Journal of Industrial and Systems Engineering

Journal of Industrial and Systems Engineering

Examining the Impact of Online Education on Iranian Engineering Students during COVID-19: MCDM and Machine Learning Approach

Document Type : Research Paper

Authors
Zahra Ghorbani 1
Abtin Boostani 2
Ali Ghorbanian 2
1 Edinburgh Business School, Business Management, Edinburgh, Scotland, UK
2 Department of Industrial Engineering, Esfarayen University of Technology, Esfarayen, Iran
Abstract
In this research, we introduce a comprehensive framework designed to assess the influence of remote learning during the COVID-19 pandemic on the sleep habits, interpersonal competencies, mental health, digital technology, and academic performance of engineering students. Additionally, we examine how these factors relate to the student's Grade Point Average (GPA). To achieve this, we conducted a web-based questionnaire survey involving 500 participants. The collected responses were subjected to various statistical analyses, including the Best-Worst Method, One-Sample Wilcoxon Signed Ranked Test, Spearman's Rank Correlation, Multilayer Perceptron, and K-nearest neighbors. The study outcomes revealed statistically significant impacts of online classes during the COVID-19 pandemic on several aspects, including delayed sleep time, sleep quality, emotional intelligence, critical thinking, stress levels, social isolation, distraction, social life, theoretical understanding, practical understanding, and course grades among students. Interestingly, no statistically significant differences were observed in irregular sleep schedules, communication, depression, and entertainment within the surveyed sample. Furthermore, the results indicated a significant gender-based difference in delayed sleep time and stress levels, with notable variations between male and female participants. Additionally, we leveraged machine learning algorithms to establish a quantitative framework for predicting students' GPAs in online classes. Since the situation of COVID-19 is still unstable in Iran and online education is still used in the education system, the insights from this research can aid educational leaders in devising effective strategies to maintain a positive learning experience for students.
Keywords
Online Education
Engineering Students
Grade Point Average
Best-Worst Method
Machine Learning
COVID-19 Pandemic
Subjects
Adams, R. V., & Blair, E. (2019). Impact of time management behaviors on undergraduate engineering students' performance. Sage Open, 9(1), 2158244018824506.
Ali, H. S., & Mohammed, Q. Q. (2020). Influence of Emotional Intelligence on Academic Achievement among Students at Secondary Schools in Babylon City. Indian Journal of Forensic Medicine & Toxicology, 14(1).
AlMahdawi, M., Senghore, S., Ambrin, H., & Belbase, S. (2021). High school students' performance indicators in distance learning in chemistry during the COVID-19 pandemic. Education Sciences, 11(11), 672.
Atlam, E. S., Ewis, A., Abd El-Raouf, M. M., Ghoneim, O., & Gad, I. (2022). A new approach in identifying the psychological impact of COVID-19 on university student's academic performance. Alexandria Engineering Journal, 61(7), 5223-5233.
Basilaia, G., Dgebuadze, M., Kantaria, M., & Chokhonelidze, G. (2020). Replacing the classic learning form at universities as an immediate response to the COVID-19 virus infection in Georgia.(March).
Benham, G. (2021). Stress and sleep in college students prior to and during the COVID‐19 pandemic. Stress and Health, 37(3), 504-515.
Brooks, S. K., Webster, R. K., Smith, L. E., Woodland, L., Wessely, S., Greenberg, N., & Rubin, G. J. (2020). The psychological impact of quarantine and how to reduce it: rapid review of the evidence. The Lancet, 395(10227), 912-920.
Brown, W. J., Wilkerson, A. K., Boyd, S. J., Dewey, D., Mesa, F., & Bunnell, B. E. (2018). A review of sleep disturbance in children and adolescents with anxiety. Journal of sleep research, 27(3), e12635.
