Impact of the Covid-19 Pandemic on the Metacognition and Emotional Intelligence of Natural Science Students

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Keywords

emotional intelligence
metacognition
metacognitive regulation
reflection
self-organization
purposefulness
perseverance
pandemic
higher education
remote learning

Abstract

Introduction. This paper presents the results of an empirical study that compares the parameters of the metacognitive components and emotional intelligence (EI) of young people using cross-sectional surveys before and during the COVID-19 pandemic. This study explores, for the first time, the effects of remote learning during the COVID-19 pandemic using samples of natural science students. Methods. The sample was comprised of 551 second-year students at St. Petersburg State University, 260 of whom took part in the study in 2018–2019; 98 respondents took part in the study in May 2020; 114 respondents took part in the study in January 2021; 79 respondents took part in the study in May 2021. The study used the following diagnostic tools: (a) the Emotional Intelligence Questionnaire developed by D. V. Lyusin, (b) a short version of the Metacognitive Awareness Inventory modified by E. I. Perikova and V. M. Byzova, (c) the Differential Test of Reflectivity developed by D. A. Leontiev and E. N. Osin, and (d) the Self-organization of Activity Questionnaire developed by E. Yu. Mandrikova. Results. The study showed an increase in the scores of metacognitive awareness and metacognitive regulation, as well as a reduction in interpersonal EI in students during the COVID-19 pandemic, compared to the pre-pandemic group. Students’ scores of purposefulness and intrapersonal EI increased significantly during the pandemic. However, the differences were only significant in some pandemic subgroups. The predictors contributing to the level of intrapersonal EI differed in the pre-pandemic and pandemic groups. Systemic reflection and purposefulness were significant predictors of the level of intrapersonal EI for the pre-pandemic group (explained 11 % of the variance). Systemic reflection, metacognitive knowledge, and perseverance were significant predictors of the level of intrapersonal EI for the pandemic group (explained 28 % of the variance). Discussion. The emerging transition from the classical form of learning to remote learning, in the context of the Coronavirus pandemic, seems to lead to an improvement in metacognitive regulation and a decline in interpersonal EI in students of natural sciences.

https://doi.org/10.21702/rpj.2022.1.9
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PDF (Russian)

References

Aleshkovskii, I. A., Gasparishvili, A. T., Krukhmaleva, O. V., Narbut, N. P., & Savina, N. E. (2020). Russian university students about distance learning: Assessments and opportunities. Vysshee obrazovanie v Rossii (Higher Education in Russia), 29(10), 86–100. https://doi.org/10.31992/0869-3617-2020-29-10-86-100 (in Russ.).

Allodola, V. F., Buccolo, M., & Mongili, S. (2020). Representations and emotions on Covid-19 in Italy: An exploratory research. International Journal of Psychoanalysis and Education, 12(1), 15–30.

Baranova, V. A., Dubovskaya, E. M., & Savina, O. O. (2021). Life experience and resources for overcoming the difficulties of social isolation in the first period of the COVID-19 pandemic among students. Sotsial'naya psikhologiya i obshchestvo (Social Psychology and Society), 12(1), 10–25. https://doi.org/10.17759/sps.2021120102 (in Russ.).

Barzilay, R., Moore, T. M, Greenberg, D. M, DiDomenico, G. E., Brown, L. A., White, L. K., … Gur, R. E. (2020). Resilience, COVID-19-related stress, anxiety and depression during the pandemic in a large population enriched for healthcare providers. Translational Psychiatry, 10, 291. https://doi.org/10.1038/s41398-020-00982-4

Bazanova, E. M., & Sokolova, E. E. (2017). Massive open online course on academic writing: Management of students’ motivation to study. Vysshee obrazovanie v Rossii (Higher Education in Russia), 2, 99–109. (in Russ.).

Bekova, S. K., Terentev, E. A., & Maloshonok, N. G. (2021). Educational inequality and COVID 19 pandemic: Relationship between the family socio-economic status and student experience of remote learning. Voprosy obrazovaniya (Educational Studies Moscow), 1, 74–92. https://doi.org/10.17323/1814-9545-2021-1-74-92 (in Russ.).

Bekova, S. K., Vilkova, K. A., Dzhafarova, Z. I., Larionova, V. A., Maloshonok, N. G., Semenova, T. V., … Shcheglova, I. A. (2020). Online, don’t panic! Models and effectiveness of integration of massive open online courses into Russian universities. Sovremennaia analitika obrazovaniia. Express-vypusk, 11. https://ioe.hse.ru/sovaobr (in Russ.).

