UNIVERSITY STUDENTS' APPROACH TO DISTANCE EDUCATION: SCALE DEVELOPMENT AND VALIDATION

Yıl 2022, , 192 - 204, 08.10.2022

Şebnem Zorlutuna , Necati Alp Erilli

https://doi.org/10.11611/yead.1102926

Öz

This study aims to develop a valid and reliable measurement tool that can be used to determine university students' approaches to distance education during the Covid-19 pandemic process. For this purpose, a questionnaire study was applied to 1636 students studying at Sivas Cumhuriyet University. Explanatory factor analysis was applied to 1285 of the students and confirmatory factor analysis was applied to 351 of them. According to the results of the analysis, a 17-item, 3-factor structure with factor loading values between 0.653 and 0.842 was determined. The reliability coefficient of the scale was found as 0.941 and the subscales were also found 0.927, 0.864, 0.839 respectively. According to the Confirmatory Factor Analysis results, all fit indices were found to have valid values. As a result, it has been determined that the proposed Distance Education scale is a valid and reliable scale to determine the approaches of university students to distance education.

Anahtar Kelimeler

Covid-19, Distance Education, Scale Development, CFA

Kaynakça

• Alkan, I., (2020). Kovid-19 Pandemi Döneminde Türkiye’de Uzaktan Eğitimle İlgili Olarak Yapılan Bilimsel Çalışmaların İncelenmesi, 3. Uluslararası Uzaktan Öğrenme ve Yenilikçi Eğitim Teknolojileri Konferansı Bildiri Kitabı, 153-159 (In Turkish).
• Alomyan, H. (2021). The impact of distance learning on the psychology and learning of university students during the covid-19 pandemic. International Journal of Instruction, 14(4), 585-606.
• Bakhov, I., Opolska, N., Bogus, M., Anishchenko, V., & Biryukova, Y. (2021). Emergency Distance Education in the Conditions of COVID-19 Pandemic: Experience of Ukrainian Universities. Education Sciences, 11(7), 364.
• Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88, 588–606.
• Browne, M. W., & R. Cudeck (1993). Testing Structural Equation Models. In Alternative Ways of Assessing Model fit, ed. K. A. Bollen, and J. S. Long. Newbury Park, CA: Sage.
• Chung, E., Subramaniam, G., & Dass, L. C. (2020). Online learning readiness among university students in Malaysia amidst COVID-19. Asian Journal of University Education, 16(2), 46-58.
• Di Martino, V., & Strongoli, R. C. (2021). Distance Education and Learning Processes. A Survey at University of Catania Durıng The Covid-19 Pandemic. Education and New Developments 2021, 236-240. https://doi.org/10.36315/2021end051
• Giusti, L., Mammarella, S., Salza, A., Del Vecchio, S., Ussorio, D., Casacchia, M., & Roncone, R. (2021). Predictors of academic performance during the covid-19 outbreak: impact of distance education on mental health, social cognition and memory abilities in an Italian university student sample. BMC psychology, 9(1), 1-17.
• Hamdan, K. M., Al-Bashaireh, A. M., Zahran, Z., Al-Daghestani, A., Samira, A. H., & Shaheen, A. M. (2021). University students' interaction, Internet self-efficacy, self-regulation and satisfaction with online education during pandemic crises of COVID-19 (SARS-CoV-2). International Journal of Educational Management, 35, 713-725.
• Händel, M., Stephan, M., Gläser-Zikuda, M., Kopp, B., Bedenlier, S., & Ziegler, A. (2020). Digital readiness and its effects on higher education students’ socio-emotional perceptions in the context of the COVID-19 pandemic. Journal of Research on Technology in Education, 1-13. https://doi.org/10.1080/15391523.2020.1846147.
• Ismaili, Y. (2021). Evaluation of students’ attitude toward distance learning during the pandemic (Covid-19): a case study of ELTE university. In On the Horizon; Emerald Publishing Limited: Bingley, UK, 2020; Volume 29, 17–30
• Kline, R. B. (2014). “Principles and Practice of Structural Equation Modeling” In Principles and Practice of Structural Equation Modeling. 2nd ed., The Guilford Press, NY, USA.
• Newby, T. J., Stepich, D. A., Lehman, J. D., & Russell, J. D. (2000). Instructional technology for teaching and learning. New Jersey: Prentice Hall.
• Roblyer, M. D., & Edwards, J. (2000). Integrating educational technology into teaching: Transforming Learning Across Disciplines (2nd ed.). Pearson Education, NY, USA.
• Rotas, E. E., & Cahapay, M. B. (2020). Difficulties in Remote Learning: Voices of Philippine University Students in the Wake of COVID-19 Crisis. Asian Journal of Distance Education, 15(2), 147-158.
• Sherry, L. (1996). Issues in Distance Learning. International Journal of Educational Telecommunications, 1(4), 337-365.
• Sun, L., Tang, Y., & Zuo, W. (2020). Coronavirus pushes education online. Nature Materials, 19(6), 687-687.
• Tuncer, M., & Taşpınar, M. (2008). Sanal Ortamda Eğitim ve Öğretimin Geleceği ve Olası Sorunlar, Sosyal Bilimler Dergisi, 10 (1),125-144 (In Turkish).
• UNESCO (2020). COVID-19 Impact on Education. https://en.unesco.org/covid19/educationresponse, (Date of Access: 15.10.2021).
• Uşun, S. (2006). Uzaktan Eğitim, (1.Basım), Nobel Yayın Dağıtım, Ankara (In Turkish).
• WHO: World Health Organization (2021). https://covid19.who.int/table (Date of Access: 01.10.2021)
• YÖK: Yükseköğretim Kurulu (Turkish Council of Higher Education) (2020). https://www.yok.gov.tr/HaberBelgeleri/BasinDuyurusu/2020/yok-dersleri-platformu erisimeacildi.pdf, (Date of Access:12.10.2021).