: The effects of servicescapes and emotions in academic learning environments. Journal of Further and Higher Education, 40(4), 486-508. https://doi.org/10.1080/0309877X.2014.984599