Chabook, M. (2020, Feburary 23). Closing universities in 10 provinces by the end of the week to deal with the corona. Mehrnews Agancy. https://www.mehrnews.com/news/4860374/
Chen, C. C., & Jones, K. T. (2007). Blended learning vs. traditional classroom settings: Assessing effectiveness and student perceptions in an MBA accounting course. Journal of educators online, 4(1), n1.
Chen, C. C., Jones, K. T., & Xu, S. (2012). The communication methods of today's students. The CPA Journal, 82(11), 66.
Cohen, L., Manion, L., & Morrison, K (2007). Research Methods in Education.
Driscoll, M., & Carliner, S. (2005). Advanced web-based training strategies: Unlocking instructionally sound online learning. John Wiley & Sons.
Feng, S., Wong, Y. K., Wong, L. Y., & Hossain, L. (2019). The Internet and Facebook usage on academic distraction of college students. Computers & Education, 134, 41-49.
Fruehwirth, J. C., Biswas, S., & Perreira, K. M. (2021). The Covid-19 pandemic and mental health of first-year college students: Examining the effect of Covid-19 stressors using longitudinal data. PloS one, 16(3), e0247999.
Grubic, N., Badovinac, S., & Johri, A. M. (2020). Student mental health in the midst of the COVID-19 pandemic: A call for further research and immediate solutions. International Journal of Social Psychiatry, 66(5), 517-518.
Henriksen, D., Creely, E., Henderson, M., & Mishra, P. (2021). Creativity and technology in teaching and learning: a literature review of the uneasy space of implementation. Educational Technology Research and Development, 69(4), 2091-2108.
Hershner, S. (2020). Sleep and academic performance: Measuring the impact of sleep. Current Opinion in Behavioral Sciences, 33, 51-56.
Hew, K.F.; Cheung, W.S.; Ng, CSL Student contribution in asynchronous online discussion: A review of the research and empirical exploration. Instr. Sci. 2010, 38, 571–606.
Iqbal, J., Qureshi, N., Ashraf, M. A., Rasool, S. F., & Asghar, M. Z. (2021). The effect of emotional intelligence and academic social networking sites on academic performance during the COVID-19 pandemic. Psychology Research and Behavior Management, 14, 905.
Jamet, E., Gonthier, C., Cojean, S., Colliot, T., & Erhel, S. (2020). Does multitasking in the classroom affect learning outcomes? A naturalistic study. Computers in Human behavior, 106, 106264.
Jones, S. (2008). Internet goes to college: How students are living in the future with today's technology. Diane Publishing.
Koosha, H. R., Ghorbani, Z., & Nikfetrat, R. (2022). A Clustering-Classification Recommender System based on Firefly Algorithm. Journal of AI and Data Mining, 10(1), 103-116.
Lee, J. E., & Recker, M. (2021). The effects of instructors' use of online discussions strategies on student participation and performance in university online introductory mathematics courses. Computers & Education, 162, 104084.
Limniou, M. (2021). The effect of digital device usage on student academic performance: A case study. Education Sciences, 11(3), 121.
Limniou, M., Varga-Atkins, T., Hands, C., & Elshamaa, M. (2021). Learning, student digital capabilities and academic performance over the COVID-19 pandemic. Education Sciences, 11(7), 361.
Mandasari, B. (2020). The impact of online learning toward students' academic performance on business correspondence course. EDUTEC: Journal of Education and Technology, 4(1), 98-110.
May, K. E., & Elder, A. D. (2018). Efficient, helpful, or distracting? A literature review of media multitasking in relation to academic performance. International Journal of Educational Technology in Higher Education, 15(1), 1-17.
Moore, M. (2012). Behavioral sleep problems in children and adolescents. Journal of clinical psychology in medical settings, 19(1), 77-83.
