Examining the Pandemic Process from the Educational Perspective: What Are Scientific Studies Telling Us?

Yıl 2023, Cilt: 8 Sayı: 2, 221 - 236, 03.07.2023

Hatice Yıldız Durak , Şeyhmus Aydoğdu

https://doi.org/10.53850/joltida.1190421

Öz

Due to Covid-19 pandemic, one of the biggest crises occurred in the field of education. The number of students whose educational activities were interrupted because of the pandemic is an indicator of the effects of the pandemic on education. However, when the studies in the literature are examined, they mostly focus on the field of health. Studies in the field of education are relatively limited and the studies or data are unstructured. As a matter of fact, it is important to structure the data in the world created by data; to understand how the process works, to discover opportunities and the patterns that make up the world, to predict what will happen in new situations. In this context, the purpose of this study is to determine which issues are examined in the field of education in Turkey and around the world in the Covid-19 pandemic. In accordance with this purpose, analyzes were made using text mining techniques on text-based data. As a result of the research, in the international literature, more in-depth and theoretical research is included in the context of education, while in the national literature, situation determination and superficial distance education studies have been carried out.

Anahtar Kelimeler

Covid-19, text mining, topic analysis, scientific studies, educational perspective

Kaynakça

• Amelan, R. (2020). UN Secretary-General warns of education catastrophe, pointing to UNESCO estimate of 24 million learners at risk of dropping out. Retrieved from https://en.unesco.org/news/secretary-general-warns-education-catastrophe-pointing-unesco-estimate-24-million-learners-0
• Atman Uslu, N., & Yildiz Durak, H. (2022). Understanding self-regulation, achievement emotions, and mindset of undergraduates in emergency remote teaching: a latent profile analysis. Interactive Learning Environments, 1-20.
• Aydoğdu, Ş. (2020). Metin Madenciliği. In T. Güyer, H. Yurdugül, & S. Yıldırım (Eds.), Eğitsel veri madenciliği ve öğrenme analitikleri. Ankara: Anı.
• Azzalini, A., & Scarpa, B. (2012). Data analysis and data mining: An introduction. OUP USA.
• Balamurugan, R., & Pushpa, D. S. (2015). A Review on Various Text Mining Techniques and Algorithms. 2nd International Conference on recent innovations in science, engineering, and management JNU convention center, New Delhi, 22nd November.
• Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191–215.
• Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs, NJ, 1986(23-28).
• Bardak, T., & Sözen, E. (2018, October). Veri madenciliği ve önemi. 6th ASM International Congress of Agriculture and Environment, 2018 Proceeding Book.
• Bender, L. (2020). Key Messages and Actions for COVID-19 Prevention and Control in Schools. https://www.unicef.org/romania/documents/key-messages-and-actions-covid-19-prevention-and-control-schools
• Birinci, M., & Bulut, T. (2020). Covid-19’un Sosyo-Ekonomik Yönden Dezavantajlı Gruplar Üzerindeki Etkileri: Sosyal Hizmet Bakış Açısından Bir Değerlendirme. Sosyal Çalışma Dergisi, 4(1), 62-68.
• Bozkurt, A. (2020). Koronavirüs (Covid-19) pandemi süreci ve pandemi sonrası dünyada eğitime yönelik değerlendirmeler: Yeni normal ve yeni eğitim paradigması. Açıköğretim Uygulamaları ve Araştırmaları Dergisi, 6(3), 112-142.
• Bozkurt, A., Jung, I., Xiao, J., Vladimirschi, V., Schuwer, R., Egorov, G., ... & Rodes, V. (2020). A global outlook to the interruption of education due to COVID-19 Pandemic: Navigating in a time of uncertainty and crisis. Asian Journal of Distance Education, 15(1), 1-126.
• Chen, J., Chen, M., Qu, J., Chen, H., & Ding, J. (2018). Smart and connected health projects: Characteristics and research challenges. Paper presented at the International Conference on Smart Health.
• Cucinotta, D., & Vanelli, M. (2020). WHO declares COVID-19 a pandemic. Acta Bio Medica: Atenei Parmensis, 91(1), 157.
