Improving online learning through student stress evaluation

Elty Sarvia, Christina Wirawan, Meilena Kristianti, Zukhruf Ramadhani

Abstract


The COVID-19 pandemic impacted almost all countries and caused disruptions in education. Governments, including Indonesia, closed schools and campuses to mitigate the spread of COVID-19, leading to a transition to online learning. This lasted for two years and continued with hybrid learning. The abrupt change increased stress, especially for already stressed students. This study assessed stress levels during online learning at the Industrial Engineering Study Programme of Maranatha Christian University, Bandung. Stress was measured subjectively using the Perceived Stress Scale (PSS) and objectively using Galvanic Skin Response (GSR) and pulse sensors on thirty-two students. The PSS results classified the stress perception of most students as ‘normal’ or ‘moderate’. Meanwhile, the results of the GSR and pulse sensor measurements indicated that the students were stressed. Furthermore, a comparison of stress levels between synchronous and asynchronous learning and between mathematics and theory courses was conducted. According to the findings, there was a difference in the average heart rate values between synchronous and asynchronous learning. There was also a difference between mathematics and theory courses. With this research, it is necessary to pay attention to learning methods, materials, etc. need to be designed to reduce student stress and improve student performance.

Keywords


Online Learning; Stress; Perceived Stress Scale (PSS); Galvanic Skin Response (GSR); Pulse Sensor

Full Text:

PDF

References


A. M. Kashyap, S. Sailaja, K. Venkata, R. Srinivas, S. Suryanarayana, and R. 4#, “Challenges in Online Teaching amidst Covid Crisis: Impact on Engineering Educators of Different Levels,” Journal of Engineering Education Transformations, vol. 34, pp. 2394–1707, 2021.

E. M. Onyema, S. Sen, F. Obafemi, and Sharma Aabha, “Impact of Coronavirus Pandemic on Education,” Journal of Education and Practice, vol. 11, no. 13, pp. 108–121, May 2020, doi: 10.7176/jep/11-13-12.

W. Andriani, M. Subandowo, H. Karyono, and W. Gunawan, “Learning Loss dalam Pembelajaran Daring di masa Pandemi Corona (Learning Loss in Online Learning during the Corona Pandemic),” in Seminar Nasional Pemberdayaan Teknologi Teknologi Pembelajaran Pembelajaran dalam Tatanan Multidisipliner di Era 4.0, Aug. 2021, pp. 484–501. [Online]. Available: http://snastep.com/proceeding/index.php/snastep/index

E. Timotius and G. S. Octavius, “Stress at the Workplace and Its Impacts on Productivity: A Systematic Review from Industrial Engineering, Management, and Medical Perspective,” 2022, Korean Institute of Industrial Engineers. doi: 10.7232/iems.2022.21.2.192.

R. F. Navea, P. J. Buenvenida, and C. D. Cruz, “Stress Detection using Galvanic Skin Response: An Android Application,” J Phys Conf Ser, vol. 1372, no. 012001, pp. 1–6, 2019, doi: 10.1088/1742-6596/1372/1/012001.

Firman, A. P. Sari, and Firdaus, “Aktivitas Mahasiswa dalam Pembelajaran Daring Berbasis Konferensi Video: Refleksi Pembelajaran Menggunakan Zoom dan Google Meet (Student Activities in Video Conference-Based Online Learning: Learning Reflections Using Zoom and Google Meet).,” Indonesian Journal of Educational Science (IJES), vol. 03, no. 02, pp. 130–137, Mar. 2021.

S. F. Chan and A. M. La Greca, “Perceived Stress Scale (PSS),” in Encyclopedia of Behavioral Medicine, Cham: Springer International Publishing, 2020, pp. 1646–1648. doi: 10.1007/978-3-030-39903-0_773.

S. Cohen, T. Kamarck, and R. Mermelstein, “A Global Measure of Perceived Stress,” 1983.

J. Hernandez, R. R. Morris, and R. W. Picard, “Call Center Stress Recognition with Person-Specific Models,” Springer-Verlag Berlin Heidelberg, pp. 125–134, 2011.

E. Labbe, N. Schmidt, J. Babin, and M. Pharr, “Coping with Stress: The Effectiveness of Different Types of Music,” Appl Psychophysiol Biofeedback , vol. 32, pp. 163–168, Oct. 2007, doi: 10.1007/s10484-007-9043-9.