Bysova, V. M., & Perikova, E. I. (2020). Emotional intelligence in the structure of metacognition among youth. In A. L. Zhuravlev, M. A. Kholodnaya, P. A. Sabadosh (Eds.). Abilities and mental human resources in the changes in a global world (pp. 318–324). Moscow: IP RAS. (in Russ.).

Carbon, C.-C. (2020). Wearing face masks strongly confuses counterparts in reading emotions. Frontiers in Psychology, 11. https://doi.org/10.3389/fpsyg.2020.566886

Carter Jr, R. A., Rice, M., Yang, S., & Jackson, H. A. (2020). Self-regulated learning in online learning environments: Strategies for remote learning. Information and Learning Sciences, 121(5/6), 321–329. https://doi.org/10.1108/ILS-04-2020-0114

Chirikov, I., Soria, K. M., Horgos, B., & Jones-White, D. (2020). Undergraduate and graduate students’ mental health during the COVID 19 pandemic. Berkeley: Center for Studies in Higher Education. Retrieved from https://escholarship.org/uc/item/80k5d5hw

Goodlet, K. J., Raney, E., Buckley, K., Afolabi, T., Davis, L., Fettkether, R. M., … Tennant, S. (2022). Impact of the COVID-19 pandemic on the emotional intelligence of student pharmacist leaders. American Journal of Pharmaceutical Education, 86(1). https://doi.org/10.5688/ajpe8519

Harris, L., Dargusch, J., Ames, K., & Bloomfield, C. (2020). Catering for ‘very different kids’: Distance education teachers’ understandings of and strategies for student engagement. International Journal of Inclusive Education. https://doi.org/10.1080/13603116.2020.1735543

Jia, M. (2021). The influence of distance learning during COVID-19 pandemic on student's self-regulated learning in higher education: A qualitative study. In 5th International conference on digital technology in education (pp. 47–52). https://doi.org/10.1145/3488466.3488492

Karpov, A. V., & Petrovskaya, A. S. (2008). Psychology of emotional intelligence: theory, diagnostics, practice. Yaroslavl: Yaroslavl State University. (in Russ.).

Khalimova, A. A., & Bogomaz, S. A. (2021). Psychological state of youth: emotional intelligence and meaning orientations under the conditions of pandemic. In B. S. Alishev, A. O. Prokhorov (Eds.). Psychology of mental states: Collection of materials of the XV International theoretical and practical conference for students, undergraduates, graduate students, young scientists, and university teachers (pp. 544–548). Kazan: Kazan University. (in Russ.).

Kizilcec, R. F., Saltarelli, A. J., Reich, J., & Cohen, G. L. (2017). Closing global achievement gaps in MOOCs. Science, 355(6322), 251–252. https://doi.org/10.1126/science.aag2063

Lahiri, D., Dubey, S., & Ardila, A. (2020, July). Impact of COVID-19 related lockdown on cognition and emotion: A pilot study. MedRxiv. https://doi.org/10.1101/2020.06.30.20138446

Leontiev, D. A., & Osin, E. N. (2014). “Good” and “bad” reflection: From an explanatory model to differential assessment. Psikhologiya. Zhurnal Vysshei shkoly ekonomiki (Psychology. Journal of the Higher School of Economics), 11(4), 110–135. (in Russ.).

Li, J.-B, Yang, A., Dou, K., & Cheung, R. Y. M. (2020). Self-control moderates the association between perceived severity of coronavirus disease 2019 (COVID-19) and mental health problems among the Chinese public. International Journal of Environmental Research and Public Health, 17(13), 4820. https://doi.org/10.3390/ijerph17134820

Lim, D. H., & Morris, M. L. (2009). Learner and instructional factors influencing learning outcomes within a blended learning environment. Educational Technology & Society, 12(4), 282–293.

Littlejohn, A., Hood, N., Milligan, C., & Mustain, P. (2016). Learning in MOOCs: Motivations and self-regulated learning in MOOCs. The Internet and Higher Education, 29, 40–48. https://doi.org/10.1016/j.iheduc.2015.12.003

Lyusin, D. V. (2009). An emotional intelligence questionnaire, EmIn: New psychometric data. In D. V. Lyusin, D. V. Ushakov (Eds.). Social and emotional intelligence: From models to measurements (pp. 264–278). Moscow: IP RAS. (in Russ.).

Magomed-Eminov, M. S. (2008). The phenomenon of extremeness. Moscow: Psychoanalytic Association. (in Russ.).

Mandrikova, E. Yu. (2010). The self-organization of activity questionnaire. Psikhologicheskaia diagnostika (Psychological Diagnostics), 2, 87–111. (in Russ.).

