COVID-19 Pandemisi Sürecinde Uzaktan Eğitim Sistemine Yönelik Algıların Bilgi Sistemleri Başarı Modeli ile İncelenmesi

Year 2023, , 393 - 408, 15.01.2024

Özdal Koyuncuoğlu , A. Aslan Şendoğdu , Deniz Koyuncuoglu

https://doi.org/10.53478/yuksekogretim.1199841

Abstract

COVID-19 pandemisi sürecinde, eğitim etkinliklerinde kilit bir role sahip olan uzaktan eğitim teknolojilerinin değerlendirmesi ve kullanım seviyesinin incelenmesi, üniversiteler için giderek daha önemli hale gelmektedir. Bu çalışma, COVID-19 pandemisi boyunca Bilgi Sistemleri Başarı Modeli’ni kullanarak uzaktan eğitim sistemlerinin öğrenci üzerindeki etkisini incelemeyi amaçlamaktadır. Bu doğrultuda, algılanan eğitim kalitesi, teknik hizmet kalitesi, bilgi kalitesi ve COVID-19 korkusunu da içeren genişletilmiş bir Bilgi Sistemleri Başarı Modeli kullanılmıştır. Bu amaçla, Türkiye’de Necmettin Erbakan Üniversitesi’nde öğrenim gören 1011 lisans öğrencisine uzaktan eğitim sistemini kullanmayı etkileyen faktörler hakkında anket yapılmış ve elde edilen veriler Yapısal Eşitlik Modellemesi (YEM) kullanılarak analiz edilmiştir. Analizler, COVID-19 korkusunun uzaktan eğitim sistemiyle ilgili kalite algısını olumlu etkilediğini ortaya koymuştur. Teknik hizmet, eğitim ve bilgi kalitesinin uzaktan eğitimle ilişkili olarak memnuniyet ve kullanım niyeti üzerinde önemli bir etkisi olduğu bulunmuştur. Ayrıca, çalışma sonuçları, memnuniyet ve kullanım niyetinin gerçek kullanım davranışları üzerinde olumlu bir etkiye sahip olduğunu göstermiştir.

Keywords

Bilgi sistemleri başarı modeli, Covid-19 pandemisi, Türkiye, Uzaktan eğitim, Yükseköğretim

Investigation of the Perceptions Regarding Distance Education with the Information Systems Success Model in the COVID-19 Pandemic

Abstract

During the COVID-19 pandemic, the evaluation and analysis of the usage level of distance education technologies, which play a key role in education activities, has become increasingly important for universities. This study aims to investigate the impact of distance education systems on students during the COVID-19 pandemic using the Information Systems Success Model. In this context, an expanded Information Systems Success Model, including perceived education quality, technical service quality, information quality, and fear of COVID-19, was used. For this purpose, a survey was conducted on 1011 undergraduate students studying at Necmettin Erbakan University in Türkiye about factors affecting the use of the distance education system, and the data obtained were analyzed using Structural Equation Modeling (SEM). The analyses revealed that fear of COVID-19 positively influenced the quality perception associatedwith the distance education system. It was found that technical service, education, and information quality related to distance education had a significant impact on satisfaction and intention to use. Furthermore, the study results showed that satisfaction and intention to use had a positive effect on actual usage behavior.

Keywords

Covid-19 pandemic, Distance education, Higher education, Information systems success model, Türkiye

