BibTex RIS Kaynak Göster

The Examination of the Variables Playing a Role on the Process of Adoption of Innovations by Descriptive Review Method

Yıl 2013, Cilt: 33 Sayı: 33, 53 - 71, 01.05.2013
https://doi.org/10.9779/PUJE429

Öz

The purpose of this study is to make a suggestion to researches being published in the literature about diffusion and adoption of instructional technologies. In this way, some criteria were identified by the researchers and a descriptive review was made. As a result of the descriptive review, 65 articles have been reached that meet the criteria. Articles were analyzed in terms of key words, addressed innovation, size of working and tested hypotheses. As a result of the analysis 308 tested hypothesis were found explaining the adoption and diffusion. In these hypotheses attitude, intention and usage variables were the most tested. In these hypotheses, 156 of the most frequently repeated dependent variables were related to the intention, 95 of them were related to the attitude and 57 of them were related to the usage. Intention is the most of the addressed dependent variable. It is pointed out that in the articles subjective measurements are usually made related to the usage. However, in the literature it is expressed that correlation between subjective measurement and objective measurement is weak and attitude affects usage positively but positive attitude does not mean actual usage. Also there are some uncertainties related to what the intention predict in cross-cultural studies. Starting from this point, instead of building models with attitude and intention in possible studies in which explaining diffusion, adoption and acceptance of instructional technologies as an innovation or instead of testing hypothesis predicting usage with intention and attitude; it could be proposed that there is a requirement in terms of theory and practice for conducting studies which are intended explain actual usage in educational context.

Kaynakça

  • Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
  • Alenezi, A. R., AbdulKarim, A. M., ve Veloo, A. (2010). An empirical investigation into the role of enjoyment, computer anxiety, computer self-efficacy and internet experience in influencing the students’ intention to use e-learning: Acase study from Saudi Arabian governmental univeriıties. The Turkish Online Journal of Educational Technology, 9(4), 22-34.
  • Chen, H.R., ve Huang, H.L. (2010). User acceptance of mobile knowledge management learning system: Design and analysis. Educational Technology & Society, 13 (3), 70–
  • Duan, Y., He, Q., Feng, W., Li, D., ve Fu, Z. (2010). A study on e-learning take-up intention from an innovation adoption perspective: A case in China. Computers & Education, 55, 237–246.
  • Fishbein, M. ve Ajzen I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Addison-Wesley, Reading, MA.
  • Guzzo, R.A., Jackson, S.E., ve Katzell R.A. (1987). Meta-Analysis Analysis. Research in organizational behavior, (9), 407-442.
  • Keung, J., Jeffery, R., ve Kitchenham, B. (2004). The challenge of introducing a newsoftware costestimation technology into a small software organisation, in: Proceedings of the 2004 Australian Software Engineering Conference (ASWEC’04), IEEE Computer Society Press, 52–59.
  • Kim, S. ve Garrison, G. (2009). Investigating mobile wireless technology adoption: An extension of the technology acceptance model. Information Systems Frontiers, 11, 323–333
  • King, W. R. ve He, J. (2005). Understanding the role and methods of meta-analysis in IS research. Communications of th eAssociation for Information Systems, 16, 665-6
  • Kopcha, T. J., ve Sullivan, H. J. (2007). Selfpresentation bias in surveys of teachers’ educational technology practices. Educational Technology Research and Development, 55(6), 627-646.
  • Lee, Y., Kozar, K.A. ve Larsen, K.R.T. (2003). The technology acceptance model: Past, present, and future. Communications of the Association for Information Systems, 12 (50), 752-780.
  • Ma, Q. ve Liu, L. (2004). The technology acceptance model: A meta-analysis of empirical findings. Journal of Organizational and End
  • User Computing, 16(1), 59–72. Mazman, S. G. ve Usluel, Y. K. (2010). Modeling educational usage of facebook. Computers & Education, 55(2), 444-453.
  • Rogers, E.M. (2003). Diffusion of innovations (5th edition). The Free Press. New York.
  • Schepers, J., ve Wetzels, W. (2007). A meta-analysis of the TAM-investigating subjecting norm and moderation affects. Information and management, 44(1), 90–103.
  • Straub, D.W. (1994). The effect of culture on IT diffusion E-mail and FAX in Japan and the U.S. Information Systems Research, 5(1), 23Straub, D., Limayem, M., ve Karahanna-Evaristo, E. (1995). Measuring system usage – implications for IS theory testing. Management Science, 41(8), 1328–2134.
  • Sury, D. W. (1997). Diffusion Theory and Instructional Technology. Paper presented at the Annual Conference of the Association for Educational Communications and Technology (AECT), Albuquerque, New Mexico February. İnternetten 24 Ocak 2011’de http://www2.gsu.edu/~wwwitr/ docs/diffusion/ adresinden alınmıştır.
  • Turner, M., Kitchenham, B., Brereton, P., Charters, S. ve Budgen, D. (2010). Does the technology acceptance model predict actual use? A systematic literature review. Information and Software Technology, 52, 463–479

