HARMANLANMIŞ ÖĞRETİME HAZIRBULUNUŞLUK ÖLÇEĞİNİN TÜRKÇE UYARLAMA ÇALIŞMASI

Yıl 2022, , 460 - 479, 30.07.2022

Pınar Mıhcı Türker , Mücahit Öztürk

https://doi.org/10.17943/etku.1084982

Cited By: 2

Öz

Bu araştırmada harmanlanmış öğretime hazırbulunuşluk ölçeği uyarlama çalışması gerçekleştirilmiştir. Bu ölçek ile öğretmen adaylarının harmanlanmış öğretime ne düzeyde hazır oldukları belirlenmek istenmiştir. Ölçeğin uyarlanması sürecinde öncelikle dil geçerliliği yapılmıştır. Daha sonra ölçeğin yapı geçerliğinin değerlendirilmesi amacıyla açımlayıcı faktör analizi ve doğrulayıcı faktör analizinden; güvenirliğinin değerlendirilmesinde ise madde toplam korelasyon değerlerinden, alt %27-üst %27 grupların madde ortalama puanlarının karşılaştırılması için İlişkisiz T-testinden ve iç tutarlılık güvenirlik katsayısı Cronbach Alfa testinden yararlanılmıştır. Bu kapsamda 503 öğretmen adayı ile çalışma gerçekleştirilmiştir. Elde edilen bulgular doğrultusunda ölçeğin tüm değerlerinin kabul edilebilir düzeylerde olduğu ve ölçek ile öğretmen adaylarının harmanlanmış öğretime hazırbulunuşluk düzeylerinin belirlenebileceği sonucuna ulaşılmıştır.

Anahtar Kelimeler

harmanlanmış öğretim, harmanlanmış öğretime hazırbulunuşluk, ölçek uyarlama, öğretmen adayları

