Abstract
In this study, an experimental study was conducted with 4th grade students at classroom teaching department in Turkey in an attempt to describe the ideal classroom space for primary education students. In the research, photographs (images) of 20 different primary education classrooms were evaluated by 4th grade 100 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 numerical data obtained from the student about concepts as well as the classroom space photos. Levenberg-Marquart (LM) back-propagation algorithm has been used to train ANN model. Numerical data were treated and test procedures were performed to ensure that ANN makes decisions in the name of 4th grade students at classroom teaching department. It has been seen that ANN has been successful on solving complex problems such as user-perception evaluations thanks to its dynamic structure.
Abstract
Bu çaly?mada, ideal ilkö?retim synyf mekânynyn tanymlanabilmesi amacyyla synyf ö?retmenleri üzerinde deneysel bir çaly?ma gerçekle?tirilmi?tir. Ara?tyrmada, 20 farkly ilkö?retim synyf mekâny görselleri (foto?raflary), 100 synyf ö?retmeni tarafyndan de?erlendirilmi?tir. Synyf ö?retmenlerinin de?erlendirmeleri anket aracyly?y ile alynmy? ve ö?retmenlerden synyfy kullanacak olan ö?renciler açysyndan synyf görsellerinin de?erlendirmelerini yapmalary istenmi?tir. Bu ba?lamda ö?retmenlere aidiyet, be?eni, ö?renme ve güven olmak üzere dört kavrama ili?kin sorular synyf görselleri üzerinden sorulmu?tur. Anketlerden elde edilen sayysal verilerin güvenilirlik analizleri yapylmy? ve çe?itli istatistiksel analiz i?lemlerine tabi tutulmu?tur. Çaly?manyn ikinci kysmynda ise, synyf ö?retmenleri anketlerinden elde edilen veriler ve synyf görselleri kullanylarak Yapay Sinir A?lary (YSA) yöntemiyle yeni bir model kurulmu? ve YSA'nyn bu model sayesinde anket sonuçlary ile synyf görselleri arasynda sayysal bir ili?ki kurmasyna çaly?ylmy?tyr. YSA modelinin e?itimi için Levenberg-Marquart (LM) geri yayylym algoritmasy kullanylmy?tyr. YSA modeli sonuçlary ile synyf ö?retmenlerinden elde edilen verilerin istatistiksel analiz sonuçlarynyn büyük do?ruluk oranlaryyla e?le?ti?i görülmü?tür. YSA'nyn dinamik yapysyndan dolayy kullanycy - algy de?erlendirmesi gibi karma?yk problemlerin çözümünde ba?aryly oldu?u görülmü?tür.
Details
| Primary Language | Turkish |
|---|---|
| Journal Section | Computer Engineering |
| Authors | |
| Publication Date | May 1, 2011 |
| Published in Issue | Year 2011 Volume: 6 Issue: 4 |