An examination of the factor structure of the Turkish version of the online learning Environment survey

Bu araştırmada, yükseköğretimde uzaktan eğitim programlarına devam eden öğrencilerin, eğitim gördükleri çevrimiçi öğrenme ortamlarına yönelik psikososyal algılarının niteliğinin belirlenmesi amaçlanmaktadır. Bu amaçla, çevrimiçi öğrenme ortamındaki psikososyal niteliği ölçen 54 maddelik Çevrimiçi Öğrenme Ortamları Ölçeği Türkçe uyarlandı. Uç modelden oluşan bu araştırmada I. Modelde Online Learning Environment Survey (OLES) (Trinidad, Aldridge & Fraser, 2004) ölçeğinin geçerlik ve güvenirlik çalışması yapılmıştır. Dokuz faktörden oluşan ölçek, uzaktan eğitim gören 902 üniversite öğrencisi üzerinde uygulanmıştır. II. Modelde, Çevrimiçi Öğrenme Ortamları Ölçeği'nden elde edilen ölçümlerin, ölçeğin özgün boyutlarına uygun olarak birinci ve ikinci sıralı doğrulayıcı faktör modellerine uyumları sınanmıştır. Bu sınamalar sonucunda, ölçümlerin model-veri uyumunu sağlamadığı görülmüştür. Bu nedenle, Türkiye örneklemindeki görgül ölçme modeline ulaşmak için temel bileşenler analizine başvurulmuştur. Bu inceleme sonucu, araştırmada kullanılan ölçümlerin yüksek uyum değerleri ile on iki faktörde toplandığı görülmüştür. III. Modelde, OLES-TR'nin on iki birinci sıralı faktörünün ikinci sıralı faktör analizi ile belirlenen genel çevrimiçi öğrenme ortamları arasındaki bağıntıları ortaya konmuştur.

Çevrimiçi öğrenme ortamları ölçeği'nin faktör yapısının incelenmesi

The primary aim of this study was to examine the reliability and validity of the Turkish version of the Online Learning Environment Survey (OLES) in postsecondary distance education. The OLES is a 54 item instrument for assessing social-psychological perceptions among distance education students. The second aim was to investigate empirically perception of the online learning environment in Turkish context. This paper consisted of three models explaining online learning environments in the Turkish context. Model I, based on relations of originally item-construct reported by Trinidad, Aldridge & Fraser, (2004), was analyzed with gathered data from Turkey setting by the translation, adaptation, and validation of the Online Learning Environment Survey (OLES) (Trinidad, Aldridge & Fraser, 2004) in a new Turkish-language form. In Model I, the OLES was designed to measure nine dimensions of online educational environment. The fit of the proposed multidimensional factor structure was examined with 902 post-secondary distance education students in two institutions. Model II, based on relations of emprically item-construct which were obtained with principal component analysis, was investigated with first-order confirmatory factor analysis. Model II consist of twelve subconstructs. Model III, with a higher-order construct with twelve first-order factors of OLES-TR, was perfectly represented as a general online learning environments trait rather than the OLES.

