BibTex RIS Kaynak Göster

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Yıl 2013, Cilt: 28 Sayı: 28-2, 335 - 347, 01.06.2013

Öz

This study was designed to test the validity and reliability of the Web-based Learning Environment Instrument (WEBLEI). Developed by Chang and Fisher (2003), the WEBLEI is a four-factor scale that measures the access, interaction, response and results. The multidimensional construct assesses student perceptions of four core aspects of the Web-based learning environment. The psychometric properties of the Turkish form of the WEBLEI were examined using a sample of 772 post-secondary students from Turkey. A series of CFA were performed to test four models to compare differing conceptualizations of the underlying structure of the WEBLEI to examine whether the WEBLEI comprises four sub-constructs, proposed by Chang and Fisher (2003). Results indicated that the psychometric properties of correlated four-factor model were a satisfactory fit data. Present findings evidence that the WEBLEI is valid and reliable measure of Turkish students’ perceived web-based learning environments traits.

Kaynakça

  • Akbıyık, C., & Seferoğlu, S. S. (2012). İlköğretim Bilişim Teknolojileri dersinin işlenişi: Öğretmen görüş ve uygulamaları. Kuram ve Uygulamada Eğitim Bilimleri (KUYEB), 12(1), 405-424.
  • Aldridge, J. M., Dorman, J. P., & Fraser, B. J. (2004). Use of multitrait-multimethod modelling to validate actual and preferred forms of the Technology-Rich Outcomes-Focused Learning Environment Inventory (TROFLEI). Australian Journal of Educational and Developmental Psychology, 4, 110-125.
  • Behling, O., & Law, K. S. (2002). Translating Questionnaires and Other Research Instruments: Problems and Solutions, Sage, Thousand Oaks, CA.
  • Bentler, P. M. (1976). Multistructure statistical model applied to factor analysis. Multivariate Behavioral Research, 11, 3Bentler, P. M., & Weeks, D. G. (1980). Linear structural equations with latent variables. Psychometrika, 45, 289-308.
  • Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In: Bollen, K. A. & Long, J. S. (Eds.) Testing Structural Equation Models. pp. 136–162. Beverly Hills, CA: Sage.
  • Byrne, B. M. (1998). Structural equation modeling with LISREL, PRELIS, and SIMPLIS: Basic concepts, applications, and programming. Mahwah, NJ: Lawrence Erlbaum Associates.
  • Byrne, B. M., & Watkins, D. (2003). The issue of measurement invariance revisited. Journal of Cross-Cultural Psychology, 34, 155-175.
  • Çakır, M. (2011). Validity and reliability of the Turkish form of technology-rich outcome-focused learning environment inventory. Educational Sciences: Theory & Practice, 11(4), 1959-1963.
  • Carmines, E. G., & McIver, J. P. (1981). Analyzing models with unobservable variables. In G. W. Bohrnstedt and E. F. Borgatta (Ed.), Social Measurement: Current Issues, (pp. 65-115), Beverly Hills: Sage Publications.
  • Çelen, F. K., Çelik, A., & Seferoglu, S. S. (2013). Analysis of teachers 'approaches to distance education. Procedia Social and Behavioral Sciences, 83, 388-392.
  • Chandra, V. Fisher, D., & Chang, V. (2012) Investigating higher education and secondary school web-based learning environments using the WEBLEI. In Le, Thao & Le, Quynh (Eds.) Technologies for Enhancing Pedagogy, Engagement and Empowerment in Education : Creating Learning-Friendly Environments. pp. 93-105. IGI Global, Hershey, PA, Chang, V., & Fisher, D. L. (1998). The validation and application of a new learning environment instrument to evaluate online learning in higher education. [Available online at: http://www.aare.edu.au/01pap/cha01098.htm], Retrieved on September 15, 2013
  • Chang, V., & Fisher, D. L. (2003). The validation and application of a new learning environment instrument for online learning in higher education. In M. S. Khine & D. L. Fisher (Eds.), Technology-Rich Learning Environments A Future Perspective. pp. 1-20. Singapore: World Scientific Publishing Co. Pte. Ltd.
  • Fraser, B. J. (1998). Classroom environment instruments: Development, validity and applications. Learning Environments Research, 1, 7-33.
  • Fraser, B. J. (2007). Classroom learning environments. In S. K. Abelland & N. G. Lederman (Eds.), Handbook of research on science education, pp.103-124. Mahwah, NJ: Lawrence Erlbaum.
  • Fraser, B. J., & Fisher, D. L. (1982). Predicting students’ outcomes from their perceptions of classroom psychosocial environment. American Educational Research Journal, 19, 498-518.
  • Haertel, G. D., Walberg, H. J., & Haertel, E. H. (1981). Sociopsychological environments and learning: A quantitative synthesis. British Educational Research Journal, 7, 27-36.
  • Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate Data Analysis (5th edition). New Jersey, Prentice Hall.
  • Hambleton, R. (1999). Issues, designs, and technical guidelines for adapting test in multiple languages and cultures (Laboratory of Psychometric and Evaluative Research Report No. 353). Amherst: University of Massachusetts, School of Education.
  • Harlow, L. L., & Rose, J. S. (1994). Prediction models: Optimal conditions and fit assessment. Paper presented at the annual meeting of the Society for Multivariate Experimental Psychology, Princeton, NJ
  • Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1-55.
  • Jegede, O., Fraser, B. J., & Fisher, D. L. (1998). Development, validation and use of learning environment instrument for university distance education settings. Paper presented at the Annual Meeting of the American Educational Research Association, San Diego, CA.
  • Khan, B. H. (1997). Web-Based Instruction. Englewood Cliffs, NJ: Educational Technology.
  • Laurillard, D. (1993) Rethinking university teaching: A framework for the effective use of educational technology. Routledge/Falmer: London.
  • Maor, D., & Fraser, B. J. (1996). Use of classroom environment perceptions in evaluating inquiry-based computer assisted learning. International Journal of Science Education, 18, 401-421
  • Maruyama, G. M. (1998). Basics of structural equation modeling. SAGE Publications, Inc. Thousand Oaks, CA.
  • Moos, R. H. (1974). The social climate scales: An overview. Palo Alto, CA: Consulting Psychologists Press.
  • Noar, S. M. (2003). The role of structural equation modeling in scale development. Structural Equation Modeling, 10(4), 622-647.
  • Özkök, A., Büyüköztürk, Ş., & Walker, S. (2009). Reliability and validity of a Turkish Version of the DELES. Journal of Learning Environment Research, 12(3), 191-207.
  • Özkök, A., Yurdugül, H., Aşkar, P. (2011). An examination of the factor structure of the Turkish version of the online learning environment survey. Eğitim ve Bilim, 36(161), 159-175.
  • Palloff, R. M., & Pratt, K, (1998). Effective teaching and learning in the virtual classroom. In Davies, G. (Ed.) Teleteaching '98. Distance learning, training and education. Proceedings of the XV. IFIP World Computer Congress. Part II.
  • 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 of Computer Assisted Learning, 21, 396-404.
  • Reeves, T. C., & Reeves, P. M. (1997). Effective dimensions of interactive learning on the World Wide Web. In B. H. Kahn (Ed.), Web-based instruction. pp. 59-65. Englewood Cliffs: NJ, Educational Technology Publications.
  • Rubio, D. M., Berg-Weger, M., & Tebb, S. S. (2001). Using structural equation modeling to test for multidimensionality. Structural Equation Modeling, 8, 613–626.
  • Shannon, D. M., Johnson, T. E., Searcy, S., & Lott, A. (2002). Using electronic surveys: Advice from survey professionals. Practical Assessment Research & Evaluation, 8(1). [Available online at: http://PAREonline.net/getvn.asp?v=8&n=1 ], Retrieved on September 15, 2013
  • Tobin, K. (1998). Qualitative perceptions of learning environments on the World Wide Web. In B. J. Fraser and K. G. Tobin (eds.). International Handbook of Science Education. pp. 139-162. Dordrecht: Kluwer Academic Publishers.
  • Villagran, M. M., & Lucke, J. F. (2005). Translating communication measures for use in non-English speaking populations. Communication Research Reports, 22(1- 4), 247-251.
  • Walberg, H. J. (1976). Psychology of learning environments: behavioral, structural, or perceptual? In L. Shulman (Ed.), Review of research in education, Itasca, IL: Peacock. 4,142-178.
  • Walker, S. L. (2003). Development and validation of an instrument for assessing distance education learning environments in higher education: The Distance Education Learning Environments Survey (DELES). Unpublished dissertation, Curtin University of Technology, Perth, Western Australia. [Available online at: http://espace.library.curtin.edu.au/R?func=dbin-jump-full&local_base=gen01era02&object_id=14269 ],Retrieved on September 15, 2013
  • Walker, S. L., & Fraser, B. J. (2005). Development and validation of an instrument for assessing distance education learning environments in higher education: The Distance Education Learning Environments Survey (DELES). Learning Environments Research, 8(3), 289-308.
  • Wheaton, B., Muthén B., Alwin, D., & Summers, G. (1977). Assessing reliability and stability in panel models. In Sociological Methodology, ed. D. Heise, Sab Francisco: Jossey-Bass.

