Abstract
Across the globe, online learning has become the new order in tertiary education, and Nigeria is no exception. The traditional face-to-face and classroom method of teaching and learning is slowly being replaced by online teaching and learning, which causes some students to stress due to the difficulties they encounter. It may also cause health issues. Study aims to discover if there is a possible link between student stress and online learning in Jos, Nigeria. In this study, students at the University of Jos, Plateau State Polytechnic, Federal School of Medical Laboratory Science in Jos, and School of Nursing in Jos were asked to complete Perceived Stress Scale (PSS) questionnaires. Using the PSS scale, the study shows prevalence of low stress as 17% (N = 85), medium stress with 66% (N = 330), and high stress is 17% (N = 85) among the students in Jos, Nigeria. According to the sample results, the mean PSS-10 tally is 18.65 (SD = 6.37). The PSS-10 total score held no gender differences which indicates that women (M = 17.35, SD = 5.06) felt similarly stressed to men (M = 18.05, SD = 5.07). With coordinated coping mechanisms, students should experience less stress and mental health challenges when utilizing online learning at Jos tertiary institutions. In a stress-filled environment, they can use the stress as an incentive to improve their performance and learning. While the distress component must be reduced, coping may be considered for some limits.
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Acknowledgements
We acknowledge the cooperation of tertiary students in Jos who despite the crisis in Jos participated in the study based on experience during online studies during institutional short down.
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The study ethical clearance was gotten from the Ethical Committee of Federal School of Medical Laboratory Science (FSMLS), Jos via the letter (Ref. No.: EC/FSMLS/021/2021) on 2nd September 2021.
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Obeta, U.M., Etukudoh, N.S., Chhetri, B., Goyal, L.M. (2022). Tertiary Students Stress Detection During Online Learning in Jos, Nigeria. In: Mittal, M., Goyal, L.M. (eds) Predictive Analytics of Psychological Disorders in Healthcare. Lecture Notes on Data Engineering and Communications Technologies, vol 128. Springer, Singapore. https://doi.org/10.1007/978-981-19-1724-0_12
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