G. Alev ÖZKÖK, M. Emin AKPOLAT

2417

Üniversite Öğrencilerinin Öğrenme Nesneleri Kullanımlarının Öğrenme Nesnesi Kabul Modeline Göre İncelenmesi

Bu çalışmanın amacı, üniversite öğrencilerinin çevrimiçi öğrenme ortamlarının öğretim materyalleri olan öğrenme nesnelerini kullanma eğilimlerine etki eden değişkenleri tespit etmek ve bu değişkenler arasındaki nedensel ilişkileri incelemektir. Çalışma grubu 427 üniversite birinci sınıf öğrencisinden oluşmaktadır. Bu çalışmada, Lau ve Woods (2008a) tarafından geliştirilen Teknoloji Kabul Modelinin (Davis, 1989) genişletilmiş versiyonu olan Öğrenme Nesnesi Kabul Modeli-ÖNKM (Learning Object Acceptance Model - LOAM) Türkçe'ye uyarlanarak araştırmada kullanılmıştır. Araştırma kapsamında Türkçe’ye uyarlanan ölçeğe ilişkin bulgular incelendiğinde, Öğrenme Nesnesi Kabul Ölçeği’nin (ÖNKÖ), 35 madde ve 7 faktörden oluştuğu bulunmuştur. ÖNKÖ; “pedagojik kalite”, “teknik kalite” ve “içerik kalitesi” harici değişkenleri ile “yarar algısı”, “kullanım kolaylığı algısı”, “davranışsal niyet” ve “gerçek kullanım” asıl değişkenlerinden oluşmuştur. Ölçeğin genel Cronbach Alfa güvenirlik katsayısı 0,93 olarak elde edilmiştir. Araştırma modeli LISREL 8.0 kullanılarak oluşturulan yapısal eşitlik modeli (YEM) ile sınanmıştır. Araştırmanın bulguları, yarar algısının doğrudan ve kullanım kolaylığı algısının dolaylı olarak öğrenme nesnelerinin kullanım niyetinin belirleyicileri olduğunu göstermektedir. Kullanım kolaylığı algısının, öğrenme nesneleri kullanımı için doğrudan niyet üzerinde bir etkisi olmadığı görülmektedir.

Examining University Students Acceptance of Learning Objects according to Learning Object Acceptance Model