Reliability and Validity of the Turkish Version of the Web-Based Learning Environment Instrument (WEBLEI)

Yıl 2013, Cilt: 28 Sayı: 28-2, 335 - 347, 01.06.2013

Öz

Bu araştırmada, Web-tabanlı Öğrenme Ortamı Ölçeği’nin (Chang ve Fisher, 2003) Türkçe formunun oluşturulması ve ölçeğin Türkçe formunun Türkiye’nin sosyokültürel yapısına uygunluğu, psikometrik özellikleri açısından araştırılması amaçlanmıştır. Web-tabanlı öğrenme ortamlarının psikolojik ve sosyolojik atmosferine yönelik öğrenci algılarının ölçülmesi için Chang ve Fisher (2003) tarafından geliştirilen Web-tabanlı öğrenme ortamı ölçeği dört farklı boyutta yer alan 32 maddeden oluşmaktadır. Bu boyutlar; erişim, etkileşim, memnuniyet, içerik yönetimi. Ölçeğin Türkçe formu Türkiye’deki dört üniversitede öğrenim gören 772 öğrencisi üzerinde gerçekleştirilmiştir. Webtabanlı öğrenme ortamı ölçeğinin Türkçe formundan elde edilen ölçümlerin çözümlenmesinde doğrulayıcı faktör analizine başvurulmuş ve beş farklı model sınanmıştır. Bu modellerden elde edilen faktör çözümlemesi sonucunda 32 maddenin dört farklı alt boyuta yer aldığı ilişkili dört faktörlü modele ilişkin veri-model uyum değerleri ve bağıntılarından anlamlı sonuçlar elde edilmiştir. Bununla birlikte ölçme aracından elde edilen verilerin güvenirliği (Cronbach Alfa) ile test edilmiştir. Elde edilen sonuçlar, Web-tabanlı Öğrenme Ortamı Ölçeği’nin Türkçe formunun geçerli ve güvenilir bir ölçme aracı olduğunu göstermektedir.