Destekleyen Kurum

-

Proje Numarası

-

Teşekkür

-

Kaynakça

• Aldosemani, T., Shepherd, C. E., & Bolliger, D. U. (2019). Perceptions of instructors teaching in Saudi blended learning environments. TechTrends, 63(3), 341-352.
• Alsalhi, N. R., Al-Qatawneh, S., Eltahir, M., & Aqel, K. (2021). Does Blended Learning Improve the Academic Achievement of Undergraduate Students in the Mathematics Course?: A Case Study in Higher Education. EURASIA Journal of Mathematics, Science and Technology Education, 17(4), em1951.
• Anderson, J. C., & Gerbing, D. W. (1984). The effect of sampling error on convergence, improper solutions, and goodness-of-fit indices for maximum likelihood confirmatory factor analysis. Psychometrika, 49(2), 155-173.
• Antwi-Boampong, A. (2020). Towards a faculty blended learning adoption model for higher education. Education and Information Technologies, 25(3), 1639-1662.
• Archambault, L., & Barnett, J. H. (2010). Revisiting technological pedagogical content knowledge: Exploring the TPACK framework. Computers & Education, 55(4), 1656-1662.
• Archibald, D. E., Graham, C. R., & Larsen, R. (2021). Validating a blended teaching readiness instrument for primary/secondary preservice teachers. British Journal of Educational Technology, 52(2), 536-551.
• Arnesen, K. T., Graham, C. R., Short, C. R., & Archibald, D. (2019). Experiences with personalized learning in a blended teaching course for preservice teachers. Journal of online learning research, 5(3), 275-310.
• Ates-Cobanoglu, A., & Cobanoglu, I. (2021). Do Turkish Student Teachers Feel Ready for Online Learning in Post-Covid Times? A Study of Online Learning Readiness. Turkish Online Journal of Distance Education, 22(3), 270-280.
• Büyüköztürk, Ş. (2002). Faktör analizi: Temel kavramlar ve ölçek geliştirmede kullanımı. Kuram ve uygulamada eğitim yönetimi, 32(32), 470-483.
• Büyüköztürk, Ş. (2014). Sosyal Bilimler İçin Veri Analizi El Kitabı (20. Baskı). Ankara: Pegem Akademi.
• Büyüköztürk, Ş., Akgün, Ö. E., Özkahveci, Ö. ve Demirel, F. (2004). Güdülenme ve Öğrenme Stratejileri Ölçeğinin Türkçe Formunun Geçerlik ve Güvenirlik Çalışması. Kuram ve Uygulamada Eğitim Bilimleri, 4(2), 207-239.
• Cahapay, M. B., & Anoba, J. L. D. (2020). The readiness of teachers on blended learning transition for post COVID-19 period: An assessment using parallel mixed method. PUPIL: International Journal of Teaching, Education and Learning, 4(2), 295-316.
• Cole, D. A. (1987). Utility of confirmatory factor analysis in test validation research. Journal of consulting and clinical psychology, 55(4), 584. Cunningham, D. (2021). A case study of teachers’ experiences of blended teaching and learning. Journal of Online Learning Research, 7(1), 57-83.
• Cutri, R. M., Mena, J., & Whiting, E. F. (2020). Faculty readiness for online crisis teaching: transitioning to online teaching during the COVID-19 pandemic. European Journal of Teacher Education, 43(4), 523-541.
• Çokluk, Ö., Şekercioğlu, G. ve Büyüköztürk Ş. (2012). Sosyal Bilimler İçin Çok Değişkenli İstatistik SPSS ve LISREL Uygulamaları, (2. Baskı). Ankara: Pegem Yayınları.
• Doll, W. J., Xia, W., & Torkzadeh, G. (1994). A confirmatory factor analysis of the end-user computing satisfaction instrument. MIS quarterly, 453-461.
• Graham, C. R. (2013). Emerging practice and research in blended learning. In M. G. Moore (Ed.), Handbook of distance education (3rd ed., pp. 333–350). New York, NY: Routledge.
• Graham, C. R., Borup, J., Pulham, E., & Larsen, R. (2019). K–12 blended teaching readiness: Model and instrument development. Journal of Research on Technology in Education, 51(3), 239-258.
• Graham, C. R., Borup, J., Short, C., & Archambault, L. (2019). K–12 blended teaching: A guide to personalized learning and online integration. EdTech Books. Retrieved from https://edtechbooks.org/k12blended
• Hashemi, A., & Si Na, K. (2020). The effects of using blended learning in teaching and learning English: A review of literature. The Eurasia Proceedings of Educational and Social Sciences, 18, 173-179.
• Hauk, S., St John, K., & Jones, M. (2021). Profiles of readiness: Using a blended framework to explore what it takes for faculty to be ready to change instructional practice. Journal of Geoscience Education, 69(3), 281-299.
• Howard, S. K., Tondeur, J., Siddiq, F., & Scherer, R. (2021). Ready, set, go! Profiling teachers’ readiness for online teaching in secondary education. Technology, Pedagogy and Education, 30(1), 141-158.
• Junus, K., Santoso, H. B., Putra, P. O. H., Gandhi, A., & Siswantining, T. (2021). Lecturer readiness for online classes during the pandemic: A survey research. Education sciences, 11(3), 139.
• Kalaycı, Ş. (2010). SPSS Uygulamalı Çok Değişkenli İstatistik Teknikleri (5. Baskı). Ankara: Asil Yayınevi.
• Keskin, S. & Yurdugül, H. (2019). Factors affecting students’ preferences for online and blended learning: Motivational vs. cognitive. European Journal of Open, Distance and E-Learning (EURODL), 22(2), 72-86.
• Marsh, H. W., Balla, J. R., & McDonald, R. P. (1988). Goodness-of-fit indexes in confirmatory factor analysis: The effect of sample size. Psychological bulletin, 103(3), 391.
• Martín Martínez, L., Sainz López, V., & Rodríguez Legendre, F. (2020). Evaluation of a blended learning model for pre-service teachers. Knowledge Management & E-Learning, 12(2), 147-164.
• Öztürk, M. (2021). Asynchronous online learning experiences of students in pandemic process: Facilities, challenges, suggestions. Turkish Online Journal of Qualitative Inquiry, 12(2), 173-200.
• Parks, R. A., Oliver, W., & Carson, E. (2016). The status of middle and high school instruction: Examining professional development, social desirability, and teacher readiness for blended pedagogy in the southeastern United States. Journal of Online Learning Research, 2(2), 79-101.
• Pulham, E., & Graham, C. R. (2018). Comparing K-12 online and blended teaching competencies: A literature review. Distance Education, 39(3), 411-432.
• Pulham, E., Graham, C., & Short, C. (2018). Generic vs. modality-specific competencies for K-12 online and blended teaching. Journal of Online Learning Research, 4(1), 33-52.
• Saboowala, R., & Manghirmalani Mishra, P. (2021). Readiness of in-service teachers toward a blended learning approach as a learning pedagogy in the post-COVID-19 Era. Journal of Educational Technology Systems, 50(1), 9-23.
• Scmermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003). Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fitness measures. Methods of Psychological Research Online, 8(2), 23-74.
• Seçer, İ. (2013). SPSS ve LISREL ile Pratik Veri Analizi. Ankara: Anı Yayınları.
• Smith, T. D. & McMillan, B. F. (2001, Şubat). A Primer of Model Fit Indices in Structural Equation Modeling. Annual Meeting of the Southwest Educational Research Association Symposium, USA.
• Stevens, M., Borup, J., & Barbour, M.K., (2018). Preparing social studies teachers and librarians for blended teaching, Contemporary Issues in Technology and Teacher Education 18(4), 648-669.
• Tabachnick, B. G. & Fidell, L. S. (2007). Using Multivariate Statistics (Fifth Edition). USA: Pearson Press.
• Yen, S. C., Lo, Y., Lee, A., & Enriquez, J. (2018). Learning online, offline, and in-between: comparing student academic outcomes and course satisfaction in face-to-face, online, and blended teaching modalities. Education and Information Technologies, 23(5), 2141-2153.