References

• Ahorsu, D. K., Lin, C. Y., Imani, V., Saffari, M., Griffiths, M. D., & Pakpour, A. H. (2020). The fear of COVID-19 scale: Development and initial validation. International Journal of Mental Health and Addiction, 20, 1537-1545. https://doi. org/10.1007/s11469-020-00270-8
• Alkhalaf, S., Drew, S., AlGhamdi, R., & Alfarraj, O. (2012). E-learning system on higher education institutions in KSA: Attitudes and perceptions of faculty members. Procedia - Social Behavioral Sciences, 47, 1199-1205.
• Alsabawy, A. Y., Cater-Steel, A., & Soar, J. (2013). IT infrastructure services as a requirement for e-learning system success. Computers & Education, 69, 431-451.
• Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411 –423. https://doi. org/10.1037/0033-2909.103.3.411
• Armstrong-Mensah, E., Ramsey-White, K., Yankey, B., & Self- Brown, S. (2020). COVID-19 and distance learning: Effects on Georgia State University School of Public Health Students. Front. Public Health, 8, 576227. https://doi.org/10.3389/ fpubh.2020.576227
• Banerjee, D. (2020). The impact of COVID-19 pandemic on elderly mental health. International Journal of Geriatric Psychiatry 35(12), 1466-1467. https://doi.org/10.1002/gps.5320
• Bharati, P. (2002). People and information matter: Task support satisfaction from the other side. The Journal of Computer Information Systems, 43(2), 93-102.
• Bhatti, N., Bouch, A., & Kuchinsky, A. (2000). Integrating user perceived quality into web server design. Computer Networks Journal, 33(1-6), 1-16.
• Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen, & J. S. Long (Eds.), Testing Structural Equation Models (pp. 136-162). Sage.
• Cheng, Y. (2012). Effects of quality antecedents on e-learning acceptance. Internet Research, 22(3), 361-390.
• Chow, M. K., Herold, D., Choo, T. M., & Chan, K. (2012). Extending the technology acceptance model to explore the intention to use second life enhancing healthcare education. Computers & Education, 59, 1136-1144.
• Cidral, W., Aparicio, M., & Oliveira, T. (2020). Students’ long-term orientation role in e-learning success: A Brazilian study. Heliyon, 6(12), article e05735. https://doi.org/10.1016/j.heliyon.2020. e05735
• Cortina, J. M. (1993). What is coefficient alpha? An examination of theory and applications. Journal of applied psychology, 78(1), 98 –104. https://doi.org/10.1037/0021-9010.78.1.98
• Davis, F. D. (1989). Perceived usefulness, perceived ease of use and user acceptance of technology. MIS Quarterly, 13(3), 319-340.
• Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003. https://doi.org/10.1287/mnsc.35.8.982
• DeLone, W. H., & McLean, E. R. (1992). Information systems success: The quest for the dependent variable. Information Systems Research, 3(1), 60–95. https://doi.org/10.1287/ isre.3.1.60
• Delone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of management information systems, 19(4), 9-30.
• Dikmen, S., & Bahçeci, F. (2020). Strategies of higher education institutions towards distance education during the COVID-19 pandemic: Fırat University sample, Turkish Journal of Educational Studies, 7(2), 78-98.
• Dishaw, M. T., & Strong, D. M. (1999). Extending the technology acceptance model with task - technology fit constructs. Information & Management, 36(1), 9–21. https://doi. org/10.1016/S0378-7206(98)00101-3
• Doğan, E., & İmamoğlu, O. (2020). Investigation of patience trends in the corona virus outbreak process of university students. Turkish Studies, 15(4), 315-324. https://dx.doi.org/10.7827/ TurkishStudies.44382
• Dominici, G., & Palumbo, F. (2013). How to build an e-learning product: Factors for student/customer satisfaction. Business Horizons, 56(1), 87-96.
