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Web Tabanlı Uzaktan Eğitim Sistemini Kullanmaya Devam Etme Niyetini Etkileyen Faktörlerin Yapısal Eşitlik Modeli ile İncelenmesi

Yıl 2018, Cilt: 18 Sayı: 78, 43 - 66, 20.11.2018

Öz

Problem
Durumu:
Bu çalışmada, Yüzüncü Yıl Üniversitesi web tabanlı uzaktan eğitim sistemi
ile formasyon eğitimi alan öğrenciler örneğinde bu sistemi kullanmaya devam
etme niyetini etkileyen faktörler yapısal eşitlik modellemesi ile
incelenmiştir.

Araştırmanın
Amacı:
Çalışmada yer alacak yapılar detaylı bir literatür taraması sonucunda
belirlenmiş ve birçok bileşeni bir arada bulunduran web tabanlı uzaktan eğitim
sistemlerinin karmaşık yapısı çözümlenmeye çalışılmıştır. Kullanılacak modelin
belirlenmesinde Teknoloji Kabul Modeli (TAM, Technology Acceptance Model) ve
Onaylanmayan Beklentiler Kuramı’ ndan (EDT, Expectancy Disconfirmation Theory)
faydalanılmış ve geniş kapsamlı bir araştırma yapılmıştır. Sonuç olarak bir web
tabanlı uzaktan eğitim sistemini kullanmaya devam etme niyetinin algılanan
kalite, algılanan kontrol, algılanan kullanılabilirlik yapılarından dolaylı
olarak ve memnuniyet yapısından direk etkilendiği belirlenmiştir.

Araştırmanın Yöntemi:
Araştırmanın iki aşaması mevcuttur. İlk aşamada konuyla ilgili literatür
taraması yapılarak izlenecek yol ve kavramsal çerçeve belirlenmiş ikinci
aşamada araştırma modelinin hipotezleri belirlenip veriler toplanmıştır.
Verilerin toplanmasında ölçme aracı uygulanması yöntemi kullanılmıştır. Ölçme
aracı formu geçerliliği ispatlanmış birçok ölçeğin birleşiminden oluşmaktadır.
Ölçme aracında yer alan maddelerin Türkçe ’ye adaptasyonunda eğitim bilimleri
alanında uzman kişilerden görüşler alınmış ve ayrıca gerektiği noktada çeviri
konusunda da destek alınmıştır. Her bir alt ölçeğin güvenilirliği Cronbach’s
Alfa katsayıları incelenerek test edilmiş daha sonra yapısal eşitlik modeli
(SEM) yardımıyla, ileri sürülen teorik modele bağlı nedensel ilişkilerin
analizi yapılmıştır. Ölçeklerin güvenilirliğinin ve ölçüm araçlarının içsel
tutarlılığının test edilmesinde en çok kullanılan yöntemlerden biri olan
Cronbach’s α katsayısından yararlanılmıştır. Algılanan kalite yapısının
güvenilirliği Cronbach’s α katsayısı hesaplanarak belirlenmiştir. Algılanan
kalite yapısı için 0.888, Algılanan kullanılabilirlik 0,839, Algılanan kontrol
0,880 olarak hesaplanmıştır. Bu değerler her bir yapının yüksek derecede
güvenilir olduğunu göstermektedir.

Araştırmanın Bulguları:
Path katsayıları anlamlı bulunmuştur ve hipotezler doğrulanmıştır. Bir
e-öğrenme sisteminde algılanan kalitede meydana gelen 1 birimlik artış
algılanan kontrolde 0.99 birim artışa sebep olacaktır. Aynı şekilde algılanan
kalitede meydana gelen 1 birimlik artış algılanan kullanılabilirlikte 0.96
birim artışa sebep olacaktır, algılanan kullanılabilirlikte meydana gelen 1
birimlik artış memnuniyette 0.90 birimlik artışa sebep olacaktır ve son olarak
memnuniyette meydana gelen 1 birimlik artış kullanmaya devam etme niyetinde
0.93 birim artışa sebep olacaktır. Belirlilik katsayıları (
 ) % 91, %81 ve %87 olarak hesaplanmıştır.









