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Yüksek Öğrenimde Çevrimiçi Değerlendirmede Fakülte Üyelerinin Yaşadığı Zorluklara Yönelik Gizli Sınıf Analizi Yaklaşımı

Yıl 2024, Cilt: 26 Sayı: 2, 197 - 207, 30.06.2024
https://doi.org/10.17556/erziefd.1382191

Öz

Çevrim içi ölçme ve değerlendirme, öğretim elemanlarının öğrenmeyi yönlendirmek ve denetlemek için bilgisayar teknolojilerini kullanmasıdır. Pandemi ve doğal afetler nedeniyle eğitimde sürdürülebilirliğin sağlanması için birçok üniversite, teknolojinin getirdiği avantajlardan yararlanarak çevrim içi ölçme ve değerlendirme uygulamalarını kullanmışlardır. Betimsel türde tasarlanan bu araştırma 105 öğretim elemanı ile yürütülmüştür. Bu amaç ile geliştirilen ölçme ve değerlendirmeye yönelik zorlukları belirleyen ölçme aracı, öğretim elemanlarına uygulanmış ve sonuçlar örtük sınıf analizi ile incelenmiştir. Araştırmaya Akaike bilgi kriteri (AIC) ve Bayesyen bilgi kriteri (BIC) değerlerine göre örtük sınıf sayısının belirlenmesi ile başlanmış ve veri yapısının iki sınıflı model ile uyumlu olduğu belirlenmiştir. Sınıf sayısı belirlendikten sonra iki sınıflı yapı test edilerek maddelere ait koşullu olasılıklar hesaplanmış ve yorumlanmıştır. Araştırmanın sonuçlarına göre çevrim içi ölçme ve değerlendirme uygulamalarında oluşan sınıflardan birincisinin zorlanan gruba (%58.7) ikincisinin ise zorlanmayan guruba (% 41.3) ait olduğu tespit edilmiştir. Koşullu olasılıklar incelendiğinde, veri yapısının iki sınıflı olmasına en büyük katkıyı sağlayan gözlenen değişkenlerin: kopya çekme, intihal yapma ve eğitim politikalarının eksikliği olduğu sonucuna ulaşılmıştır. Her iki grupta (zorlanan veya zorlanmayan) da çevrim içi ölçme ve değerlendirme uygulamalarında zorlanılan konuların başında kopya çekme, intihal, eğitim politikalarının eksiklikleri olduğu bulunmuştur.

Kaynakça

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  • Amante, L., Oliveira, I. R. & Gomes, M. J. (2019). E-assessment in Portuguese higher education: Framework and perceptions of teachers and students. In A. Azevedo & J. Azevedo (Eds.), Handbook of research on e-assessment in higher education (pp. 312–333). IGI Global.
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  • Bloom, T. J., Rich, W. D., Olson, S. M. & Adams, M. L. (2018). Perceptions and performance using computer-based testing: One institution's experience. Currents in Pharmacy Teaching and Learning, 10(2), 235–242. https://doi.org/10.1016/j.cptl.2017.10.015
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A Latent Class Analysis Approach to Challenges Experienced by Faculty Members in Online Assessment in Higher Education

Yıl 2024, Cilt: 26 Sayı: 2, 197 - 207, 30.06.2024
https://doi.org/10.17556/erziefd.1382191

Öz

Online assessment is the use of computer technologies by faculty members to guide and check learning. Taking the advantage of technology, many universities have used online assessment applications to ensure sustainability in education due to the pandemic and natural disasters. The purpose of the current study is to explore challenges experienced by faculty members in online assessment, using latent class analysis. The descriptive design research was carried out with the participation of 105 faculty members. For the study, the number of latent classes was decided according to the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC) and it was observed that the data structure was a good fit for a two-class model. According to the research results, the first class in online assessment applications was considered as the with-difficulty group (58.7 %) and the second as the without-difficulty group (41.3 %). When the conditional probabilities were examined, it was concluded that the observed variables that mostly contributed to the two-class model data structure were as follows, cheating, plagiarism and lack of education policies. It was found that the primary challenges in both groups (with or without difficulty) in online assessment applications were cheating, plagiarism and lack of education policies.

Etik Beyan

This research received favourable opinion from the Hakkari University’s research ethics committee: reference: 20.12.2022-43035.