Yeniliklerin Benimsenmesi Sürecinde Rol Oynayan Değişkenlerin Betimsel Tarama Yöntemiyle İncelenmesi

Yıl 2013, Cilt: 33 Sayı: 33, 53 - 71, 01.05.2013
https://doi.org/10.9779/PUJE429

Öz

Bu çalışmanın amacı, bir yenilik olarak öğretim teknolojisinin yayılımı ve benimsenmesi konusunda alanyazında yayınlanmış olan araştırma makalelerinden hareket ederek, gelecekte yapılması planlanan çalışmalara yönelik bir öneri getirmektir. Buradan hareketle, araştırmacılar tarafından belirlenen ölçütlere göre alanyazında betimsel tarama yapılmıştır. Yapılan betimsel tarama sonucunda, ölçütlere uyan 65 makaleye ulaşılmıştır. Makaleler anahtar sözcük, ele aldığı yenilik, çalışma grubu ve büyüklüğü ile test edilen hipotezler açısından analiz edilmiştir. Analiz sonucunda çalışmaya dahil edilen makalelerde benimseme ve yayılımı açıklamaya dönük olarak 308 tane hipotezin test edildiği bulunmuştur. Bu hipotezlerde, en sık tekrarlanan bağımlı değişkenlerin 156 tanesinin niyetle, 95 tanesinin tutumla, 57 tanesinin kullanımla ilgili olduğu belirlenmiştir. Makalelerde kullanımla ilgili olarak çoğunlukla öznel ölçümler yapıldığı dikkati çekmiştir. Oysa alanyazında, öznel ölçüm ve nesnel ölçüm arasındaki ilişkinin zayıf olduğu, tutumun kullanıma olumlu etkisinin olmasının yanında gerçek kullanımı beraberinde getirmediği ve niyetin kültürlerarası çalışmalarda neyi yordadığına ilişkin belirsizlikler olduğu ifade edilmektedir. Buradan yola çıkarak bir yenilik olarak öğretim teknolojisinin yayılımı ve benimsenmesini açıklamaya dönük yapılabilecek olası çalışmalarda, benimseme ve yayılımı niyet ve tutum üzerinden öngörmeye yönelik modelleri geliştirmek ve hipotezleri test etmek yerine, eğitsel bağlamda gerçek kullanımı açıklamaya yönelik çalışmaların yapılmasına kuram ve uygulama açısından gereksinim olduğu ileri sürülebilir.