Kaynakça

  • Akbıyık, C., & Seferoğlu, S. S. (2012). İlköğretim Bilişim Teknolojileri dersinin işlenişi: Öğretmen görüş ve uygulamaları. Kuram ve Uygulamada Eğitim Bilimleri (KUYEB), 12(1), 405-424.
  • Aldridge, J. M., Dorman, J. P., & Fraser, B. J. (2004). Use of multitrait-multimethod modelling to validate actual and preferred forms of the Technology-Rich Outcomes-Focused Learning Environment Inventory (TROFLEI). Australian Journal of Educational and Developmental Psychology, 4, 110-125.
  • Behling, O., & Law, K. S. (2002). Translating Questionnaires and Other Research Instruments: Problems and Solutions, Sage, Thousand Oaks, CA.
  • Bentler, P. M. (1976). Multistructure statistical model applied to factor analysis. Multivariate Behavioral Research, 11, 3Bentler, P. M., & Weeks, D. G. (1980). Linear structural equations with latent variables. Psychometrika, 45, 289-308.
  • Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In: Bollen, K. A. & Long, J. S. (Eds.) Testing Structural Equation Models. pp. 136–162. Beverly Hills, CA: Sage.
  • Byrne, B. M. (1998). Structural equation modeling with LISREL, PRELIS, and SIMPLIS: Basic concepts, applications, and programming. Mahwah, NJ: Lawrence Erlbaum Associates.
  • Byrne, B. M., & Watkins, D. (2003). The issue of measurement invariance revisited. Journal of Cross-Cultural Psychology, 34, 155-175.
  • Çakır, M. (2011). Validity and reliability of the Turkish form of technology-rich outcome-focused learning environment inventory. Educational Sciences: Theory & Practice, 11(4), 1959-1963.
  • Carmines, E. G., & McIver, J. P. (1981). Analyzing models with unobservable variables. In G. W. Bohrnstedt and E. F. Borgatta (Ed.), Social Measurement: Current Issues, (pp. 65-115), Beverly Hills: Sage Publications.
  • Çelen, F. K., Çelik, A., & Seferoglu, S. S. (2013). Analysis of teachers 'approaches to distance education. Procedia Social and Behavioral Sciences, 83, 388-392.
  • Chandra, V. Fisher, D., & Chang, V. (2012) Investigating higher education and secondary school web-based learning environments using the WEBLEI. In Le, Thao & Le, Quynh (Eds.) Technologies for Enhancing Pedagogy, Engagement and Empowerment in Education : Creating Learning-Friendly Environments. pp. 93-105. IGI Global, Hershey, PA, Chang, V., & Fisher, D. L. (1998). The validation and application of a new learning environment instrument to evaluate online learning in higher education. [Available online at: http://www.aare.edu.au/01pap/cha01098.htm], Retrieved on September 15, 2013
  • Chang, V., & Fisher, D. L. (2003). The validation and application of a new learning environment instrument for online learning in higher education. In M. S. Khine & D. L. Fisher (Eds.), Technology-Rich Learning Environments A Future Perspective. pp. 1-20. Singapore: World Scientific Publishing Co. Pte. Ltd.
  • Fraser, B. J. (1998). Classroom environment instruments: Development, validity and applications. Learning Environments Research, 1, 7-33.
  • Fraser, B. J. (2007). Classroom learning environments. In S. K. Abelland & N. G. Lederman (Eds.), Handbook of research on science education, pp.103-124. Mahwah, NJ: Lawrence Erlbaum.
  • Fraser, B. J., & Fisher, D. L. (1982). Predicting students’ outcomes from their perceptions of classroom psychosocial environment. American Educational Research Journal, 19, 498-518.
  • Haertel, G. D., Walberg, H. J., & Haertel, E. H. (1981). Sociopsychological environments and learning: A quantitative synthesis. British Educational Research Journal, 7, 27-36.
  • Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate Data Analysis (5th edition). New Jersey, Prentice Hall.
  • Hambleton, R. (1999). Issues, designs, and technical guidelines for adapting test in multiple languages and cultures (Laboratory of Psychometric and Evaluative Research Report No. 353). Amherst: University of Massachusetts, School of Education.
  • Harlow, L. L., & Rose, J. S. (1994). Prediction models: Optimal conditions and fit assessment. Paper presented at the annual meeting of the Society for Multivariate Experimental Psychology, Princeton, NJ
  • Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1-55.