M. Laeremans et al., “Physical activity and sedentary behaviour in daily life: A comparative analysis of the Global Physical Activity Questionnaire (GPAQ) and the SenseWear armband,” PLoS One, vol. 12, no. 5, May 2017, doi: 10.1371/journal.pone.0177765.

X. Yang et al., “The effects of traveling in different transport modes on galvanic skin response (GSR) as a measure of stress: An observational study,” J Phys Conf Ser, vol. 156, pp. 1–10, Jul. 2021, doi: 10.1016/j.envint.2021.106764.

F. Deza, P. Madona, and N. Rahmardy, “Alat Pendeteksi Tingkat Stress Manusia Berdasarkan Suhu Tubuh, Kelembaban Kulit, Tekanan Darah dan Detak Jantung (Human Stress Level Detection Tool Based on Body Temperature, Skin Moisture, Blood Pressure and Heart Rate).,” Jurnal Elektro dan Mesin Terapan, vol. 3, no. 2, pp. 31–42, Nov. 2017, doi: 10.35143/elementer.v3i2.194.

B. N. Böke, D. J. Mills, J. Mettler, and N. L. Heath, “Stress and coping patterns of university students,” J Coll Stud Dev, vol. 60, no. 1, pp. 85–103, Jan. 2019, doi: 10.1353/csd.2019.0005.

A. I. Clinciu, “Adaptation and Stress for the First Year University Students,” Procedia Soc Behav Sci, vol. 78, pp. 718–722, May 2013, doi: 10.1016/j.sbspro.2013.04.382.

R. J. Murphy, S. A. Gray, G. Sterling, K. Reeves, and J. DuCette, “A Comparative Study of Professional Student Stress,” J Dent Educ, vol. 73, no. 3, pp. 328–337, Mar. 2009, doi: 10.1002/j.0022-0337.2009.73.3.tb04705.x.

M. C. Zurlo, M. F. Cattaneo Della Volta, and F. Vallone, “COVID-19 Student Stress Questionnaire: Development and Validation of a Questionnaire to Evaluate Students’ Stressors Related to the Coronavirus Pandemic Lockdown,” Front Psychol, vol. 11, Oct. 2020, doi: 10.3389/fpsyg.2020.576758.

S. Maroufizadeh, F. Foroudifard, B. Navid, Z. Ezabadi, B. Sobati, and R. Omani-Samani, “The Perceived Stress Scale (PSS-10) in women experiencing infertility: A reliability and validity study,” Middle East Fertil Soc J, vol. 23, no. 4, pp. 456–459, Dec. 2018, doi: 10.1016/j.mefs.2018.02.003.

M. A. Vallejo, L. Vallejo-Slocker, E. G. Fernández-Abascal, and G. Mañanes, “Determining factors for stress perception assessed with the Perceived Stress Scale (PSS-4) in Spanish and other European samples,” Front Psychol, vol. 9, no. JAN, Jan. 2018, doi: 10.3389/fpsyg.2018.00037.

L. Yan, Y. Gan, X. Ding, J. Wu, and H. Duan, “The relationship between perceived stress and emotional distress during the COVID-19 outbreak: Effects of boredom proneness and coping style,” J Anxiety Disord, vol. 77, pp. 1–11, Jan. 2021, doi: 10.1016/j.janxdis.2020.102328.

X. Zhao, M. Lan, H. Li, and J. Yang, “Perceived stress and sleep quality among the non-diseased general public in China during the 2019 coronavirus disease: a moderated mediation model,” Sleep Med, vol. 77, pp. 339–345, Jan. 2021, doi: 10.1016/j.sleep.2020.05.021.

M. Chauhan, S. V Vora, and D. Dabhi, “Effective Stress Detection using Physiological Parameters.”

P. Melillo, M. Bracale, and L. Pecchia, “Nonlinear Heart Rate Variability features for real-life stress detection. Case study: students under stress due to university examination,” Biomed Eng Online, vol. 10, no. 96, 2011.

B. Szakonyi, I. Vassányi, E. Schumacher, and I. Kósa, “Efficient methods for acute stress detection using heart rate variability data from Ambient Assisted Living sensors,” Biomed Eng Online, vol. 20, no. 1, Dec. 2021, doi: 10.1186/s12938-021-00911-6.