Melnichuk, M. V., & Belogash, M. A. (2021) Emotional intelligence as the subject of studying metacognitive processes in universities. Sibirskii pedagogicheskii zhurnal (Siberian Pedagogical Journal), 6, 89–100. https://doi.org/10.15293/1813-4718.2106.10 (in Russ.).

Milligan, C., & Littlejohn, A. (2014). Supporting professional learning in a massive open online course. The International Review of Research in Open and Distributed Learning, 15(5). https://doi.org/10.19173/irrodl.v15i5.1855

Moreno-Fernandez, J., Ochoa, J. J., Lopez-Aliaga, I., Alferez, M. J. M., Gomez-Guzman, M., Lopez-Ortega, S., & Diaz-Castro, J. (2020). Lockdown, emotional intelligence, academic engagement and burnout in pharmacy students during the quarantine, Pharmacy, 8(4), 194. https://doi.org/10.3390/pharmacy8040194

Pelikan, E. R., Lüftenegger, M., Holzer, J., Korlat, S., Spiel, C., & Schober, B. (2021). Learning during COVID-19: The role of self-regulated learning, motivation, and procrastination for perceived competence. Zeitschrift für Erziehungswissenschaft, 24, 393–418. https://doi.org/10.1007/s11618-021-01002-x

Perikova, E. I., & Bysova, V. M. (2021). Mental self-regulatory system of educational activities: Metacognitive approach. Sibirskiy Psikhologicheskiy Zhurnal (Siberian Journal of Psychology), 79, 15–29. https://doi.org/10.17223/17267080/79/2 (in Russ.).

Perikova, E. I., & Byzova, V. M. (In press). Factor structure of the Russian version of the Metacognitive Awareness Inventory. Кul'turno-istoricheskaya psikhologiya (Cultural-Historical Psychology). (in Russ.).

Rivers, D. J., Nakamura, M., & Vallance, M. (2021). Online self-regulated learning and achievement in the era of change. Journal of Educational Computing Research, 60(1), 104–131. https://doi.org/10.1177/07356331211025108

Serdyukov, P., & Hill, R. A. (2013). Flying with clipped wings: Are students independent in online college classes. Journal of Research in Innovative Teaching, 6(1), 52–65.

Sergienko, Е. A. (2014). The theory of mind as a paradigm of social cognition. Psikhologicheskie Issledovaniya (Psychological Studies), 7(36). http://psystudy.ru/index.php/num/2014v7n36/1017-sergienko36.html (in Russ.).

Soria, K. M., & Horgos, B. (2020, September). Social class differences in students’ experiences during the COVID-19 pandemic. UC Berkeley: Center for Studies in Higher Education. Retrieved from https://escholarship.org/uc/item/3hw2m00g

Soria, K. M., Chirikov, I., & Jones-White, D. (2020). The obstacles to remote learning for undergraduate, graduate, and professional students. UC Berkeley: Center for Studies in Higher Education. Retrieved from https://escholarship.org/uc/item/5624p4d7

Taylor, R., Thomas-Gregory, A., & Hofmeyer, A. (2020). Teaching empathy and resilience to undergraduate nursing students: A call to action in the context of Covid-19. Nurse Education Today, 94. https://doi.org/10.1016/j.nedt.2020.104524

Vargas Valencia, Á. R., Vega-Hernández, M. C., Aguila Sánchez, J. C., Vázquez Espinoza, J. A., & Hilerio López, Á. G. (2022). Self-perceived emotional intelligence levels in nursing students in times of a pandemic: Multivariate representation. International Journal of Environmental Research and Public Health, 19(3), 1811. https://doi.org/10.3390/ijerph19031811

Watson, S. L., Watson, W. R., Yu, J. H., Alamri, H., & Mueller, C. (2017). Learner profiles of attitudinal learning in a MOOC: An explanatory sequential mixed methods study. Computers & Education, 114, 274–285. https://doi.org/10.1016/j.compedu.2017.07.005

Williamson, B., Eynon, R., & Potter, J. (2020). Pandemic politics, pedagogies and practices: Digital technologies and distance education during the coronavirus emergency. Learning, Media and Technology, 45(2), 107–114. https://doi.org/10.1080/17439884.2020.1761641

Zheng, C., Liang, J.-C., Li, M., & Tsai, C.-C. (2018). The relationship between English language learners’ motivation and online self-regulation: A structural equation modelling approach. System, 76, 144–157. https://doi.org/10.1016/j.system.2018.05.003

Zimmerman, B. J. (2008). Investigating self-regulation and motivation: Historical background, methodological developments, and future prospects. American Educational Research Journal, 45(1), 166–183. https://doi.org/10.3102/0002831207312909

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