Araştırmanın Sonuçları ve Önerileri:
Uzaktan eğitim sistemleri internet ve iletişim alanında yaşanılan gelişmelerle
birlikte öğrenme biçimlerinde çeşitliliğe yol açmıştır. Uzaktan eğitim artık
çoğunluğu web tabanlı olan bu sistemler üzerinden yürütülmektedir. Bu sistemler
birçok isimle, birçok öğrenme ortamı ile karşımıza çıkmaktadır. M-öğrenme,
harmanlanmış öğrenme, sanal ve gerçekliği arttırılmış öğrenme ortamları
bunlardan bazılarıdır. E-öğrenme uygulamaları açısından başarılı öğrenme
ortamlarının sağlanması önemli bir konudur. E-öğrenmenin şekli Web’ de yaşanan
gelişmelerle birlikte kullanıcıları öğrenme sürecinde üçüncü şahıs olmaktan öteye
geçirmiş, Web 2.0 ile etkileşime açık hale gelen öğrenme ortamları Web 3.0 ile
kullanıcıları öğrenme sürecine dâhil etmiştir. Bu sebeplerle kullanıcının
giderek sistemin merkezine oturduğu bu e-öğrenme sistemlerini kullanmaya devam
etme niyetlerini etkileyen faktörlerin incelenmesi araştırılmaya değer bir
konudur. Bu sebeple bu çalışma ile literatür incelenerek bir e-öğrenme
sistemini kullanmaya devam etme niyetini etkileyebilecek yapılar gerek önceki
çalışmalar ışığında gerekse yapılan analizler ve yapısal eşitlik modelleri ile
incelenmiştir. Kullanılan modellerde algılanan kalite, algılanan
kullanılabilirlik, algılanan kontrol, memnuniyet ve kullanmaya devam etme
niyeti yapıları arasındaki ilişkiler açığa çıkarılmaya çalışılmıştır. TAM ve
EDT’ nin yapıları ile bir takım diğer yapılar birleştirilerek incelenmiştir.
İlk olarak algılanan kalitenin sistem, servis ve bilgi kaliteleri ile
açıklanabileceği öne sürülmüş ve bu ilişkiler doğrulanmıştır. Literatürde bilgi
ve sistem kalitelerinin e-öğrenme ile ilgili çalışmalarda servis kalitesine
görece daha fazla kullanılmış olduğu görülmüştür. Ancak servis kalitesinin
algılanan kalitedeki değişimi açıklamada %85 ile önemli bir etkisinin olduğu
belirlenmiştir. Algılanan kullanılabilirlik yapısı, algılanan fayda, algılanan
kullanım kolaylığı ve bilişsel kapılma faktörleri ile açıklanmak istenmiş ve bu
ilişkiler de anlamlı bulunmuştur. Burada bahsedilmesi gereken önemli bir nokta,
bilişsel kapılmanın literatürde benzer kavramlar olarak nitelendirilen
algılanan eğlenebilirlik ve algılanan zevk bileşenleri olarak farklı isimlerle
de olsa bilgi sistemlerini ilgilendiren birçok çalışmada yer almasıdır. Diğer
bir hipotezde algılanan kalitenin algılanan kullanılabilirlik üzerindeki etkisi
incelenmiş ve anlamlı bir etkisi olduğu gösterilmiştir. Daha sonra algılanan
kontrol yapısı; internet öz-yeterliliği, bilgisayar öz yeterliliği ve internet
deneyimi boyutları ile incelenmiştir. Son yıllarda yapılan çalışmalarda
e-öğrenme öz-yeterliliği, e-öğrenme deneyimi gibi kavramların kullanıldığı
görülmüştür Bu sebeple Ülkemizde de e-öğrenme yaygınlaşmaya devam ettikçe
e-öğrenme deneyiminin farklı bir boyut olarak ayrıca irdelenmesinin faydalı
olacağı düşünülmektedir. Nitekim araştırmanın ilk kısmında yer alan demografik
bilgiler kısmında kullanıcıların daha önceden online bir sertifika programına
katılıp katılmadıkları sorulmuş ve öğrencilerin yaklaşık % 80’inin katılmadığı
bilgisine ulaşılmıştır. Kullanmaya devam etme niyetinde memnuniyetin pozitif
bir etkisi olduğu belirlenmiştir. Bu çalışmada yapılar arasındaki ilişkiler
ayrı ayrı birbirleri açısından değerlendirilmiştir ve sonuç olarak memnuniyetin
kullanmaya devam etme niyetinde direk etkisi olduğu diğer yapıların ise dolaylı
etkisi olduğu belirlenmiştir. Sayıca çoğalan online eğitim veren kuruluşlar göz
önünde bulundurulduğunda özellikle algılanan kalite yapısının gelecekteki
çalışmalarca incelenmesi faydalı olacaktır. Van Yüzüncü Yıl Üniversitesinde
uzaktan eğitimle pedagojik formasyon eğitimi gören öğrencilerin bir kısmına
anket uygulanması ile oluşturulmuştur. Bunlar araştırmanın kısıtlarını
oluşturmaktadır. Benzer çalışmalar farklı uzaktan eğitim merkezleri ve uzaktan
eğitim veren kuruluşlarca farklı öğrenci/kullanıcı gruplarına uygulanabilir.
Özellikle şirketlerce de kullanımı yaygınlaşan e-öğrenme sistemleri bu
çevrelere yapılacak araştırmalarla genişletilebilir. Web tabanlı eğitim
sistemleri yapısı farklı faktörler kullanılarak çözümlenebilir. Yapılacak
karşılaştırmalı çalışmalar ve benzer çalışmalar ile bu alanda faaliyet gösteren
kuruluşlara yol gösterme anlamında katkı sunabilir.