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Aşkar, P. (2005). Distance education in Turkey. Encyclopedia ofDistance Learning, 4, 635-639.
Bentler, P. M. (1976). Multistructural statistical models applied to factor analysis. Multivariate Behavioral Research, 11, 3-25.
Bentler, P. M., & Weeks, D. G. (1980). Linear structural equations with latent variables. Psychometrika, 452, 289-308.
Bentler, P. M., & Wu, E. J. C. (1995). EQS/Windows user's guide. Multivariate Software, Encino, CA.
Brown, R. (2001). The process of community-building in distance learning classes. Journal of Asynchronous Learning Networks, 5, (2). Retrieved from http://www.aln.org/ publications/jaln/v5n2/index.asp on May 10, 2007
Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing fit. In K. A. Bollen & J.S. Long (Eds.), Testing structural equation models. Newbury Park.
Byrne, B. M. (1998). Structural equation modeling with LISREL, PRELIS, and SIMPLIS: Basic concepts, applications and programming. Mahwah, NJ: Erlbaum.
Dorman, J., Fisher, D., & Waldrip, B. (2006). Classroom environment, students' perceptions of assessment, academic efficacy and attitude to science: A LISREL analysis. In D. L. Fisher & M. S. Khine (Eds), Contemporary approaches to research on learning environments: World views (pp. 1-28). Singapore: World Scientific.
Fraser, B. J. (1981). Tests of Science-Related Attitudes (TOSRA). Australian Council for Educational Research, Melbourne.
Fraser, B. J. (1998). Classroom environment instruments: Development, validity and applications.Learning Environments Research: An International Journal, 1(1), 68-93.
Fraser, B. J. (2002). Learning environments research: Yesterday, today and tomorrow. In S. Goh & M. S. Khine (Eds.), Studies in educational learning environments: An international perspective (pp. 1-26). River Edge, NJ: World Scientific.
Fraser, B. J., & Fisher, D. (1994). Assessing and researching the classroom environment. In D. Fisher (Ed.), The Study of Learning Environments (Vol. 8, pp. 23-39). Perth: Curtin University of Technology.
Gorsuch, R. L. (1983). Factor analysis (2 ed.). Hillsdale, N. J: Lawrence Erlbaum Associates.
Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (2005). Multivariate Data Analysis. Englewood Clifts, NJ: Prentice-Hall.
Horn, J.L. (1965). A rationale and test for the number of factors in factor analysis. Psychometrika, 30,179-185.
Hu, L., & Bentler, P. M. (1999). Cutoft criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1-55.
Jöreskog, K, & Sörbom, D. (1993). LISREL 8: User's reference guide. Chicago: Scientific Software International.
Kızılkaya, G. & Aşkar, P. (2009). The Development of a Scale on Reflective problem solving skill. Education and Science, 34 (154), 82-92.
Kim, J., & Mueller, C.W. (1978). Factor analysis: Statistical methods and practical issues. London: SAGE Publications.
Macnish, J., Trinidad, S., Fisher, D., & Aldridge, J. (2003). The online learning environment of a technology-rich secondary college. Paper Presented at the Annual Meeting of the American Educational Research Association, Chicago, IL, April.
Maor, D., & Fraser, B. J. (1996). Use of classroom environment perceptions in evaluating inquiry-based computer assisted learning. International Journal ofScience Education, 18, 401-421.
Margianti, E. S. (2003). The relationship between attitudes and achievement of university students in computer classrooms in Indonesia. In M. S. Khine & D. Fisher (Eds). Technlogy-rich learning environments: Afuture perspective (71-96). Singapore: World Scientific.
Marsh, H. W., & Hocevar, D. (1985). Anew more powerful approach to multitrait-multimethod analysis: Application of second-order confirmatory analysis. Journal of Applied Psychology, 73.107-117.
Maruyama, G. M. (1998). Basics of structural equation modeling. Thousand Oaks, CA: Sage Publications, Inc.
Moos, R. H. (1974). The Social Climate Scales: An overview. Consulting Psychologists Press, Palo Alto, CA.
Ntuli, S. (2003). Using a learning environment instrument to improve primary mathematics teaching during distance education teacher training program. Doctoral dissertation, Curtin University of Technology, Perth, Western Australia.
Nunnally, J. C. (1978). Psychometric Theory. New York: McGraw-Hill Inc.
Pearson, J. (2005, July). Evaluating e-learning environments using the Online Learning Environment Survey. 8th IFIP World Conference on Compuiters in Education (WCCE2005), Jul 4 - Jul 7, Cape Town, South Africa.
Pearson, J., & Trinidad, S. (2004). An evaluation of problem based learning (PBL) as a strategy for designing and implementing an e-learning environment. In Acquiring and Constructing Knowledge Through Human-Computer Interaction: Creating New Visions for the Future of Learning (ed. E. McKay), pp. 1101-1109. RMIT University, Melbourne.
Pearson, J., & Trinidad, S. (2005). OLES: An instrument for refining the design of e-learning environments. Journal ofComputer Assisted Learning, 21, 396-404.
Raykov, T. (1997). Estimation of composite reliability for congeneric measures. Applied Psychological Measurement, 21,173-184.
Rindskopf, D., & Rose, T. (1988). Some theory and applications of confirmatory second-order factor analysis. Multivariate Behavioral Research, 23, 51-67.
Shannon, D., Johnson, T., Searcy, S., & Lott, A. (2002). Using electronic surveys: Advice from survey professionals. Practical Assessment, Research & Evaluation, 8 (1). Retrieved May 15, 2007, from http://ericae.net/pare/getvn.asp?v=8&n=l.
Stacey, E., & Rice, M. (2002). Evaluating an online learning environment. Australian Journal of Educational Technology, 18(3), 323-340.
Steiger, J. H. (1990). Structural model evaluation and modification: an interval estimation approach. Multivariate Behavioral Research, 25 (2), 173-80.
Tabachnick, B. G., & Fidell, L. S. (2001). Using multivariate statistics (4th ed.). Needham Heights, MA: Allyn and Bacon.
Teh, G., & Fraser, B. J. (1995). Development and validation of an instrument for assessing the psychosocial environment of computer-assisted learning classrooms. Journal of Educational ComputingResearch, 12,177-193.
Teh, G., & Fraser, B. J. (1994). An evaluation of computer assisted learning in geography in Singapore. Australian Journal ofEducational Technology, 10(1), 55-68.
Thompson, B. (1990). SECONDOR: Aprogram that computes a second-order principal components analysis and various interpretation aids. Educational and Psychological Measurement, 50, 575-580.
Trinidad, S. (2005, November). Constructive solutions: Improving teaching and learning in e-learning environments. Australian Association for Research in Education (AARE) 2005, Parramatta: The University of Western Sydney.
Trinidad, S., Aldridge, J., & Fraser, B. (2004). Development and use of an online learning environment survey. Paper presented to the Annual Meeting of the American Educational Research Association AERA 2004, San Diego, CA.
Trinidad, S., Aldridge, J., & Fraser, B. (2005). Development, validation and use of the online learning environment survey. Australian Journal ofEducational Technology, 21(1), 60-81.
Trinidad, S., & Pearson, J. (2004). Implementing and evaluating e-learning environments. In Beyond the Comfort Zone: Proceedings of the 21st ASCILITE Conference, Perth, 5-8 December (eds R. Atkinson, C. McBeath, D. Jonas-Dwyer & R. Phillips), pp. 895-903. Retrieved from http://www.asciliate.org.au/conferences/perth04/procs/trinidad.htm on 30 June 2007
Walberg, H. J. (1976). Psychology of learning environments: Behavioral, structural, or perceptual?Review ofResearch in Education 4,142-178.
Walker, S. L. (2004). A distance education learning environment survey. Academic Exchange Quarterly, 8(4), 262-267.
YÖK (2003). Regulations On Inter-University Distance Higher Education Based on Communication and Information Technologies. Retrieved from http://www.yok.gov.tr/english/distance. html August 18, 2007
Yurdugül, H., & Aşkar, P. (2008). Öğrencilerin teknolojiye yönelik tutum ölçeği faktör yapılarının incelenmesi. İlköğretim Online, 7(2), 288-309.