• Dobeli Honegger, B., & Stajic, O. (2020). Frau avatar statt frau fessa? Der Standard. https://www.derstandard.at/ story/2000117356265/frau-avatar-statt-frau-fessa
• Efiloğlu-Kurt, Ö. (2015). Determining university students’ perspectives on distance education with the integration of technology acceptance model and information systems success model. International Journal of Alanya Business Faculty, 7(3), 224- 229.
• Efiloğlu-Kurt, Ö. (2016). An e-learning system evaluation with the information systems success model. Journal of Management Information Systems, 1(3), 140-149.
• Egunjobi, J. P. (2020). The perception of COVID-19 as a fear factor in the preparation for the pandemic aftermath. https://doi.org/10.13140/ RG.2.2.14933.17125
• Eom, S., Wen, J., & Ashil, N. (2006). An empirical investigation the determinants of students’ perceived learning outcomes and satisfaction in university online education. Decision Sciences Journal of Innovative Education, 4, 215-235.
• Freeze, R. D., Alshare, K. A., Lane, P. L., & Wen, H. J. (2010). IS Success Model in E-Learning Context Based on Students’ Perceptions. Journal of Information Systems Education, 21(2), 173- 184.
• Furrer, F., Bührer, W., Wyss, C., Degonda, A., & Hiss, J. A. (2023). Lernen mit Augmented Reality Technologie in der Hochschullehre. Erkenntnisse einer Videostudie mit angehenden Sekundarlehrpersonen. MedienPädagogik: Zeitschrift für Theorie und Praxis der Medienbildung, 51, 87-113. https://doi. org/10.21240/mpaed/51/2023.01.13.X
• Garrote, A., Neuenschwander, M. P., Hofmann, J., Mayland, C., Niederbacher, E., Prieth, V., & Rosti, I. (2021). Fernunterricht wahrend der Coronavirus-Pandemie. Analyse von Herausforderungen und Gelingensbedingungen. Fachhochschule Nordwestschweiz. https://www.fhnw.ch/de/forschung-und-dienstleistungen/ paedagogik/institut-forschung-und-entwicklung/ zentrumlernen-und-sozialisation/fernunterricht-2020-lernenwaehrendder- coronavirus-pandemie/short_fernunterricht_ garrote_etal_2021.pdf
• Godoy, L. D., Falcoski, R. M., Incrocci, R. M., Versuti, F. M., & Padovan-Neto, F. E. (2021). The psychological impact of the COVID-19 Pandemic in remote learning in higher education. Education Sciences, 11, 473. https://doi.org/10.3390/ educsci11090473
• Gonzalez, T., De La Rubia, M. A., Hincz, K. P., Comas-Lopez, M., Subirats, L., Fort, S., & Sacha, G. M. (2020). Influence of COVID-19 confinement on students’ performance in higher education. PloS One, 15(10), e0239490.
• Grynyuk, S., Kovtun, O., Sultanova, L., Zheludenko, M., Zasluzhena, A., & Zaytseva, I. (2022). Distance learning during the COVID-19 Pandemic: The experience of Ukraine’s Higher Education System. Electronic Journal of e-Learning, 20(3), 242-256. https://doi. org/10.34190/ejel.20.3.2198
• Guimaraes, T., Armstrong, C. P., & Jones, B. M. (2009). A new approach to measuring information systems quality. The Quality Management Journal, 16(1), 42-51.
• Guneş, A. (2020). Pandemic could be an opportunity for Turkish higher education. https://www.universityworldnews.com/post. php?story=20200506061559172
• Hassanzadeh, A., Kanaani, F., & Elahi, S. (2012). A model for measuring e-learning systems success in universities. Expert Systems with Applications: An International Journal, 39(12), 10959-10966.
• Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115- 135.
• Hsieh, P. A. J., & Cho, V. (2011). Comparing e-Learning tools’ success: The case of instructor–student interactive vs. self-paced tools. Computers & Education, 57(3), 2025-2038.
• Hsu, Y. (2022). Impact of emergency remote education in the 2021 COVID-19 Pandemic: A case of higher education students in the department of mechanical engineering. Higher Education Studies, 12(2), 71-83.
• Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1-55.