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  • Taylor, S., & Todd, P. (1995). Assessing IT usage: the role of prior experience. MIS Quarterly, 19(4), 561–570.
  • Teh, P. L., & Yong, C. C. (2011). Knowledge sharing in IS personnel: Organizational behavior's perspective. Journal of Computer Information Systems, 51(4), 11.
  • Teo, T., & Noyes, J. (2011). An assessment of the influence of perceived enjoyment and attitude on the intention to use technology among pre-service teachers: A structural equation modeling approach. Computers & Education, 57(2), 1645-1653.
  • Teune, H., & Przeworski, A. (1970). The logic of comparative social inquiry (pp. 32-34). New York: Wiley-Interscience.
  • Timm, H. N. (2002). Applied Multivariate Analysis. New York: Springer.
  • Tomer, A. (2003). A short history of structural equation models. In B. Pugesek (Ed.), Structural equation modeling: Applications in ecological and evolutionary biology (pp. 85−121). Cambridge University Press.
  • Torkzadeh, G., & Van Dyke, T.P. (2001). Development and validation of an Internet self-efficacy scale. Behaviour and Information Technology, 20(4), 275–280.
  • Tsai, C. C., Lin, S. S., & Tsai, M. J. (2001). Developing an Internet attitude scale for high school students. Computers & Education, 37(1), 41-51.
  • Udo, G. J., Bagchi, K. K., & Kirs, P. J. (2011). Using SERVQUAL to assess the quality of e-learning experience. Computers in Human Behavior, 27(3), 1272-1283.
  • Usluel, Y. K., & Vural, F. K. (2009). Adaptation of cognitive absorption scale to Turkish. Egitim Bilimleri Fakultesi Dergisi, 42(2), 77.
  • 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.
  • Venkatesh, V. (2000). Determinants of perceived ease of use: integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342–365.
  • Venkatesh, V., & Davis, F.D. (2000). A theoretical extension of the technology acceptance model: four longitudinal field studies. Management Science, 46(2), 186–204.
  • Wang, Y. S., Lin, H. H., & Liao, Y. W. (2012). Investigating the individual difference antecedents of perceived enjoyment in students’ use of blogging. British Journal of Educational Technology, 43(1), 139-152.
  • Webster, J., & Martocchio, J.J. (1992). Microcomputer playfulness: Development of a measure with workplace implications. MIS Quarterly, 16(2), 201–226.
  • Wen, C., Prybutok, V. R., & Xu, C. (2011). An integrated model for customer online repurchase intention. Journal of Computer Information Systems, 52(1), 14-23.
  • Whitten, D., & Wakefield, R. L. (2006). Measuring switching costs in IT outsourcing services. The Journal of Strategic Information Systems, 15(3), 219-248.
  • Wood, R., & Bandura, A. (1989). Social cognitive theory of organizational management. Academy of Management Review, 14(3), 361-384.
  • Woszczynski, A.B., Roth, P.L., & Segars, A.H. (2002). Exploring the theoretical foundations of playfulness in computer interactions. Computers in Human Behavior, 18(4), 369–388.
  • Xu, J. D., Benbasat, I., & Cenfetelli, R. T. (2013). Integrating service quality with system and information quality: an empirical test in the e-service context. MIS Quarterly, 37(3), 777-794.

