PROFILING LEARNING PREFERENCES OF DISTANCE EDUCATION STUDENTS BASED ON NEURAL NETWORK ANALYSIS

Abstract

The learning preferences of the learners are of prime importance in the planning of distance education systems and the design of learning environments. Learning technique and learning material preferences are considered as the two most common and referable learning preferences to understand the learning preferences profile of distance education students. This research investigates the learning preferences of distance education students. Data was collected from 3390 distance education students from Anadolu University, considered as one of the mega universities in the world. Neurol Network Analyze conducted to profile learning preferences of distance education students. For this purpose, Multilayer Perception Model was applied as an artificial neural network analysis model in the analysis of data. The age of students was found as the most important independent variable on the prediction of material preferences and learning technique preferences of distance education students. The full Multilayer Perception Model of the learning preferences profile of distance education students was provided as a conclusion. Recommendations provided for future research and applications.