• Çiftçi, N. (2003). Kohlberg’in bilişsel ahlak gelişimi teorisi: Ahlak ve demokrasi eğitimi. Değerler Eğitimi Dergisi, 1(1), 43-77.
• Daniel, S. J. (2020). Education and the COVID-19 pandemic. Prospects, 1-6.
• Diakite, A., Dubourg, G., & Raoult, D. (2021). Updating the repertoire of cultured bacteria from the human being. Microbial Pathogenesis, 150, 104698.
• Drane, C. F., Vernon, L., & O’Shea, S. (2020b). Vulnerable learners in the age of COVID-19: A scoping review. The Australian Educational Researcher, 1-20.
• Drane, C., Vernon, L., & O’Shea, S. (2020a). The impact of ‘learning at home’on the educational outcomes of vulnerable children in Australia during the COVID-19 pandemic. Literature Review Prepared by the National Centre for Student Equity in Higher Education. Curtin University, Australia.
• Eren, E. (2020). Yeni Tip Koronavirüs'ün Türk eğitim politikaları uygulamalarına etkisi: Milli E¤itim Bakanlığının ve Yükseköğretim Kurulunun yeni düzenlemeleri. Yükseköğretim Dergisi, 10(2), 153–162. doi:10.2399/yod.20.716645.
• Feldman, R., & Dagan, I. 1995. KDT - knowledge discovery in texts. In Proceedings of the First International Conference on Knowledge Discovery (KDD-95). Menlo Park, CA: AAAI Press.
• Han, J., Kanber, M., & Pei, J. (2012). Data Mining. Concepts and Techniques. 3rd edition. Amsterdam: Elsevier Hung, J. L. (2012). Trends of e‐learning research from 2000 to 2008: Use of text mining and bibliometrics. British journal of educational technology, 43(1), 5-16.
• Jin, X., & Han, J. (2010). K-Means Clustering. In C. Sammut & G. I. Webb (Eds.), Encyclopedia of Machine Learning (pp. 563-564). Boston, MA: Springer US.
• Kohlberg, L. (1981). The philosophy of moral development moral stages and the idea of justice. Harper & Row, Cambridge.
• Kolesnikov, A. M., Lomachenko, T. I., Kokodey, T. A., Khitushchenko, V. V., & Mihailov, Y. I. (2019). A strategy of visualization and interactive support for university level educational digitalization. Paper presented at the 2019 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus).
• Lee, D. D., & Seung, H. S. (1999). Learning the parts of objects by non-negative matrix factorization. Nature, 401(6755), 788-791.
• Lloyd, S. P. (1957). Least squares quantization in PCM. Technical Report RR-5497, Bell Lab, September 1957.
• Lohmann, S., Heimerl, F., Bopp, F., Burch, M., & Ertl, T. (2015). Concentri cloud: Word cloud visualization for multiple text documents. Paper presented at the 2015 19th International Conference on Information Visualisation.
• Lopes, N., & Ribeiro, B. (2015). Non-Negative Matrix Factorization (NMF). In N. Lopes & B. Ribeiro (Eds.), Machine Learning for Adaptive Many-Core Machines - A Practical Approach (pp. 127-154). Cham: Springer International Publishing.
• MacQueen, J. B. (1967). Some methods for classification and analysis of multivariate observations. In L. M. Le Cam & J. Neyman (Eds.), Proceedings of the fifth Berkeley symposium on mathematical statistics and probability (Vol. 1, pp. 281–297). California: University of California Press.
• Milli Eğitim Bakanlığı (2020). İzleme ve Değerlendirme Raporu 2020 “Küresel Salgın Döneminde Uzaktan Eğitim”. http://covid19.meb.gov.tr/assets/files/02-rapor-yayin-bilgilendirme/04-raporlar/01.pdf
• Miner, G., Delen, D., Elder, J., Fast, A., Hill, T., & Nisbet, R. A. (2012). Practical text mining and statistical analysis for non-structured text data applications. Academic Press.
• Özcan & Tomasi, (2020). COVID-19’un Ekonomi ve İstihdam Üzerinde Yarattığı Etkilere Verilecek Yanıt Küresel Çapta Tam ve Etkin İş Birliğinden Geçiyor. http://www.iktisatvetoplum.com/wp-content/uploads/2020/06/ILOveUNDP.pdf
• Özer, M. (2020a). Educational policy actions by the Ministry of National Education in the times of COVID-19 pandemic in Turkey. Kastamonu Education Journal, 28(3), 1124–1129.
• Özer, M. (2020b). Vocational education and training as “a friend in need” during Coronavirus pandemic in Turkey. Bartın University Journal of Faculty of Education, 9(2), 1–7.
• Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., ... & Duchesnay, E. (2011). Scikit-learn: Machine learning in Python. the Journal of machine Learning research, 12, 2825-2830.
