| Título: | Judging Primary School Classroom Spaces Via Artificial Neural Networks Model |
| Autores: |
Hatice Derya ARSLAN; Selcuk University,
Eng-Arch. Faculty,
Architecture Department
Campus Selcuklu Konya Murat CEYLAN; Selcuk University, Eng-Arch. Faculty, Electical Engineering Department Campus Selcuklu Konya |
| Fecha: | 2012-01-24 |
| Publicador: | Gazi University Journal of Science |
| Fuente: |
 |
| Tipo: | Peer-reviewed Article |
| Tema: | Spatial perception, Statistical analysis, Classroom design, Artificial Neural Networks. |
| Descripción: | An experimental study was conducted with 2nd grade students at primary schools in Turkey as part of an attempt to describe the ideal classroom space for primary education students. In the study, photographs of 20 different primary education classrooms were evaluated by 189 students. The students evaluated the images by means of surveys in which they were asked questions on four concepts: belonging, like (partiality), learning and safety. Reliability analyses of numeric data obtained from student surveys were made and they were subjected to various statistical analyses. In the second part of the study, the students’ preferences for the classroom spaces were evaluated by means of Artificial Neural Networks (ANN) method, by using numeric data obtained from the student about concepts as well as the classroom space photos. Numeric data were treated and test procedures were performed to ensure that ANN makes decisions in the name of 2nd grade students. This is the first study in which numeric survey results and photographic characteristics have been used together. The ANN results were very similar to the students’ evaluation of the ideal classroom space, particularly in terms of belonging and like (partiality) concepts. Key Words: Spatial perception, Statistical analysis, Classroom design, Artificial Neural Networks. |
| Idioma: | Inglés |