Examining Factors of Academic Procrastination Tendency of University Students by using Artificial Neural Network

Examining Factors of Academic Procrastination Tendency of University Students by using Artificial Neural Network

  IJCTT-book-cover
 		 International Journal of Computer Trends and Technology (IJCTT)          
 
© 2016 by IJCTT Journal
Volume-34 Number-1
Year of Publication : 2016
Authors : Dr. Murat Kayri, Dr. Ömay Çokluk
DOI :  10.14445/22312803/IJCTT-V34P101

MLA

Dr. Murat Kayri, Dr. Ömay Çokluk "Examining Factors of Academic Procrastination Tendency of University Students by using Artificial Neural Network". International Journal of Computer Trends and Technology (IJCTT) V34(1):1-8, April 2016. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
The purpose of this study is to model the factors that are influential on academic procrastination behaviour with artificial neural network. The population of the research consisted of students in undergraduate programs of Ankara University. A sample was not selected from the population since access to the whole population was targeted. So, this study was carried out on 1271 university students. Information about personal and socio-demographic features in the research was gathered with a form prepared by the authors. The Academic Procrastination Scale and the General Procrastination Scale were applied in the study to explore the levels of academic procrastination and general procrastination of the participants. The influential factors on academic procrastination were scrutinized by using Radial Basis Function Artificial Neural Network. It is clear that the “general procrastination tendency”, “self-assessment of course attendance”, “studying habit satisfaction”, “Preference in revision for exams” and “Planning before any kind of tasks” predictors are influential on academic procrastination tendency. In this study, neural network which is one of the robust and unbiased methods was applied to the educational data due to the its’ predictive ability.

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Keywords
Academic Procrastination, General Procrastination, Artificial Neural Networks, Radial Basis Function.