• Reimers, F. M. (2020). Educating students to improve the world (p. 131). Springer Nature. Reimers, F. M., & Schleicher, A. (2020). A framework to guide an education response to the COVID-19 Pandemic of 2020. OECD. Retrieved April, 14(2020), 2020-04.
• Sağlık Bakanlığı, (2020). T. C. Sağlık Bakanlığı Covid-19 Bilgilendirme Sayfası. https://covid19.saglik.gov.tr Salton, G., & Buckley, C. (1988). Term-weighting approaches in automatic text retrieval. Information processing & management, 24(5), 513-523.
• Sezgin, S., & Fırat, M. (2020). Covid-19 pandemisinde uzaktan eğitime geçiş ve dijital uçurum tehlikesi. Açıköğretim Uygulamaları ve Araştırmaları Dergisi, 6(4), 37-54.
• TEDMEM (2020a). COVID-19 Sürecinde Eğitim: Uzaktan Öğrenme, Sorunlar ve Çözüm Önerileri. https://tedmem.org/yayin/covid-19-surecinde-egitim-uzaktan-ogrenme-sorunlar-cozum-onerileri
• TEDMEM (2020b). Okulları Yeniden Açmak: Ne Zaman, Kim İçin ve Nasıl?. https://tedmem.org/download/okullari-yeniden-acmak-ne-zaman-kim-icin-nasil?wpdmdl=3342&refresh=5fffdfb23752e1610604466).
• Toquero, C. M. (2020). Challenges and Opportunities for Higher Education Amid the COVID-19 Pandemic: The Philippine Context. Pedagogical Research, 5(4), 1-5.
• Turkish Academy of Science (2020). Covid-19 Pandemi Değerlendirme Raporu. http://www.tuba.gov.tr/files/images/2020/kovidraporu/Covid-19%20Raporu-Final%2B.pdf
• UNESCO. (2020a). COVID-19 Impact on Education. https://en.unesco.org/covid19/educationresponse
• UNESCO. (2020b). School closures caused by Coronavirus (Covid-19). UNESCO. https://en.unesco.org/covid19/educationresponse UNESCO. (2020b). Startling digital divides in distance learning emerge. UNESCO. https://en.unesco.org/news/startling-digital-divides-distance-learning-emerge
• United Nations (2020). United Nations Comprehensive Response to COVID-19. https://www.un.org/sites/un2.un.org/files/un_comprehensive_response_to_covid-19_june_2020.pdf
• United Nations Development Programme [UNDP] (2020a). Covid-19 Resilience and Response. https://www.tr.undp.org/content/turkey/en/home/projects/COVID-19-response.html
• United Nations Development Programme [UNDP], (2020b). Putting the un framework for socio-economic response to Covid-19 into action: Insights. https://reliefweb.int/report/world/brief-2-putting-un-framework-socio-economic-response-covid-19-action-insights-june-2020
• Van Bavel, J. J., Baicker, K., Boggio, P. S., Capraro, V., Cichocka, A., Cikara, M., ... & Willer, R. (2020). Using social and behavioural science to support COVID-19 pandemic response. Nature Human Behaviour, 1-12.
• Vezne, R., Yildiz Durak, H., & Atman Uslu, N. (2022). Online learning in higher education: Examining the predictors of students’ online engagement. Education and Information Technologies, 1-25.
• WHO (2020a). Coronavirus disease 2019 (COVID-19) situaiton report – 96. World Health Organization. Accessed through. https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200425-sitrep-96-covid-19.pdf?sfvrsn=a33836bb_2
• WHO (2020b). Turkey’s Response to COVID-19: First Impressions. https://apps.who.int/iris/bitstream/handle/10665/335803/WHO-EURO-2020-1168-40914-55408-eng.pdf
• WHO (2021). COVID-19 Explorer. https://worldhealthorg.shinyapps.io/covid
• Wiborg, S. (2000). Political and cultural nationalism in education. The ideas of Rousseau and Herder concerning national education. Comparative Education, Nigel Grant Festschrift, 36(2), 235–243.
• Wong, A. S., & Kohler, J. C. (2020). Social capital and public health: responding to the COVID-19 pandemic. Globalization and Health, 16(1), 1-4.
• Worldbank (2020). The COVID-19 Pandemic: Shocks to Education and Policy Responses. https://www.worldbank.org/en/topic/education/publication/the-covid19-pandemic-shocks-to-education-and-policy-responses
• Yamamoto, G. T., & Altun, D. (2020). Coronavirüs ve çevrimiçi (online) eğitimin önlenemeyen yükselişi. Üniversite Araştırmaları Dergisi, 3 (1), 25-34.
• Yildiz Durak, H., Şimşir Gökalp, Z., Seki, T., Saritepeci, M., & Dilmaç, B. (2022). Examination of non-cognitive variables affecting academic achievement: a conceptual model proposal. Quality & Quantity, 1-22.