The aim of this study is to identify variables that affect the students' tendency to use learning objects, which are teaching materials in their online learning environments, and to examine the causal relationships between these variables. The study group consisted of 427 university freshman. The Learning Object Acceptance Model (LOAM), an extended version of the Technology Acceptance Model (Davis, 1989) developed by Lau and Woods (2008a), has been adapted to Turkish and used in the study. When the findings related to the scale adapted to Turkish within the scope of the study were examined, it was found that Learning Object Acceptance Model (LOAM) was composed of 35 items with 7 factors. LOAM consists of; “pedagogical quality”, “technical quality”, “content quality”; external factors and “perceived usefulness”, “perceived ease of use”, “behavioral intention", “actual use”, main factors. The general Cronbach Alpha reliability coefficient of the scale was 0.93. The research model was tested with the Structural Equation Model (SEM) developed using LISREL 8.0. As a result of the research, the findings show that the perceived usefulness is a direct determinant and perceived ease of use is an indirect determinant of intention to use learning objects. The perceived ease of use does not seem to have an immediate influence on the direct intention to use learning objects.
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  • Agarwal, R., & Karahanna, E. (2000). Time flies when you're having fun: Cognitive absorption and beliefs about information technology usage. MIS Quarterly, 24(4), 665-694. doi:10.2307/3250951
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  • Corwin, T. A. (1998). Prediction of and differences in computer use: universal adoption of notebook computers at three undergraduate institutions (unpublished doctoral dissertation). Lowa State University, IA.
  • Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297-334.
  • Dağhan, G., & Akkoyunlu, B. (2016). Modeling the continuance usage intention of online learning environments. Computers in Human Behavior, 60, 198-211. doi: 10.1016/j.chb.2016.02.066
  • Dasgupta, S. Granger, M., & McGarry, N. (2002). User acceptance of e-collaboration technology: An extension of the technology acceptance model. Group Decision and Negotiation, 11, 87-100.
  • Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results (Unpublished doctoral dissertation). Sloan School of Management, MIT, Cambridge, MA. 6 Haziran 2018 tarihinde https://www.kisa.link/Lag2 adresinden erişildi.
  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
  • Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management Science, 35(8), 982-1003.
  • Fishbein, M. & Ajzen, I. (1975). Belief, attitude, intention and behaviour: an introduction to theory and research. Addison-Wesley, Reading, MA.
  • Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18, 39-50.
  • Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27, 51- 90.
  • Güvenir, C., & Bağlı, H. H. (2019). The potentials of learning object design in design thinking learning. Markets, Globalization & Development Review, 4(2), 1-34. doi: 10.23860/MGDR-2019-04-02-03
  • Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data analysis (7th ed.). Pearson Education.
  • Hambleton, R. K. (2005). Issues, designs and technical guidelines for adapting tests into multiple languages and cultures. In R. K. Hambleton, P. F. Merenda, & C. D. Spielberger (Eds.). Adapting Psychological and Educational Tests for Cross-Cultural Assessment. NJ: Lawrence Erlbaum.
  • Hambleton, R. K., & Patsula, L. (1999). Increasing the validity of adapted tests: Myths to be avoided and guidelines for improving test adaptation practices. Journal of Applied Testing Technology, 1(1), 1-30.
  • Horton, R. P., Buck, T., Waterson, P. E., & Clegg, C. W. (2001). Explaining intranet use with the technology acceptance model. Journal of Information Technology, 16(4), 237-249.
  • 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), 1-55.
  • Igbaria, M., Guimaraes, T., & Davis, G. B. (1995). Testing the determinants of microcomputer usage via a structural equation model. Journal of Management Information Systems, 11(4), 87-114.
  • Jackson, C. M., Chow, S., & Leitch, R. A. (1997). Towards an understanding of the behavioral intention to use an information system. Decision Sciences, 28(2), 357-389.
  • Jan, A., & Contreras, V. (2011) Technology acceptance model for the use of information technology in universities. Computers in Human Behavior, 27(2), 845-851. doi: 10.1016/j.chb.2010.11.009
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  • Ong, C.-S., Lai, J.-Y., & Wang, Y.-S. (2004). Factors affecting engineers' acceptance of asynchronous e-learning systems in high- tech companies. Information & Management, 41(6), 795-804.
  • Özer, G., & Yılmaz, E. (2010). Mantıklı Eylem Teorisi (MET) ile muhasebecilerin bilgi teknolojisi kullanımına yönelik bir uygulama. İktisat, İşletme ve Finans, 25, 65-88.
  • Özer, G., Özcan, M., & Aktaş, S. (2010). Muhasebecilerin bilgi teknolojisi kullanımının teknoloji kabul modeli ile incelenmesi. Journal of Yaşar University, 5(19), 3278-3293.
  • Özkök, G. A. (2015). Yaratıcı problem çözme metodu ile öğrenme nesnesi tasarımı ve geliştirilmesi. B. Akkoyunlu, A. İşman, & H. F. Odabaşı (Ed). Eğitim Teknolojileri Okumaları içinde (ss. 421-444). TOJET - Sakarya Üniversitesi.
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  • Saade, R., & Bahli, B. (2005). The impact of cognitive absorption on perceived usefulness and perceived ease of use in on-line learning: An extension of the technology acceptance model. Information & Management, 42(2), 317-327.
  • Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003). Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of Psychological Research Online, 8(2), 23-74.
  • Seddon, P. B. (1997). A respecification and extension of the Delone and Mclean model of IS success. Information Systems Research, 8, 3, 240-250.
  • Selim, H. M. (2003). An empirical investigation of student acceptance of course websites. Computers & Education, 40(4), 343- 360.
  • Singh, H. (2000). Achieving interoperability in e-learning. American Society for Training and Development (ASTD).
  • Surry, D. W., & Ely, D. P. (2002). Adoption, diffusion, implementation, and institutionalization of instructional design and technology. In R. A. Reiser & J. V. Dempsey (Eds.), Trends and issues in instructional design and technology (183-193. ss.). Upper Saddle River, NJ: Merrill Prentice Hall.
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  • Tetiwat, O., & Huff, S. (2002). Determinants of the adoption of Web-based educational technology: A preliminary data analysis of New Zealand tertiary education. Paper presented at the Proceedings of the International Conference on Computers in Education, Auckland, New Zealand.
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  • Thong, J. Y. L., Hong W. H., & Tam, K. R. (2002). Understanding user acceptance of digital libraries: What are the roles of interface characteristics, organizational context and individual differences?. International Journal of Human Computer Studies, 57, 215- 242.
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  • Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: development and test. Decision Sciences, 27(3), 451-481.
  • Ong, C.-S., Lai, J.-Y., & Wang, Y.-S. (2004). Factors affecting engineers' acceptance of asynchronous e-learning systems in high- tech companies. Information & Management, 41(6), 795-804.
  • Özer, G., & Yılmaz, E. (2010). Mantıklı Eylem Teorisi (MET) ile muhasebecilerin bilgi teknolojisi kullanımına yönelik bir uygulama. İktisat, İşletme ve Finans, 25, 65-88.
  • Özer, G., Özcan, M., & Aktaş, S. (2010). Muhasebecilerin bilgi teknolojisi kullanımının teknoloji kabul modeli ile incelenmesi. Journal of Yaşar University, 5(19), 3278-3293.
  • Özkök, G. A. (2015). Yaratıcı problem çözme metodu ile öğrenme nesnesi tasarımı ve geliştirilmesi. B. Akkoyunlu, A. İşman, & H. F. Odabaşı (Ed). Eğitim Teknolojileri Okumaları içinde (ss. 421-444). TOJET - Sakarya Üniversitesi.
  • Polsani, P. R. (2003). Use and abuse of reusable learning objects. Journal of Digital Information, 3(4). https://journals.tdl.org/jodi/index.php/jodi/article/view/89/88
  • Raymond, L. (1988). The impact of computer training on the attitudes and usage behavior of small business managers. Journal of Small Business Management, 26(3), 8-13.
  • Rogers, E. M. (1995). Diffusion of innovations (4th ed.). New York: The Free Press.
  • Saade, R., & Bahli, B. (2005). The impact of cognitive absorption on perceived usefulness and perceived ease of use in on-line learning: An extension of the technology acceptance model. Information & Management, 42(2), 317-327.
  • Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003). Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of Psychological Research Online, 8(2), 23-74.
  • Seddon, P. B. (1997). A respecification and extension of the Delone and Mclean model of IS success. Information Systems Research, 8, 3, 240-250.
  • Selim, H. M. (2003). An empirical investigation of student acceptance of course websites. Computers & Education, 40(4), 343- 360.
  • Singh, H. (2000). Achieving interoperability in e-learning. American Society for Training and Development (ASTD).
  • Surry, D. W., & Ely, D. P. (2002). Adoption, diffusion, implementation, and institutionalization of instructional design and technology. In R. A. Reiser & J. V. Dempsey (Eds.), Trends and issues in instructional design and technology (183-193. ss.). Upper Saddle River, NJ: Merrill Prentice Hall.
  • Szajna, B. (1996). Empirical evaluation of the revised technology acceptance model. Management Science, 42(1), 85-92.
  • Şimşek, Ö. F. (2007). Yapısal eşitlik modellemesine giriş: Temel ilkeler ve Lisrel uygulamaları. Ankara: Ekinoks Yayıncılık.
  • Tabachnick, B. G., & Fidell L. S. (2015) Çok değişkenli istatistiklerin kullanımı. (6. Basımdan çeviri) Çeviri Editörü: M. Baloğlu. Ankara: Nobel Akademik Yayıncılık.
  • Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: a test of competing models. Information Systems Research, 6, 144-176.
  • Tetiwat, O., & Huff, S. (2002). Determinants of the adoption of Web-based educational technology: A preliminary data analysis of New Zealand tertiary education. Paper presented at the Proceedings of the International Conference on Computers in Education, Auckland, New Zealand.
  • Tezbaşaran, A. A. (1997). Likert tipi ölçek geliştirme kılavuzu. Ankara: Türk Psikologlar Derneği.
  • Thong, J. Y. L., Hong W. H., & Tam, K. R. (2002). Understanding user acceptance of digital libraries: What are the roles of interface characteristics, organizational context and individual differences?. International Journal of Human Computer Studies, 57, 215- 242.
  • Urden, T. A., & Weggen, C. C. (2000). Corporate e-learning: exploring a new frontier. WR Hambrecht and Company Equity Research Report, San Francisco. 6 Haziran 2018 tarihinde https://www.kisa.link/LafY adresinden erişildi.
  • Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: development and test. Decision Sciences, 27(3), 451-481.
Hacettepe Üniversitesi Eğitim Fakültesi Dergisi-Cover
  • Başlangıç: 1986
  • Yayıncı: Hacettepe Üniversitesi Eğitim Fakültesi Dekanlığı
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