• Iflahen, F., & Benkhallouq, F. (2022). The impact of remote education on university students at Cadi Ayyad University in Morocco: Situation and perceptions. Environment-Behaviour Proceedings Journal. 10th AMER International Conference on Quality of Life Shangri-la Rasa Sayang, Malaysia, 16-17 Mar 2022. https://doi. org/10.21834/ebpj.v7i19.3195
• Internationale Arbeitsorganisation (2020). COVID-19 und der Bildungssektor. https://www.ilo.org/wcmsp5/groups/public/--- ed_dialogue/---sector/documents/briefingnote/wcms_749063. pdf
• Jöreskog, K. G., & Sörbom, D. (1998). LISREL 8: Structural equation modeling with the simplis command language. Scientific Software International, Inc.
• Kantipudi, P., Moses, C. J., Aluvalu, D., & Goud, G. T. (2021). Impact of COVID-19 on Indian Higher Education. Library Philosophy and Practice (e-journal), 4991. https://digitalcommons.unl.edu/ libphilprac/4991
• Keskin, M., & Özer Kaya, D. (2020). Evaluation of students’ feedback on web-based distance education during the COVID-19 process. Journal of Izmir Katip Celebi University Faculty of Health Sciences, 5(2), 59-67.
• Kim, K., Trimi, S., Park, H., & Rhee, S. (2012). The impact of CMS quality on the outcomes of e-learning systems in higher education: An empirical study. Decision Sciences Journal of Innovative Education, 10(4), 575-587.
• Koyuncuoğlu, Ö. (2020). Yükseköğretimde yeni normalleşme senaryoları ve önerileri. Turkish Studies, 15(6), 635-662. http:// dx.doi.org/10.7827/TurkishStudies.44686
• Koyuncuoğlu, D. (2021a). Pandemi sürecinde yükseköğretimde dijital teknoloji kullanımı ve uzaktan eğitim modelleri. In A. Çatalcalı- Ceylan (Ed.), Sosyal, Beşeri ve İdari Bilimlerde Yeni Arayışlar ve Çalışmalar (pp. 77-104). Serüven Publishing.
• Koyuncuoğlu, Ö. (2021b). COVID-19 Pandemi sürecinde yükseköğretim kurumlarında tükenmişlik. In A. Çatalca-Ceylan (Ed.), Sosyal, Beşeri ve İdari Bilimlerde Yeni Arayışlar ve Çalışmalar (pp. 14-42). Serüven Publishing.
• Lang, C. (2020). Pandemi-Progose. Drei Szenarien zum weiteren Verlauf. Pharmazeutische Zeitung. https://www.pharmazeutische-zeitung. de/drei-szenarien-zumweiterenverlauf-117609/
• Levy, Y. (2007). Comparing dropouts and persistence in e-learning courses. Computers and Education, 48(2), 185–204. https://doi. org/10.1016/j.compedu.2004.12.004
• Li, Y., Duan, Y., Fu, Z., & Alford, P. (2012). An empirical study on behavioural intention to reuse e-learning systems in rural China. British Journal of Educational Technology, 43(6), 933-948.
• Lin, K. (2011). E-learning continuance intention: Moderating effects of user e-learning experience. Computer & Education, 56(2), 515- 526.
• Linnes, C., Ronzoni, G., Agrusa, J., & Lema, J. (2022). Emergency remote education and its impact on higher education: A temporary or permanent shift in instruction? Education Sciences, 12(10), 721. https://doi.org/10.3390/educsci12100721
• Malhotra, N. K., & Dash, S. (2011). Marketing research: An applied orientation. Pearson
• Masalimova, A. R., Khvatova, M. A., Chikileva, L. S., Zvyagintseva, E. P., Stepanova, V. V., & Melnik, M. V. (2022). Distance learning in higher education during COVID-19. Frontiers in Education, 7, 1-6. https://doi.org/10.3389/feduc.2022.822958
• McDonald, R. P., & Marsh, H. W. (1990). Choosing a multivariate model: Noncentrality and goodness of fit. Psychological Bulletin, 107(2), 247-255.
• Mohammadi, H. (2015). Factors affecting the e-learning outcomes: An integration of TAM and IS success model. Telematics and Informatics, 32, 701-719.
• Morgan, B. (2020). Commentary: Many students in developing countries cannot access education remotely. The University of Chicago. Harris School of Public Policy. https://harris.uchicago.edu/newsevents/ news/commentary-many-students-developing-countriescannot- access-education-remotely
