Year 2020, Volume 21 , Issue 3, Pages 156 - 169 2020-07-01

ARTIFICIAL NEURAL NETWORK APPROACH TO PREDICT LMS ACCEPTANCE OF VOCATIONAL SCHOOL STUDENTS

Umut Birkan ÖZKAN [1] , Harun CİGDEM [2] , Tolga ERDOGAN [3]


The contribution of e-learning technologies, especially LMS which has become an important component of e-learning, is significantly increasing in higher education. It is critical to understand the factors that affect the behavioral intention of students towards LMS use. The aim of this study is to explore predictors of students’ acceptance of Course Portal at a postsecondary vocational school level. We utilised a framework suggested by Sezer and Yilmaz (2019) for understanding students’ acceptance of LMS. This framework obtains the main constructs in UTAUT: namely, performance expectancy, effort expectancy, social influence and facilitating conditions. More external variables, associate degree programs, high school type, academic grade point average were also adopted. Accordingly, 387 students were answered the questionnaire for investigating behavioral intention. Artificial neural network analysis (ANN) was used to predict students’ acceptance of LMS use according to variables associated with their use of LMS technology. ANN analyses in the present study revealed that performance expectancy, effort expectancy, social influence and facilitating conditions are important predictors of students’ behavioral intention to use LMS. Nevertheless, performance expectancy was found to be the most influencing predictor of LMS use. The analyses of this research provides evidence on the utilization of ANN to predict the determining factors of LMS acceptance.
Artificial neural networks, LMS acceptance, UTAUT,, MOODLE,, social influence, vocational school
  • Haykin, S. (2004). Neural Networks: A Comprehensive Foundation. Pearson Education.
Primary Language en
Subjects Social
Journal Section Articles
Authors

Orcid: 0000-0001-8978-3213
Author: Umut Birkan ÖZKAN (Primary Author)
Institution: National Defence University
Country: Turkey


Orcid: 0000-0001-5958-5216
Author: Harun CİGDEM
Institution: National Defence University
Country: Turkey


Orcid: 0000-0002-1921-5517
Author: Tolga ERDOGAN
Institution: TED ÜNİVERSİTESİ
Country: Turkey


Dates

Application Date : June 20, 2019
Acceptance Date : August 6, 2020
Publication Date : July 1, 2020

APA Özkan, U , Ci̇gdem, H , Erdogan, T . (2020). ARTIFICIAL NEURAL NETWORK APPROACH TO PREDICT LMS ACCEPTANCE OF VOCATIONAL SCHOOL STUDENTS . Turkish Online Journal of Distance Education , 21 (3) , 156-169 . DOI: 10.17718/tojde.762045