Welcome to the Open Access System!


OpenAccess@IKU is the Academic Open Access System of Istanbul Kultur University. It was established in June 2014 to digitally store and open access the academic outputs of Istanbul Kultur University in international standards. OpenAccess@IKU includes academic outputs such as articles, presentations, thesis, books, book chapters, reports produced within the body of Istanbul Kultur University.


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PublicationOpen Access
Ortaokullarda Görev Yapan Yöneticilerin Sergiledikleri Liderlik Stillerinin Öğretmenlerin İş Performansına Etkisi
(Milli Eğitim Bakanlığı, 2023) Can, Sultan; GÜNEŞ, DEMET ZAFER
Bu araştırmanın amacı, yöneticilerin dönüşümcü, öğretimsel, kültürel, vizyoner ve etik liderlik stillerinin ortaokulda görev yapan öğretmenlerin iş performansına etkisini belirlemektir. Araştırmada nicel araştırma yöntemlerinden ilişkisel tarama modeli kullanılmıştır. Araştırmanın evrenini 2021-2022 eğitim öğretim yılında İstanbul ili Küçükçekmece ilçesinde devlet ortaokulunda görev yapan 2194 öğretmen oluşturmaktadır. Araştırmanın örneklemini basit seçkisiz örnekleme yöntemi ile seçilen 318 öğretmen oluşturmaktadır. Bulguların toplanmasında “Demografik Bilgi Formu”, “Liderlik Stilleri Ölçeği” ve “Öğretmen Performans Ölçeği” kullanılmıştır. Verilerin analizinden önce verilerin normal dağılıp dağılmadığına bakılmış, verilerin normal dağılım gösterdiği tespit edilmiştir. Verilerin analizinde frekans, yüzde, ortalama, minimum, maksimum, standart sapma, korelasyon ve basit doğrusal regresyon kullanılmıştır. Araştırma sonucunda yöneticilerin sergiledikleri; dönüşümcü, öğretimsel, kültürel, vizyoner ve etik liderlik stilleri ile ilgili öğretmen görüşlerinin yüksek düzeyde olduğu belirlenmiştir. Öğretmenlerin performans ölçeği geneli için görüşlerinin yüksek düzeyde olduğu belirlenmiştir. Liderlik stilleri ve öğretmen performansı arasında pozitif yönde düşük düzeyde anlamlı bir ilişki tespit edilmiştir. Ayrıca liderlik stillerinin, öğretmen performansının anlamlı bir yordayıcısı olduğu sonucuna ulaşılmıştır.
Publication
COVID-19 Fear, Vaccination Hesitancy, and Vaccination Status in Pregnant and Breastfeeding Women in Turkey
(Afr J Reprod Health, 2023) MİRAL, MUKADDES TURAN; Turgut, Nurgül; Güldür, Ayşe; Güloğlu, Zübeyde E.; Mamuk, Rojjin
This study aimed to determine the level of COVID-19 fear, vaccination, and vaccination hesitancy as well as the affecting factors in pregnant and breastfeeding women who participated in an online prenatal education in Turkey. The study, which was designed as descriptive cross-sectional, was conducted online with 360 pregnant and breastfeeding women from Istanbul. Data were collected through the Participant Information Form, Fear of COVID-19 Scale and Vaccine Hesitancy Scale in Pandemics. The rate of accepting the COVID-19 vaccine is 65.6%. The Fear of COVID-19 Scale was 16.215.54, and the Vaccine Hesitancy Scale in Pandemics mean score was 29.294.54. The COVID-19 fear of the women participating in this study was moderate, the level of vaccination hesitancy was low, and two-thirds of them were vaccinated. There is a need to organize special counseling and vaccination campaigns for pregnant and lactating women.
PublicationOpen Access
Augmented Reality Experience in an Architectural Design Studio
(Springer, 2023) Alp, Neşe Çakıcı; YAZICI, YASEMİN ERKAN; Öner, Dilan
Thanks to the developing technology, different methods and tools are used in architectural representation, and architects contribute to developing these tools. Architects can easily model their designs with computer technologies and even make them visible in the environment with augmented reality technologies. Also, it is thought that these technologies will become widespread in basic architectural education over time. This study conducted a practice at the undergraduate architecture level using augmented reality technology. Within the scope of the study, the predisposition of students who experience augmented reality technologies to new representation, gender, course period, familiarity with playing computer games, the effect of computer programs that they can use in their previous augmented reality experience and designs if any, and the correlation between them has been tried to be revealed with this study. In this context, a study was carried out with thirteen students in the architectural design studio. Students were expected to parametrically design indoor exhibition elements using Rhinoceros 3D software and the Grasshopper plugin in the study. Then, an experimental augmented reality study was conducted with the Fologram, in which the students transferred these virtual exhibition elements they designed to the real indoors and reshaped them according to the space. Afterwards, a questionnaire consisting of five independent and ten dependent variables was applied to the students. The survey results were analysed with the IBM SPSS Statistics program. According to the results obtained, significant results were determined between 4 independent variables and one dependent variable.
Publication
Symptom Based Health Status Prediction via Decision Tree, KNN, XGBoost, LDA, SVM, and Random Forest
(Springer Science and Business Media Deutschland GmbH, 2023) MERİÇ, ELİF; Özer, Çaǧdaş
Machine learning applications in health science become more important and necessary every day. With the help of these systems, the load of the medical staff will be lessened and faults because of a missing point, or tiredness will decrease. It should not be forgotten that the last decision lies with the professionals, and these systems will only help in decision-making. Predicting diseases with the help of machine learning algorithm can lessen the load of the medical staff. This paper proposes a machine learning model that analyzes healthcare data from a variety of diseases and shows the result from the best resulting algorithm in the model. It is aimed to have a system that facilitates the diagnosis of diseases caused by the density of data in the health field by using these algorithms of previously diagnosed symptoms, thus resulting in doctors going a faster way while diagnosing the disease and have a prediction about the diseases of people who do not have the condition to go to the hospital. In this way, it can ease the burden on health systems. The disease outcome corresponding to the 11 symptoms found in the data set used is previously experienced results. During the study, different ML algorithms such as Decision Tree, Random Forest, KNN, XGBoost, SVM, LDA were tried and compatibility/performance comparisons were made on the dataset used. The results are presented in a table. As a result of these comparisons and evaluations, it was seen that Random Forest Algorithm gave the best performance. While data was being processed, input parameters were provided to each model, and disease was taken as output. Within this limited resource, our model has reached an accuracy rate of 98%.
Publication
Exploring the Impact of Digitalized Learning and Teaching Systems on the Big Five Personality Traits
(Springer Science and Business Media Deutschland GmbH, 2023) Arslan, Ezgi Yıldırım; Yıldırım, Osman; KAYNAŞ, TAYFUN; Atanasov, Koycho
As information technologies develop, educational technology tools develop and differentiate in parallel. Effective and easily applicable technological learning methods have great effects on both learning styles and teaching styles and even transform them. Keeping in mind the contributions of learning technologies to the learning environment, this chapter aimed to examine the effects of flipped learning styles on students’ personality traits. For this purpose, research data were collected by applying a face-to-face survey to 362 higher education students who accepted voluntary participation, and the obtained data were evaluated and interpreted with the help of statistical analysis. According to the analysis findings, important relationships emerged between the sub-dimensions of the flipped learning sub-dimensions of a model known as the big five models. For example, a flexible environment was found to be explained by 12.9% of personality traits, conscientiousness, extraversion, and openness to experience dimensions. One aspect that unifies this research is that educators’ attention is drawn to the points where the development of information technologies forces them to go beyond the classical classroom face-to-face teaching methods.
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