• Mulenga, E. M., & Marbán, J. M. (2020). Is COVID-19 the gateway for digital learning in mathematics education? Contemporary Educational Technology, 12(2), ep269. https://doi.org/10.30935/ cedtech/7949
• Neuenschwander, M. P. (2021). Chancengleichheit im Fernunterricht während Corona-Pandemie: Einschätzungen von schulischen Akteuren. Institut Forschung und Entwicklung Padagogische Hochschule der Fachhochschule Nordwestschweiz. https:// irf.fhnw.ch/bitstream/handle/11654/32488/Schlussbericht_ R2.pdf?sequence=1&isAllowed=y
• O’brien, R. M. (2007). A caution regarding rules of thumb for variance inflation factors. Quality & quantity, 41(5), 673-690.
• Ouajdouni, A., Chafik, K., & Boubker, O. (2021). Measuring e-learning systems success: Data from students of higher education institutions in Morocco. Data in Brief, 35. https://doi. org/10.1016/j.dib.2021.106807
• Petter, S., DeLone, W., & McLean, E. (2008). Measuring information systems success: Models, dimensions, measures, and interrelationships. European Journal of Information Systems, 17, 236–263.
• Petter, S., DeLone, W., & McLean, E. (2012). The past, present and future of “IS Success”. Journal of the Association for Information Systems, 13(5), 341-362.
• Petter, S., & McLean, E. R. (2009). A meta-analytic assessment of the DeLone and McLean IS success model: An examination of IS success at the individual level. Information & Management, 46(3), 159-166.
• Poulova, P., & Simonova, I. (2014). E-learning Reflected in Research Studies in Czech Republic: Comparative Analyses. Procedia - Social and Behavioral Sciences, 116, 1298-1304. https://doi. org/10.1016/j.sbspro.2014.01.386
• Ramayah, T., Ahmad N., H., & Lo, M. C. (2010). The role of quality factors in intention to continue using an e-learning system in Malaysia. Procedia-Social Behavioral Sciences, 2(2), 5422-5426.
• Republic of Türkiye Ministry of Health (2021). Ministry of Health COVID-19 Patient Table. https://covid19.saglik. gov.tr/?clid=CjwKCAiAirb_BRBNEiwALHlnD57UJ2XhwUKmAsUqRa0jbcBc4uRwZjbQMpG1q7WgsildQ_ OZVxgqBoC6p8QAvD_BwE
• Resch, K., Alnahdi, G., & Schwab, S. (2022). Exploring the effects of the COVID-19 emergency remote education on students’ social and academic integration in higher education in Austria. Higher Education Research & Development, 42(1), 215-229. https://doi.or g/10.1080/07294360.2022.2040446
• Roca, J., Chiu, C. M., & Martinez, F. J. (2006). Understanding e-learning continuance intention: An extension of the technology acceptance model. International Journal of Human – Computer Studies, 64(8), 683–696.
• Rokhman, F., Mukhibad, H., Hapsoro, B. B., & Nurkhin, A. (2022). E-learning evaluation during the COVID-19 pandemic era based on the updated of Delone and McLean information systems success model. Cogent Education, 9(1), 2093490, https:// doi.org/10.1080/2331186X.2022.2093490
• Roky, H., & Meriouh, Y. A. (2015). Evaluation by users of an industrial information system (XPPS) based on the DeLone and McLean model for IS success. Procedia Economics and Finance, 26, 903–913. https://doi.org/10.1016/s2212-5671(15)00903-x
• Saba, T. (2013). Implications of e-learning systems and selfefficiency on students’ outcomes: A model approach. Human- Centric Computing and Information Sciences, 2, 6(2012). https:// doi.org/10.1186/2192-1962-2-6
• Safsouf, Y., Mansouri, K., & Poirier, F. (2020). An analysis to understand the online learners’ success in public higher education in Morocco. Journal of Information Technology Education: Research, 19(March), 087–112. https://doi. org/10.28945/4518
