Adaptation Study into Turkish of the Flexibility Scale in Open and Distance Learning

Yıl 2020, , 366 - 385, 31.07.2020

Mehmet Kokoç

https://doi.org/10.17943/etku.643358

Cited By: 3

Öz

The aim of the study is to adapt the
perceived flexibility scale for Turkish open and distance learners and to
evaluate psychometric properties of the perceived flexibility scale. The original
scale which was developed by Bergamin, Ziska and Groner (2009) and revised by
Bergamin Ziska, Werlen and Siegenthaler (2012), measures students' level of
perceived flexibility in the context of open and distance learning. The study
used two
different samples of distance learners located in the Turkey. To examine
how the factorial structure of the scale patterns for Turkey sample,
exploratory factor analysis was performed using data derived from 91 open and distance
education students. The second sample of 141 open and distance students was
used for first-order and second-order confirmatory factor analysis to assess
the hierarchical structure and examine 3-factor alternative measurement models which
were yielded after exploratory factor analysis. Convergent and discriminant
validities were employed to ensure construct validity. Findings showed that a
three-factor inter-correlated model of perceived flexibility provided the best
fit for the data. The model is consistent with the factor structure of the
original scale which was developed based on data from European distance
learners. In
conclusion, the study provides a valid and reliable Turkish version of
perceived flexibility scale in open and distance learning. The Turkish version
of the perceived flexibility scale consisting of nine items and three factors
can be useful to measure perceived flexibility of learners in open and distance
learning as a validated and reliable scale.

Anahtar Kelimeler

open and distance learning, flexibility, psychometric properties

Açık ve Uzaktan Öğrenmede Esneklik Ölçeğini Türkçe’ye Uyarlama Çalışması

Öz

Bu araştırmanın amacı, “Açık ve Uzaktan Öğrenmede Esneklik”
ölçeğini Türkçe’ye uyarlamak ve ilgili ölçeğin maddeleri ile ölçek genelinin
psikometrik özelliklerini sınamaktır. Bergamin, Ziska ve Groner (2009) tarafından
geliştirilen ve Bergamin Ziska, Werlen ve Siegenthaler (2012) tarafından revize
edilen özgün ölçek, açık ve uzaktan öğrenme bağlamında öğrencilerin öğrenme
ortamına ilişkin algılanan esneklik düzeylerini ölçmeyi hedeflemektedir. Araştırmanın
iki farklı katılımcı grubu vardır. Ölçeğin faktör yapısının Türkiye örneklemi
için nasıl örüntüleneceğini incelemek için 91 açık ve uzaktan eğitim
öğrencisiyle açımlayıcı faktör analizi gerçekleştirilmiştir. Ortaya çıkan üç
faktörlü ölçme modellerini sınamak ve hiyerarşik yapıyı incelemek için 141 açık
ve uzaktan eğitim öğrencisinden veri toplanarak birinci ve ikinci düzey
doğrulayıcı faktör analizleri gerçekleştirilmiştir. Yapı geçerliği için
yakınsak geçerlik ve ayırt edici geçerlik teknikleri işe koşulmuştur. Elde
edilen bulgular, ortaya çıkan ilişkili üç faktörlü modelin geçerliğinin ve
güvenirliğinin sağlandığını kanıtlamaktadır. Bununla birlikte ilgili modelin,
Avrupa örnekleminden toplanan verilerle geliştirilen özgün ölçeğin madde-yapı
örüntüsüne benzer sonuçları işaret ettiği belirlenmiştir. Toplam dokuz madde ve
üç faktörden oluşan ölçeğin, güvenilir ve geçerli bir ölçme aracı olarak,
Türkiye’de öğrencilerin açık ve uzaktan öğrenme ortamlarına ilişkin algılanan
esneklik düzeylerini ölçmek amacıyla kullanılabileceği sonucuna ulaşılmıştır.