J. Zhang, W. Wen, F. Huang, and G. Liu, “Recognition of real-scene stress in examination with heart rate features,” in Proceedings - 9th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2017, Institute of Electrical and Electronics Engineers Inc., Sep. 2017, pp. 26–29. doi: 10.1109/IHMSC.2017.13.

A. Cantara and A. Ceniza, “Stress Sensor Prototype: Determining the Stress Level in using a Computer through Validated Self-Made Heart Rate (HR) and Galvanic Skin Response (GSR) Sensors and Fuzzy Logic Algorithm,” International Journal of Engineering Research & Technology (IJERT), vol. 5, no. 3, pp. 28–37, 2016, [Online]. Available: https://www.researchgate.net/publication/314793426

N. Widanti, B. Sumanto, P. Rosa, and M. F. Miftahudin, “Stress Level Detection using Heart Rate, Blood Pressure, and GSR and Stress Therapy by Utilizing Infrared,” in International Conference on Industrial Instrumentation and Control (ICIC), India: Col/ege of Engineering Pune, May 2015, pp. 275–279.

A. Widarjono, Analisis Statistika Multivariat Terapan (Applied Multivariate Statistical Analysis). Yogyakarta: UPP STIM YKPN, 2010.

C. Park, M. Wang, and W. Y. Hwang, “Empirical Distributions of the Robustified t-test Statistics,” Industrial Engineering and Management Systems, vol. 21, no. 3, pp. 432–439, Sep. 2022, doi: 10.7232/iems.2022.21.3.432.

M. Kuncoro, Metode Riset Untuk Bisnis & Ekonomi (Research Methods For Business & Economics). Jakarta : Erlangga. , 2009.

E. Suwarto, “Alat Pendeteksi Parameter Stres Manusia Berbasis MikrokontrolerATMega 16 (Microcontroller-Based Human Stress Parameter Detection Tool ATMega),” ORBITH , vol. 8, no. 1, 2012.

F. Joseph, J. B. Barry, E. A. Rolph, and E. A. Rolph, Multivariate data analysis. Pearson Prentice Hall, 2010.

F. Amiti, “Synchronous and Asynchronous E-Learning,” European Journal of Open Education and E-learning Studies, vol. 5, no. 2, Sep. 2020, doi: 10.46827/ejoe.v5i2.3313.

S. Agarwal and J. Dewan, “An Analysis of the Effectiveness of Online Learning in Colleges of Uttar Pradesh during the COVID 19 Lockdown,” Journal of Xi’an University of Architecture & Technology, vol. XII, no. V, pp. 2957–2963, 2020, [Online]. Available: https://nptel.ac.in/

I. M. Satyawan, Wahjoedi, and I. K. I. Swadesi, “The Effectiveness of Online Learning Through Undiksha E-Learning During the Covid-19 Pandemic,” Journal of Education Technology, vol. 5, no. 2, pp. 191–199, 2021, [Online]. Available: https://ejournal.undiksha.ac.id/index.php/JET

Suprianto, S. Hardiyanti Arhas, Mahmudin, and A. Onny Siagian, “The Effectiveness of Online Learning Amid the COVID-19 Pandemic,” Jurnal Administrare: Jurnal Pemikiran Ilmiah dan Pendidikan Administrasi Perkantoran, vol. 7, no. 2, pp. 321–330, 2020, [Online]. Available: http://ojs.unm.ac.id/index.php/administrare/index

J. Gozaly, Y. Talar, C. Wirawan, and A. V. Kurniawan, “Effectiveness of online learning in non-online classes during the pandemic,” Management in Education, 2023, doi: 10.1177/08920206231157509.




DOI: https://doi.org/10.31315/opsi.v17i2.10982

Refbacks

  • There are currently no refbacks.




Secretariat:
Industrial Engineering Department
Faculty of Industrial Engineering, UPN "Veteran" Yogyakarta
d.a Jalan Babarsari 2 Tambakbayan Yogyakarta 55281
Telp. (0274) 486256
Website http://jurnal.upnyk.ac.id/index.php/opsi
email : jurnal.opsi@upnyk.ac.id

 

indexed by:

 
 
 


Lisensi Creative Commons
This work is Licensed Under a Creative Commons Attribution 4.0 International license.

View My Stats
slot gacor slot gacor hari ini slot gacor 2025 demo slot pg slot gacor slot gacor