• Sanchez-Franco, M. J. (2009). The moderating effects of involvement on the relationships between satisfaction, trust and commitment in e-banking. Journal of Interactive Marketing, 23(3), 247-258.
• Sennheiser (2021). World Report: Leitfaden für virtuelle Meetings und Fernunterricht nach COVID-19. Sennheiser. https://assets. sennheiser.com/global-downloads/file/17027/Sennheiser_ World_Report_eBook_German.pdf
• Shigemura, J., Ursano, R. J., Morganstein, J. C., Kurosawa, M., & Benedek, D. M. (2020). Public responses to the novel 2019 coronavirus (2019-nCoV) in Japan: Mental health consequences and target populations. Psychiatry and Clinical Neurosciences, 74(4), 281. https://doi.org/10.1111/pcn.12988
• Statista (2020). Coronavirus impact: Global in-home media consumption by country 2020. https://www.statista.com/statistics/1106498/ home-media-consumption-coronavirus-worldwide-by country/
• Stevens, J. P. (2002). Applied multivariate statistics for the social sciences. Lawrence Erlbaum.
• Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics (5th ed.). Allyn and Bacon.
• Tajuddin, R. A., Baharudin, M., & Hoon, T. S. (2013). System quality and its influence on students’ learning satisfaction in UiTM Shah Alam. Procedia-Social and Behavioral Sciences, 90, 677-685. https://doi.org/10.1016/j.sbspro.2013.07.140
• Tengler, K., Schrammel, N., & Brandhofer, G. (2020). Lernen trotz Corona. Chancen und Herausforderungen des distance learning an österreichischen Schulen. Medienimpulse, 58(02). https://journals.univie.ac.at/index.php/mp/article/view/3637 (22.08.2022).
• Terzi, B., Azizoglu, F., & Ozhan, F. (2021). Factors affecting attitudes of nursing students towards distance education during the COVID-19 pandemic: A web-based cross-sectional survey. Perspectives in Psychiatric Care, 1(9). https://doi.org/10.1111/ ppc.12747
• Telli Yamamoto, G., & Altın, D. (2020). Coronavirüs ve çevrimiçi (online) eğitimin önlenemeyen yükselişi. Üniversite Araştırmaları Dergisi, 3(1), 25-34.
• Uçkaç, K. (2020). The effects of distance education related to the COVID-19 pandemic process on student emotions and behaviors in health vocational high school students. Journal of Education in Health Sciences, 3(1), 34-44.
• UNESCO (2021). Report on blended education and educational poverty. https://unesdoc.unesco.org/ark:/48223/pf0000380190
• Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.
• Wang, H. C., & Chiu, Y. F. (2011). Assessing e-learning 2.0 system success. Computers & Education, 57(2), 1790-1800.
• Wang, Y. S., & Liao, Y. W. (2008). Assessing e-government systems success: A validation of the Delone and Mclean model of information systems success. Government Information Quarterly, 25(4), 717–733.
• Wang, Y. S., Wang, H. Y., & Shee, D. Y. (2007). Measuring e-learning systems success in an organizational context: Scale development and validation. Computers in Human Behavior, 23(4), 1792-1808.
• World of Health Organization (2020). Director-General’s remarks at the media briefing on 2019 nCoV on 11 February 2020. https://www. who.int/dg/speeches/detail/who-directorgeneral-s-remarks-atthe- media-riefing-on-2019ncov-on-11-february-2020
• Worldometers. (2020). COVID-19 Coronavirus Pandemic, Worldometer. https://www.worldometers.info/coronavirus/
• Yakubu, M. N., & Dasuki, S. I. (2018). Assessing eLearning systems success in Nigeria: An application of the Delone and McLean information systems success model. Journal of Information Technology Education: Research, 17, 183–203. https://doi. org/10.28945/4077
• Yazıcıoğlu, Y., & Erdogan, S. (2011). SPSS applied scientific research methods (3. Baskı). Detay Detail Publishing.
• YÖK (2020). Press briefing. https://www.yok.gov.tr/Sayfalar/ Haberler/2020/universitelerde-uygulanacak-uzaktanegitimeiliskin- aciklama.aspx