  • Jegede, O., Fraser, B. J., & Fisher, D. L. (1998). Development, validation and use of learning environment instrument for university distance education settings. Paper presented at the Annual Meeting of the American Educational Research Association, San Diego, CA.
  • Khan, B. H. (1997). Web-Based Instruction. Englewood Cliffs, NJ: Educational Technology.
  • Laurillard, D. (1993) Rethinking university teaching: A framework for the effective use of educational technology. Routledge/Falmer: London.
  • Maor, D., & Fraser, B. J. (1996). Use of classroom environment perceptions in evaluating inquiry-based computer assisted learning. International Journal of Science Education, 18, 401-421
  • Maruyama, G. M. (1998). Basics of structural equation modeling. SAGE Publications, Inc. Thousand Oaks, CA.
  • Moos, R. H. (1974). The social climate scales: An overview. Palo Alto, CA: Consulting Psychologists Press.
  • Noar, S. M. (2003). The role of structural equation modeling in scale development. Structural Equation Modeling, 10(4), 622-647.
  • Özkök, A., Büyüköztürk, Ş., & Walker, S. (2009). Reliability and validity of a Turkish Version of the DELES. Journal of Learning Environment Research, 12(3), 191-207.
  • Özkök, A., Yurdugül, H., Aşkar, P. (2011). An examination of the factor structure of the Turkish version of the online learning environment survey. Eğitim ve Bilim, 36(161), 159-175.
  • Palloff, R. M., & Pratt, K, (1998). Effective teaching and learning in the virtual classroom. In Davies, G. (Ed.) Teleteaching '98. Distance learning, training and education. Proceedings of the XV. IFIP World Computer Congress. Part II.
  • 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 of Computer Assisted Learning, 21, 396-404.
  • Reeves, T. C., & Reeves, P. M. (1997). Effective dimensions of interactive learning on the World Wide Web. In B. H. Kahn (Ed.), Web-based instruction. pp. 59-65. Englewood Cliffs: NJ, Educational Technology Publications.
  • Rubio, D. M., Berg-Weger, M., & Tebb, S. S. (2001). Using structural equation modeling to test for multidimensionality. Structural Equation Modeling, 8, 613–626.
  • Shannon, D. M., Johnson, T. E., Searcy, S., & Lott, A. (2002). Using electronic surveys: Advice from survey professionals. Practical Assessment Research & Evaluation, 8(1). [Available online at: http://PAREonline.net/getvn.asp?v=8&n=1 ], Retrieved on September 15, 2013
  • Tobin, K. (1998). Qualitative perceptions of learning environments on the World Wide Web. In B. J. Fraser and K. G. Tobin (eds.). International Handbook of Science Education. pp. 139-162. Dordrecht: Kluwer Academic Publishers.
  • Villagran, M. M., & Lucke, J. F. (2005). Translating communication measures for use in non-English speaking populations. Communication Research Reports, 22(1- 4), 247-251.
  • Walberg, H. J. (1976). Psychology of learning environments: behavioral, structural, or perceptual? In L. Shulman (Ed.), Review of research in education, Itasca, IL: Peacock. 4,142-178.
  • Walker, S. L. (2003). Development and validation of an instrument for assessing distance education learning environments in higher education: The Distance Education Learning Environments Survey (DELES). Unpublished dissertation, Curtin University of Technology, Perth, Western Australia. [Available online at: http://espace.library.curtin.edu.au/R?func=dbin-jump-full&local_base=gen01era02&object_id=14269 ],Retrieved on September 15, 2013
  • Walker, S. L., & Fraser, B. J. (2005). Development and validation of an instrument for assessing distance education learning environments in higher education: The Distance Education Learning Environments Survey (DELES). Learning Environments Research, 8(3), 289-308.
  • Wheaton, B., Muthén B., Alwin, D., & Summers, G. (1977). Assessing reliability and stability in panel models. In Sociological Methodology, ed. D. Heise, Sab Francisco: Jossey-Bass.
Toplam 41 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Makaleler
Yazarlar

Alev Özkök Bu kişi benim

Yayımlanma Tarihi 1 Haziran 2013
Yayımlandığı Sayı Yıl 2013 Cilt: 28 Sayı: 28-2

Kaynak Göster

APA Özkök, A. (2013). Reliability and Validity of the Turkish Version of the Web-Based Learning Environment Instrument (WEBLEI). Hacettepe Üniversitesi Eğitim Fakültesi Dergisi, 28(28-2), 335-347.