Psychological Variables of Estimating Distance Learners' Motivation


The correlation between distance education motivation levels of students and their online experiences and satisfaction is studied in this paper; and the reasons of their satisfaction and dissatisfaction according to their motivation levels are described. In this study, 183 students, who were taking English and Turkish courses at Ankara University between 2013-2014 academic year through distance education participated. The study which was designed in the form of sequential mixed method research design, “Motivation and Learning Strategies Inventory” and “Online Student Satisfaction Scale” were utilized to collect data and structured interview forms that were developed by the researchers and they were also used to determine students’ online learning experiences and their satisfaction levels about distance education. Three motivation levels as low- medium-level- high were identified by clustering analysis. Logistic regression analysis was performed to evaluate motivation levels and satisfaction data and content analysis was applied to evaluate the reasons behind their satisfaction. A significant correlation was found between the students’ motivation levels and their online learning experiences and satisfaction. When it comes to the reasons of their satisfaction and dissatisfaction, the students who have low and medium-level motivation levels said that their dissatisfaction was due to lack of interaction and negative perceptions and their dependence on conventional education. On the other hand, the students who have high motivation stated that their satisfaction was because it is free from time and space, suitable for reviews, provides effective learning and meets the requirements of this age. The students who were not satisfied in three different motivation levels mentioned the problems of internet access and lack of synchronization between the picture and the sound in the videos.

KEYWORDS: Distance education motivation, online learning experience, distance education satisfaction, clustering analysis, logistic regression.