Movahed, A. B., Aliahmadi, A., Parsanejad, M., & Nozari, H. (2023). A systematic review of collaboration in supply chain 4.0 with meta-synthesis method. Supply Chain Analytics, 4, 100052.
Norboevich, T. B. (2020). Analysis of psychological theory of emotional intelligence. Eur J Res Reflect Educ Sci, 8(3), 99-104.
Nozari, H., Abdi, H., & Szmelter-Jarosz, A. (2025). Goat Optimization Algorithm: A Novel Bio-Inspired Metaheuristic for Global Optimization. arXiv preprint arXiv:2503.02331.
Nozari, H., Rahmaty, M., Foukolaei, P. Z., Movahed, H., & Bayanati, M. (2025). Optimizing Cold Chain Logistics with Artificial Intelligence of Things (AIoT): A Model for Reducing Operational and Transportation Costs. Future Transportation, 5(1), 1.
Olakanmi, E. E. (2017). The effects of a flipped classroom model of instruction on students' performance and attitudes towards chemistry. Journal of Science Education and Technology, 26(1), 127-137.
Ordway, M. R., Condon, E. M., Ibrahim, B. B., Abel, E. A., Funaro, M. C., Batten, J., ... & Redeker, N. S. (2021). A systematic review of the association between sleep health and stress biomarkers in children. Sleep medicine reviews, 59, 101494.
Pokhrel, S., & Chhetri, R. (2021). A literature review on impact of COVID-19 pandemic on teaching and learning. Higher Education for the Future, 8(1), 133-141.
Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53, 49-57.
Robillard, R., Dion, K., Pennestri, M. H., Solomonova, E., Lee, E., Saad, M., ... & Kendzerska, T. (2021). Profiles of sleep changes during the COVID‐19 pandemic: Demographic, behavioural and psychological factors. Journal of sleep research, 30(1), e13231.
Robillard, R., Dion, K., Pennestri, M. H., Solomonova, E., Lee, E., Saad, M., ... & Kendzerska, T. (2021). Profiles of sleep changes during the COVID‐19 pandemic: Demographic, behavioural and psychological factors. Journal of sleep research, 30(1), e13231.
Rodríguez-Planas, N. (2022). COVID-19, college academic performance, and the flexible grading policy: A longitudinal analysis. Journal of Public Economics, 207, 104606.
Songkram, N. (2017). Online Course Design for Creativity and Innovative Skills in Virtual Cultural ASEAN Community. International Journal of Emerging Technologies in Learning, 12(1).
Stegmann, K., Wecker, C., Weinberger, A., & Fischer, F. (2012). Collaborative argumentation and cognitive elaboration in a computer-supported collaborative learning environment. Instructional Science, 40(2), 297-323.
Wang, C., Pan, R., Wan, X., Tan, Y., Xu, L., Ho, C. S., & Ho, R. C. (2020). Immediate psychological responses and associated factors during the initial stage of the 2019 coronavirus disease (COVID-19) epidemic among the general population in China. International journal of environmental research and public health, 17(5), 1729.
WHO   (2020   (accessed   April   13,   2020))   Coronavirus. https://www.who.int/health-topics/coronavirus.
Wiles, G. (2020, July 30). Students share impact of online classes on their mental health. The State News. Retrieved from: https://statenews.com/article/2020/07/students-share-impact-of-onlineclasses-on-their-mental-health?ct=content_open&cv=cbox_latest
Wright Jr, K. P., Linton, S. K., Withrow, D., Casiraghi, L., Lanza, S. M., de la Iglesia, H., ... & Depner, C. M. (2020). Sleep in university students prior to and during COVID-19 Stay-at-Home orders. Current biology, 30(14), R797-R798.
Zarzycka, E., Krasodomska, J., Mazurczak-Mąka, A., & Turek-Radwan, M. (2021). Distance learning during the COVID-19 pandemic: students' communication and collaboration and the role of social media. Cogent Arts & Humanities, 8(1), 1953228.
Zhuo, K., Gao, C., Wang, X., Zhang, C., & Wang, Z. (2020). Stress and sleep: a survey based on wearable sleep trackers among medical and nursing staff in Wuhan during the COVID-19 pandemic. General psychiatry, 33(3).

  • Receive Date 29 January 2024
  • Revise Date 27 June 2024
  • Accept Date 04 July 2024