Examination of Factors Affecting Continuance Intention to use Web-Based Distance Learning System via Structural Equation Modelling

Yıl 2018, Cilt: 18 Sayı: 78, 43 - 66, 20.11.2018

Öz

Purpose: The present study aims to
model continuance intention to use web-based distance learning system and
reveal the relationship between structures. Method: In this study, factors affecting continuance intention to
use a web-based distance learning system was examined with a sample of 104
students attending an initial teacher training program through a web-based
distance learning system at Van Yüzüncü Yıl University. The structures used in
the study were identified as a result of a detailed review of literature.
Moreover, complex structure of web-based distance learning systems, which
included many components, were analyzed.



Technology Acceptance Model and Expectancy Disconfirmation Theory were used
in determining the model to be used, and comprehensive research was conducted. Findings: continuance intention to use web-based
distance learning system was indirectly affected by perceived quality,
perceived control, perceived usability; and was directly affected by
satisfaction.
Implications for Research and Practice: Similar studies can be
conducted with different student/user groups by different distance learning centers
and institutions that provide distance learning services. Web-based distance
learning systems, which have become widely used especially by companies, can be
expanded via studies to be conducted within these environments

Kaynakça

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  • Strong, D. M., Dishaw, M. T., & Bandy, D. B. (2006). Extending task technology fit with computer self-efficacy. ACM SIGMIS Database, 37(2-3), 96-107.
  • Tan, M., & Teo, T. S., (2000). Factors influencing the adoption of Internet banking. Journal of the AIS, 1(1es), 5.
  • Taylor, S., & Todd, P. (1995). Assessing IT usage: the role of prior experience. MIS Quarterly, 19(4), 561–570.
  • Teh, P. L., & Yong, C. C. (2011). Knowledge sharing in IS personnel: Organizational behavior's perspective. Journal of Computer Information Systems, 51(4), 11.
  • Teo, T., & Noyes, J. (2011). An assessment of the influence of perceived enjoyment and attitude on the intention to use technology among pre-service teachers: A structural equation modeling approach. Computers & Education, 57(2), 1645-1653.
  • Teune, H., & Przeworski, A. (1970). The logic of comparative social inquiry (pp. 32-34). New York: Wiley-Interscience.
  • Timm, H. N. (2002). Applied Multivariate Analysis. New York: Springer.
  • Tomer, A. (2003). A short history of structural equation models. In B. Pugesek (Ed.), Structural equation modeling: Applications in ecological and evolutionary biology (pp. 85−121). Cambridge University Press.
  • Torkzadeh, G., & Van Dyke, T.P. (2001). Development and validation of an Internet self-efficacy scale. Behaviour and Information Technology, 20(4), 275–280.
  • Tsai, C. C., Lin, S. S., & Tsai, M. J. (2001). Developing an Internet attitude scale for high school students. Computers & Education, 37(1), 41-51.
  • Udo, G. J., Bagchi, K. K., & Kirs, P. J. (2011). Using SERVQUAL to assess the quality of e-learning experience. Computers in Human Behavior, 27(3), 1272-1283.
  • Usluel, Y. K., & Vural, F. K. (2009). Adaptation of cognitive absorption scale to Turkish. Egitim Bilimleri Fakultesi Dergisi, 42(2), 77.
  • 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.
  • Venkatesh, V. (2000). Determinants of perceived ease of use: integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342–365.
  • Venkatesh, V., & Davis, F.D. (2000). A theoretical extension of the technology acceptance model: four longitudinal field studies. Management Science, 46(2), 186–204.
  • Wang, Y. S., Lin, H. H., & Liao, Y. W. (2012). Investigating the individual difference antecedents of perceived enjoyment in students’ use of blogging. British Journal of Educational Technology, 43(1), 139-152.
  • Webster, J., & Martocchio, J.J. (1992). Microcomputer playfulness: Development of a measure with workplace implications. MIS Quarterly, 16(2), 201–226.
  • Wen, C., Prybutok, V. R., & Xu, C. (2011). An integrated model for customer online repurchase intention. Journal of Computer Information Systems, 52(1), 14-23.
  • Whitten, D., & Wakefield, R. L. (2006). Measuring switching costs in IT outsourcing services. The Journal of Strategic Information Systems, 15(3), 219-248.
  • Wood, R., & Bandura, A. (1989). Social cognitive theory of organizational management. Academy of Management Review, 14(3), 361-384.
  • Woszczynski, A.B., Roth, P.L., & Segars, A.H. (2002). Exploring the theoretical foundations of playfulness in computer interactions. Computers in Human Behavior, 18(4), 369–388.
  • Xu, J. D., Benbasat, I., & Cenfetelli, R. T. (2013). Integrating service quality with system and information quality: an empirical test in the e-service context. MIS Quarterly, 37(3), 777-794.
Toplam 107 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Makaleler
Yazarlar