Kaynakça

  • Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
  • Alenezi, A. R., AbdulKarim, A. M., ve Veloo, A. (2010). An empirical investigation into the role of enjoyment, computer anxiety, computer self-efficacy and internet experience in influencing the students’ intention to use e-learning: Acase study from Saudi Arabian governmental univeriıties. The Turkish Online Journal of Educational Technology, 9(4), 22-34.
  • Chen, H.R., ve Huang, H.L. (2010). User acceptance of mobile knowledge management learning system: Design and analysis. Educational Technology & Society, 13 (3), 70–
  • Duan, Y., He, Q., Feng, W., Li, D., ve Fu, Z. (2010). A study on e-learning take-up intention from an innovation adoption perspective: A case in China. Computers & Education, 55, 237–246.
  • Fishbein, M. ve Ajzen I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Addison-Wesley, Reading, MA.
  • Guzzo, R.A., Jackson, S.E., ve Katzell R.A. (1987). Meta-Analysis Analysis. Research in organizational behavior, (9), 407-442.
  • Keung, J., Jeffery, R., ve Kitchenham, B. (2004). The challenge of introducing a newsoftware costestimation technology into a small software organisation, in: Proceedings of the 2004 Australian Software Engineering Conference (ASWEC’04), IEEE Computer Society Press, 52–59.
  • Kim, S. ve Garrison, G. (2009). Investigating mobile wireless technology adoption: An extension of the technology acceptance model. Information Systems Frontiers, 11, 323–333
  • King, W. R. ve He, J. (2005). Understanding the role and methods of meta-analysis in IS research. Communications of th eAssociation for Information Systems, 16, 665-6
  • Kopcha, T. J., ve Sullivan, H. J. (2007). Selfpresentation bias in surveys of teachers’ educational technology practices. Educational Technology Research and Development, 55(6), 627-646.
  • Lee, Y., Kozar, K.A. ve Larsen, K.R.T. (2003). The technology acceptance model: Past, present, and future. Communications of the Association for Information Systems, 12 (50), 752-780.
  • Ma, Q. ve Liu, L. (2004). The technology acceptance model: A meta-analysis of empirical findings. Journal of Organizational and End
  • User Computing, 16(1), 59–72. Mazman, S. G. ve Usluel, Y. K. (2010). Modeling educational usage of facebook. Computers & Education, 55(2), 444-453.
  • Rogers, E.M. (2003). Diffusion of innovations (5th edition). The Free Press. New York.
  • Schepers, J., ve Wetzels, W. (2007). A meta-analysis of the TAM-investigating subjecting norm and moderation affects. Information and management, 44(1), 90–103.
  • Straub, D.W. (1994). The effect of culture on IT diffusion E-mail and FAX in Japan and the U.S. Information Systems Research, 5(1), 23Straub, D., Limayem, M., ve Karahanna-Evaristo, E. (1995). Measuring system usage – implications for IS theory testing. Management Science, 41(8), 1328–2134.
  • Sury, D. W. (1997). Diffusion Theory and Instructional Technology. Paper presented at the Annual Conference of the Association for Educational Communications and Technology (AECT), Albuquerque, New Mexico February. İnternetten 24 Ocak 2011’de http://www2.gsu.edu/~wwwitr/ docs/diffusion/ adresinden alınmıştır.
  • Turner, M., Kitchenham, B., Brereton, P., Charters, S. ve Budgen, D. (2010). Does the technology acceptance model predict actual use? A systematic literature review. Information and Software Technology, 52, 463–479
Toplam 18 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Makaleler
Yazarlar

Ümmühan Avcı Bu kişi benim

Yasemin Koçak Usluel Bu kişi benim

Meltem Kurtoğlu Bu kişi benim

Nilüfer Uslu Bu kişi benim

Yayımlanma Tarihi 1 Mayıs 2013
Gönderilme Tarihi 1 Ağustos 2014
Yayımlandığı Sayı Yıl 2013 Cilt: 33 Sayı: 33

Kaynak Göster

APA Avcı, Ü., Usluel, Y. K., Kurtoğlu, M., Uslu, N. (2013). Yeniliklerin Benimsenmesi Sürecinde Rol Oynayan Değişkenlerin Betimsel Tarama Yöntemiyle İncelenmesi. Pamukkale Üniversitesi Eğitim Fakültesi Dergisi, 33(33), 53-71. https://doi.org/10.9779/PUJE429