Early intervention and early education have a special place in educating the children with Impaired Hearing (IH). The advancements in information and communication technologies have led to adopting the view that such technologies could be applied in the educational process of the children with IH. Besides, the positive results acquired in the studies conducted in the light of this review have brought up the fact that proper technology-based educational environments should be provided and popularized for the young children with IH. In this study, educational software has been developed for the purpose of teaching emotions and opposite concepts to young children with IH. With this software, videos with topic descriptions, games reinforcing funny and topic-based learning, questions and audio-visual feedbacks have been used. The effectiveness of this software in concept education along with its usability by children has been examined; and in addition, the subjective viewpoints of the teachers of students with IH on this software have been consulted as well.
Özet-Bu çalışmada, FATİH projesine yönelik internet ortamında yer alan görüşlerin metin madenciliği yöntemleri ile otomatik tespitinin yapılması amaçlanmaktadır. Çalışma iki temel kısımdan meydana gelmektedir. İlk basamakta, internet ortamındaki yapısal olmayan veri kümelerinin yapısal veri haline dönüştürülmesini sağlamak amacıyla metin madenciliği veri önişleme yazılımı geliştirilmiştir. İkinci basamakta ise geliştirilen metin madenciliği veri önişleme yazılımı ile yapısal veri kümesine dönüştürülen veriler üzerinde makine öğrenmesi algoritmaları uygulanarak yorumlar otomatik sınıflandırılmaktadır. Geliştirilen metin madenciliği veri önişleme yazılımının en önemli ayırt edici özelliği, yazılımın sadece FATİH projesine yönelik görüşlerinin veri önişleme basamağında değil, istenilen amaca yönelik metin sınıflandırma işleminin veri önişleme basamağında konudan bağımsız bir şekilde kullanılabilir olmasıdır. Çalışmada FATİH projesine yönelik 444 görüş içeren metin dosyasındaki metinler tf-idf ağırlıklandırma yöntemi ile vektörel olarak temsil edilerek sınıflandırma algoritmalarının model başarım ölçütleri karşılaştırılmıştır. Performansı karşılaştırılan algoritmalardan en yüksek başarımın Ardışık Minimal Optimizasyon Algoritmasına ait olduğu (%88,73) gözlemlenmiştir.Anahtar Kelimeler-Metin madenciliği, FATİH projesi, metin sınıflandırma, fikir madenciliği, ardışık minimal optimizasyon algoritması.
Automatic Evaluation of Opinions Concerning FATİH Project with Text Mining MethodsAbstract-In this study, it is aimed to make automatic determination of views towards the FATIH project in internet environment by using text mining methods. The study is based on two main parts. In the first step, text mining data preprocessing software was developed to convert non-structural data sets on the internet into structured data. In the second step, interpretation is automatically classified by applying machine learning algorithms on the data converted into the structural data set with the developed text mining data preprocessing software. The most important distinguishing feature of the developed text mining data preprogramming software is that its views at the data preprocessing step are not only available for the FATIH project but it is available at the data preprocessing step of all the desired text classification purposes. In the study, the texts containing 444 visions for the FATIH project were represented as vectors by the tf-idf weighting method and the model performance criteria of the classification algorithms were compared. Highest achievement for performance comparison algorithms is detected that Sequential Minimal Optimization Algorithm (88.73%).
In this study, the aim is to analyze the relationships between phubbing, alienation, digital game addiction, independent self-construal, and interdependent self-construal among high school students. The sample of the study consists of 1,932 students studying in different high schools in Turkey who were selected by the stratified random sampling method, considering the grade levels and gender variables. The students completed surveys regarding self-construal, digital game addiction, alienation, and phubbing. The data obtained were analyzed by path analysis, one of the structural equation modeling methods. In the research, nine hypotheses were developed for the proposed model based on theoretical knowledge. As a result of the analysis, eight hypotheses were supported, and one was unsupported. According to the findings, digital game addiction had a significant impact on alienation and phubbing; also, alienation had a considerable impact on phubbing. The model explained 16% of the variance (R2= .16) of phubbing, directly and indirectly. This means that the exogenous variables have a moderate level of influence on the endogenous variable. Moreover, alienation had a maximum degree of effect on phubbing.
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