Kubra Bagcı

H. Eray Celık Bu kişi benim

Yayımlanma Tarihi 20 Kasım 2018
Yayımlandığı Sayı Yıl 2018 Cilt: 18 Sayı: 78

Kaynak Göster

APA Bagcı, K., & Celık, H. E. (2018). Examination of Factors Affecting Continuance Intention to use Web-Based Distance Learning System via Structural Equation Modelling. Eurasian Journal of Educational Research, 18(78), 43-66.
AMA Bagcı K, Celık HE. Examination of Factors Affecting Continuance Intention to use Web-Based Distance Learning System via Structural Equation Modelling. Eurasian Journal of Educational Research. Kasım 2018;18(78):43-66.
Chicago Bagcı, Kubra, ve H. Eray Celık. “Examination of Factors Affecting Continuance Intention to Use Web-Based Distance Learning System via Structural Equation Modelling”. Eurasian Journal of Educational Research 18, sy. 78 (Kasım 2018): 43-66.
EndNote Bagcı K, Celık HE (01 Kasım 2018) Examination of Factors Affecting Continuance Intention to use Web-Based Distance Learning System via Structural Equation Modelling. Eurasian Journal of Educational Research 18 78 43–66.
IEEE K. Bagcı ve H. E. Celık, “Examination of Factors Affecting Continuance Intention to use Web-Based Distance Learning System via Structural Equation Modelling”, Eurasian Journal of Educational Research, c. 18, sy. 78, ss. 43–66, 2018.
ISNAD Bagcı, Kubra - Celık, H. Eray. “Examination of Factors Affecting Continuance Intention to Use Web-Based Distance Learning System via Structural Equation Modelling”. Eurasian Journal of Educational Research 18/78 (Kasım 2018), 43-66.
JAMA Bagcı K, Celık HE. Examination of Factors Affecting Continuance Intention to use Web-Based Distance Learning System via Structural Equation Modelling. Eurasian Journal of Educational Research. 2018;18:43–66.
MLA Bagcı, Kubra ve H. Eray Celık. “Examination of Factors Affecting Continuance Intention to Use Web-Based Distance Learning System via Structural Equation Modelling”. Eurasian Journal of Educational Research, c. 18, sy. 78, 2018, ss. 43-66.
Vancouver Bagcı K, Celık HE. Examination of Factors Affecting Continuance Intention to use Web-Based Distance Learning System via Structural Equation Modelling. Eurasian Journal of Educational Research. 2018;18(78):43-66.