Anahtar Kelimeler

açık ve uzaktan öğrenme, esneklik, psikometrik özellikler

Kaynakça

• Al-Harbi, K. A. S. (2011). E-Learning in the Saudi tertiary education: Potential and challenges. Applied Computing and Informatics, 9(1), 31-46. https://doi.org/10.1016/j.aci.2010.03.002
• Arbaugh, J. B. (2000). Virtual classroom characteristics and student satisfaction with Internet-based MBA courses. Journal of Management Education, 24(1), 32-54. https://doi.org/10.1177/105256290002400104
• Arbaugh, J. B. (2018). Virtual classroom characteristics and student satisfaction with Internet-based MBA courses. Journal of Management Education, 42(4), 533-556. https://doi.org/10.1177/1052562918770400
• Bandalos, D. L., & Finney, S. J. (2010). Factor analysis: Exploratory and confirmatory.In G. R. Hancock & R. O. Mueller (Eds.),The reviewer's guide to quantitative methods in the social sciences (pp. 93-114). New York, NY: Routledge.
• Bates, A. W. (2001). National strategies for e-learning in post-secondary education and training. Paris: International Institute for Educational Planning, UNESCO. Bergamin, P., Ziska, S., & Groner, R. (2009). Structural equation modeling of factors affecting success in student’s performance in ODL-programs: Extending quality management concepts. Open Praxis, 4(1), 1-8.
• Bergamin, P. B., Ziska, S., Werlen, E., & Siegenthaler, E. (2012). The relationship between flexible and self-regulated learning in open and distance universities. The International Review of Research in Open and Distributed Learning, 13(2), 101–123.
• Brown, T. A. (2015). Confirmatory factor analysis for applied research (2nd ed.). New York, NY: Guilford Press.
• Cattell, R. B. (1978). The scientific use of factor analysis in behavioral and life sciences. New York: Plenum.
• Cornelius, S., & Gordon, C. (2008). Providing a flexible, learner-centred programme: Challenges for educators. The Internet and Higher Education, 11(1), 33-41. doi:10.1016/j.iheduc.2007.11.003
• De Boer, W., & Collis, B. (2005). Becoming more systematic about flexible learning: Beyond time and distance. Association for Learning Technology Journal, 13(1), 33–48. https://doi.org/10.1080/0968776042000339781
• Farrell, A. M. (2010). Insufficient discriminant validity: a comment on Bove, Pervan, Beatty and Shiu (2009). Journal of Business Research, 63(3), 324-327.
• Field, A. (2009). Discovering statistics using SPSS (3rd ed.). London, England: SAGE Publications.
• Flannery, M., & McGarr, O. (2014) Flexibility in higher education: An Irish perspective. Irish Educational Studies, 33(4), 419-434. https://doi.org/10.1080/03323315.2014.978658Fleiss, J. L. (1971). Measuring nominal scale agreement among many raters. Psychological Bulletin, 76, 378-382.
• Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
• Garrick, J., & Jakupec, V. (2000). Flexible learning, work and human resource development. In V. Jakupec & J. Garrick (Eds.), Flexible learning, human resource and organisational development. Putting theory to work (pp. 1-8). London: Routledge.
• Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). New Jersey: Pearson.
• Hambleton, R. K. (2005). Issues, designs, and technical guidelines for adapting tests into multiple languages and cultures. Hambleton, R.K., Merenda, P. F. ve Spielberger, C. D. (Eds.), Adapting Educational and Psychological Tests for Cross-Cultural Assessment (pp. 3-38). Mahwah, N.J.: Lawrence Erlbaum Associates, Publishers.
• Harrington, D. (2009). Confirmatory factor analysis. Oxford, New York: Oxford University Press.
• Horn, J. L. (1965). A rationale and test for the number of factors in factor analysis. Psychometrica, 30(2), 179-185.
• Jöreskog, K. G., Olsson, U. H., & Wallentin, F. Y. (2016). Multivariate analysis with LISREL. Basel, Switzerland: Springer.
• Kaiser, H. F. (1960). The application of electronic computers to factor analysis. Educational and Psychological Measurement, 20, 141-151. Retrieved from http://journals.sagepub.com/doi/pdf/10.1177/001316446002000116
• Kline, R. B. (2016). Principles and practice of structural equation modeling (4th ed.). New York: Guilford Press.
• Koçak, D., Çokluk, Ö., & Kayri, M. (2016). Faktör sayısının belirlenmesinde MAP testi, paralel analizi K1 ve yamaç birikinti grafiği yöntemlerinin karşılaştırılması. Yüzüncü Yıl Üniversitesi Eğitim Fakültesi Dergisi, 13(1), 330-359.
• Koeske, G. F. (1994). Some recommendations for improving measurement validation in social work research. Journal of Social Service Research, 18, 43-72.
• Lewis, P. A., Tutticci, N. F., Douglas, C., Gray, G., Osborne, Y., Evans, K., & Nielson, C. M. (2016). Flexible learning: Evaluation of an international distance education programme designed to build the learning and teaching capacity of nurse academics in a developing country. Nurse education in practice, 21, 59-65. doi: 10.1016/j.nepr.2016.10.001
• McGarry, B. J., Theobald, K., Lewis, P. A., & Coyer, F. (2015). Flexible learning design in curriculum delivery promotes student engagement and develops metacognitive learners: An integrated review. Nurse Education Today, 35(9), 966-973. doi: 10.1016/j.nedt.2015.06.009
• Naidu, S. (2017). How flexible is flexible learning, who is to decide and what are its implications? Distance Education, 38, 269–272. doi:10.1080/01587919.2017.1371831
• Noar, S. M. (2003). The role of structural equation modeling in scale development. Structural Equation Modeling, 10(4), 622–647.
• Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). New York: McGraw-Hill.
• Orçan, F. (2018). Exploratory and Confirmatory Factor Analysis: Which One to Use First?. Journal of Measurement and Evaluation in Education and Psychology, 9(4) , 414-421 . DOI: 10.21031/epod.394323
• Pallant, J. (2010). SPSS Survival Manual: A step by step guide to data analysis using SPSS for Windows (4th ed.). Open University Press.
• Raykov T., & Marcoulides G. A. (2011). Introduction to Psychometric Theory. New York, NY: Routledge, Taylor & Francis Group.
• Tabachnick, B. G. & Fidell, L. S. (2013). Using multivariate statistics. New Jersey: Pearson Education Inc.
• Yurdugül, H. (2005). Ölçek geliştirme çalışmalarında kapsam geçerliği için kapsam geçerlik indekslerinin kullanılması. XIV. Ulusal Eğitim Bilimleri Kongresi, Pamukkale Üniversitesi Eğitim Fakültesi, 28–30 Eylül 2005, Denizli. 27.11.2018 tarihinde http://yunus.hacettepe.edu.tr/~yurdugul/3/indir/PamukkaleBildiri.pdf adresinden indirilmiştir.
• Zwick, W. R., & Velicer, W. F. (1986). Comparison of five rules for determining the number of components to retain. Psychological Bulletin, 99(3), 432–442.