Yıl 2021, Cilt 22 , Sayı 2, Sayfalar 58 - 80 2021-04-01


Rahmi BAKI [1] , Burak BIRGOREN [2] , Adnan AKTEPE [3]

The use and benefit of Distance Learning Systems (DLS) can be increased by a detailed analysis of the factors affecting students’ intention to use. This study aims to analyse the effect of various independent variables on the user satisfaction and intention to use DLS via Perceived Ease of Use and Perceived Usefulness. In addition, Time Effectiveness is proposed as a new variable with the claim that the time spent in DLS is valuable. Data were collected from 925 undergraduate students currently enrolled in 9 state universities in Turkey. Data were analysed through Structural Equation Modelling (SEM). Results show that while Interaction, Compatibility and Time Effectiveness have a positive effect on user satisfaction and intention to use via Perceived Usefulness; Self Efficacy, Subjective Norm and Enjoyment have no influence. Moreover, Self Efficacy, Interaction, Anxiety and Time Effectiveness have a significant impact on Perceived Ease of Use, yet Subjective Norm and Enjoyment don’t.
Distance Learning System, Technology Acceptance Model, intention to use, user satisfaction, e-learning
  • Abbad, M. M., Morris, D., & Nahlik, C. D. (2009). Looking under the bonnet: Factors affecting student adoption of e-Learning systems in Jordan. International Review of Research in Open and Distance Learning, 10(2), 1-15.
  • Abdullah, F., & Ward, R. (2016). Developing a general extended technology acceptance model dor e-learning (GETAMEL) by analysing commonly used external factors. Computers in Human Behaviour, 56, 238-256.
  • Abdullah, F., Ward, R., & Ahmed, E. (2016). Investigating the influence of the most commonly used external variables of TAM on students’ perceived ease of use (PEOU) and perceived usefulness (PU) of e-portfolios. Computers in Human Behavior, 63, 75-90.
  • Abramson, J., Dawson, M., & Stevens, J. (2015). An examination of the prior use of e-learning within an extended technology acceptance model and the factors that influence the behavioral intention of users to use m-learning. SAGE Open, 5(4), 1-9.
  • Adornetto, C., Hensdiek, M., Meyer, A., In-Albon, T., Federer, M., & Schneider, S. (2008). The factor structure of the childhood anxiety sensitivity index in German children. Journal of Behavior Therapy and Experimental Psychiatry, 39(4), 404-416.
  • Agudo-Peregrina, A. F., Hernandez-Garcia, A., & Pascual-Miguel, F. J. (2014). Behavioral intention, use behavior and the acceptance of electronic learning systems: Differences between higher education and lifelong learning. Computers in Human Behavior, 34, 301-314.
  • Ajzen, I. (1991). The theory of planned behaviour. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
  • Al-Ammari, J., & Hamad, S. (2008, April). Factors influencing the adoption of e-learning at UOB. In 2nd International Conference and Exhibition for Zain E-learning Center, 28-30.
Birincil Dil en
Konular Sosyal
Bölüm Articles

Yazar: Rahmi BAKI (Sorumlu Yazar)
Ülke: Turkey

Yazar: Burak BIRGOREN
Ülke: Turkey

Yazar: Adnan AKTEPE
Ülke: Turkey


Başvuru Tarihi : 9 Mayıs 2020
Kabul Tarihi : 30 Nisan 2021
Yayımlanma Tarihi : 1 Nisan 2021

APA Bakı, R , Bırgoren, B , Aktepe, A . (2021). IDENTIFYING FACTORS AFFECTING INTENTION TO USE IN DISTANCE LEARNING SYSTEMS . Turkish Online Journal of Distance Education , 22 (2) , 58-80 . DOI: 10.17718/tojde.906545