Self-organizing neural network map for the purpose of visualizing the concept images of students on angles

Abstract

The purpose of the study is to perform a less-dimensional thorough visualization process for the purpose of determining the images of the students on the concept of angle. The Ward clustering analysis combined with Self-Organizing Neural Network Map (SOM) has been used for the dimension process. The Conceptual Understanding Tool, which consisted of the open-ended question “write the first ten things you remember when the term „angle‟ is mentioned” to the study group, which consisted of 250 seventh grade students. The analysis results showed that students mostly explained the concept of angle by associating it with mathematics and other sciences with the terms like “reflection and incidence angle, numbers, light, graphics, fraction, area, speed, algebraic expressions, energy, sound, four operations, viewpoint, electricity and natural numbers”. The students mostly established relations with the static side of the angle. At the end of the study, the dataset obtained from the Conceptual Understanding Tool was used for training the SOM, and a structure that reveals the images of the students on angle has been recommended