Destekleyen Kurum

Not applicable

Teşekkür

Not applicable

Kaynakça

  • Alruwais, N., Wills, G. & Wald, M. (2018). Advantages and challenges of using e-assessment. International Journal of Information and Education Technology, 8(1), 34-37. https://www.ijiet.org/vol8/1008-JR261.pdf
  • Altıntaş, Ö. & Kutlu, Ö. (2020). Investigating Measurement Invariance of Ankara University Foreign Students Selection Test According to Latent Class and Rasch Model, Education and Science, vol.45, no.203, pp.287-308, http://dx.doi.org/10.15390/EB.2020.8685
  • Amante, L., Oliveira, I. R. & Gomes, M. J. (2019). E-assessment in Portuguese higher education: Framework and perceptions of teachers and students. In A. Azevedo & J. Azevedo (Eds.), Handbook of research on e-assessment in higher education (pp. 312–333). IGI Global.
  • Bartholomew, P. M., Knott, M. & Moustaki, I. (2011). Latent variable models and factor analysis a unified approach 3rd edition. West Sussex: John Wiley& Sons, Ltd.
  • Bearman, M., Dawson, P., Ajjawi, R., Tai, J. & Boud, D. (2020). Re-imagining university assessment in a digital world. The Enabling Power of Assessment, 7. Retrieved from https://doi.org/10.1007/978-3-030-41956-1
  • Bensaid, B. & Brahimi, T. (2020). Coping with COVID-19: Higher education in the GCC countries. Springer Proceedings in Complexity, 137–153. https://doi.org/10.1007/978-3-030-62066-0_12
  • Bloom, T. J., Rich, W. D., Olson, S. M. & Adams, M. L. (2018). Perceptions and performance using computer-based testing: One institution's experience. Currents in Pharmacy Teaching and Learning, 10(2), 235–242. https://doi.org/10.1016/j.cptl.2017.10.015
  • Bozkurt, A. & Sharma, R. C. (2020). Emergency remote teaching in a time of global crisis due to CoronaVirus pandemic. Asian Journal of Distance Education, 15(1), 1-6. https://www.asianjde.com/ojs/index.php/AsianJDE/article/view/447/297
  • Bull, J. & McKenna, C. (2003). A blueprint for computer-assisted assessment. Routledge.
  • Büyüköztürk, Ş., Kılıç Çakmak, E., Akgün, Ö.E., Karadeniz, Ş. & Demirel, F. (2012). Bilimsel araştırma yöntemleri. Ankara: Pegem Yayınları
  • Cavus, N. (2015). Distance learning and learning management systems. Procedia-Social and Behavioral Sciences, 191(2), 872-877. https://doi.org/10.1016/j.sbspro.2015.04.611
  • Celeux, G. & Soromenho, G. (1996). An entropy criterion for assessing the number of clusters in a mixture model. Journal of Classification, 13(2), 195-212. https://doi.org/10.1007/BF01246098
  • Collares, C. F. & Cecilio-Fernandes, D. (2019). When I say … computerised adaptive testing. Medical Education, 53(2), 115–116. https://doi.org/10.1111/medu.13648
  • Collins, L. M. & Lanza, S. T. (2010). Latent class andlatent transition analysis with application in the social, behavioral, and health sciences. New Jersey: John Wiley and Sons, Inc.
  • Darling-Aduana, J. (2021). Authenticity, engagement, and performance in online high school courses: Insights from micro-interactional data. Computers & Education, 167, 104175. https://doi.org/10.1016/j.compedu.2021.104175
  • Demir, E. (2014). Uzaktan eğitime genel bir bakış. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi , (39) https://dergipark.org.tr/tr/download/article-file/55935
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  • McCutcheon, A. L. (1987). Latent class analysis. Sage University Papers Series.
  • Middleton, K. V. (2022). Considerations for Future Online Testing and Assessment in Colleges and Universities. Educational Measurement: Issues and Practice. Spring 2022, Vol. 41, No. 1, pp. 51–53. https://doi.org/10.1111/emip.12497
  • Mirza, H. (2021). University Teachers’ Perceptions of Online Assessment during the Covid-19 Pandemic in Lebanon, American Academic & Scholarly Research Journal, 13(1). https://aasrc.org/aasrj/index.php/aasrj/article/view/2064/1187
  • Mitchell, T., Aldridge, N., Williamson, W. & Broomhead, P. (2003). Computer based testing of medical knowledge. Presented at the 7th Computer Assisted Assessment Conference.
  • Momeni, A. (2022). Online Assessment in Times of COVID-19 Lockdown: Iranian EFL Teachers' Perceptions, International Journal of Language Testing. Vol. 12, No. 2, October 2022. https://files.eric.ed.gov/fulltext/EJ1363125.pdf
  • Montenegro-Rueda, M., Luque-de la Rosa, A., Sarasola Sánchez-Serrano, J.L. & FernándezCerero, J. (2021). Assessment in Higher Education during the COVID-19 Pandemic: A Systematic Review. Sustainability, 13, 10509. https://doi.org/10.3390/su131910509
  • Moors, G. & Wennekers, C. (2003). Comparing moral values in western european countries between 1981 and 1999. A multigroup latent-class factor approach. International Journal of Comparative Sociology, 44(1):155-172. https://doi.org/10.1177/002071520304400203
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Toplam 81 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Eğitimde Ölçme ve Değerlendirme (Diğer)
Bölüm Bu Sayıda
Yazarlar

Emrah Gül 0000-0001-8799-3356

Erken Görünüm Tarihi 26 Haziran 2024
Yayımlanma Tarihi 30 Haziran 2024
Gönderilme Tarihi 27 Ekim 2023
Kabul Tarihi 15 Mayıs 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 26 Sayı: 2

Kaynak Göster

APA Gül, E. (2024). A Latent Class Analysis Approach to Challenges Experienced by Faculty Members in Online Assessment in Higher Education. Erzincan Üniversitesi Eğitim Fakültesi Dergisi, 26(2), 197-207. https://doi.org/10.17556/erziefd.1382191