The aim of educational system which changes according to the enhancements in educational technology is to make students more active in the learning process, as well as make them as people who have skills such as critical thinking, problem solving etc. Critical thinking is a thinking skill which consists of mental processes of discernment, analysis and evaluation. Blended Learning is learning which combines online and face-to-face approaches. By means of online discussion forms, teachers can monitor the class discussions. These discussions help teachers identify topics that need clarification or that have captured the interest of students, and they can use the insights gained by them to structure class time. Also, if teacher use the Web discussion area to address some of the more straightforward student questions, they can make better use of class time. In this sense, the purpose of this study is to examine the effects of blended learning environment which supports the course management system on the critical thinking skills of students. The model of the study is pre-test, post-test single group model. There are 44 Students who attending the course of Design And Use Of Instructional Material in the Department of Computer and Instructional Technology Education of Ankara University in third grade who constitute the study group. In this study, Watson-Glaser Critical Thinking Appraisal Test, which consists of 100 items, was used to collect data. This test is composed of a series of test exercises in which the application of the important abilities in the critical thinking is involved. This test includes five sub-tests which are listed as; Inference, Recognition of Assumption, Deduction, Interpretation, Evaluation of Arguments. The test was developed in 1964 by Googwin Watson ve Edward M. Glaser. The test was translated into Turkish by Assoc. Prof. Dr. Nükhet Çıkrıkçı – Demirtaşlı in 1996. Analysis results indicated that the range of internal consistency of the subscales are interval from .20 to .47 and the total correlation coefficient is .63. The course consists of 5 weeks throughout the semester. At the beginning of the semester, student’ WGCTA scores were obtained. In the environment of blended learning, the course is supported to chat rooms and forums. After 5 weeks, students were asked to do the test again and the critical skills of the students were examined. The data was analyzed through paired sample t-test to compare the results of pre-test post-test scores, as well as descriptive statistics. There was no significant difference between pre-tets and post-test results.

Siber güvenlik, bilgi kaynaklarının korunmasını ve kişinin kendisi de dahil olmak üzere diğer varlıkların korunmasını kapsamaktadır. Bu çalışmada, bilişim teknolojileri ile ilgili bir bölümde öğrenim gören üniversite öğrencilerinin siber güvenlik davranışları farklı değişkenler açısından incelenmiştir. Çalışma gurubunu bir devlet, bir vakıf üniversitesinin Bilgisayar Mühendisliği ile Bilgisayar ve Öğretim Teknolojileri Öğretmenliği (BÖTE) bölümlerinde öğrenim gören toplam 170 öğrenci oluşturmaktadır. Verilerin toplanmasında Siber Güvenlik Ölçeği (SGÖ) kullanılmıştır. Çalışmanın sonuçlarına göre öğrencilerin siber güvenliğe yönelik davranışlarının siber güvenliği sağlayacak düzeyde olduğu görülmektedir. Faktörlere göre daha ayrıntılı bir inceleme yapıldığında, öğrenciler kişisel gizliliklerini koruyabilmektedirler. Ayrıca güvenilmeyen uygulamalardan kaçınmakta ve güvenlik için önlem alabilmektedirler. Bunun yanı sıra kredi kartı veya banka kartı gibi ödeme bilgilerini koruyabilmekte ve İnternet üzerinde gezinirken arkalarında iz bırakmamaktadırlar. Erkek ve kızların siber güvenlik davranışları arasında anlamlı bir farklılık yoktur. Kişisel güvenliği koruma faktörü açısından BÖTE bölümünde kızlar, Bilgisayar Mühendisliği bölümünde ise erkekler daha olumlu siber güvenlik davranışına sahiptirler. İnternet-bilgisayar güvenlik eğitimi alan veya bu konuda iş deneyimi olan öğrencilerin siber güvenlik davranışları daha olumludur. Farklı sınıflarda öğrenim gören öğrencilerin siber güvenlik davranışları arasında anlamlı bir farklılık bulunmamaktadır. Meslek lisesinden mezun olan öğrencilerin iz bırakmama faktörü açısından genel/düz liseden mezun olan öğrencilere göre daha dikkatli oldukları görülmektedir.

En tr In this study, synchronous virtual classroom software used in online learning environments was examined. In this literature review study, first, virtual classroom software was described and its features were stated. Then, areas of virtual classroom software use were mentioned. After that, advantages and disadvantages of virtual classroom software were expressed and commonly used virtual classroom software such as Adobe Connect, Perculus, Blackboard, WizIQ, GoToTraining, Electa, OpenMeetings and Big Blue Button was introduced. Finally, virtual classroom software was compared with regards to some features like licensing, sharing, video playing, remote control and supporting Turkish language packet. After the comparison, it was found that software has some advantages and disadvantages relative to each other. However, it was seen that all of them have basic features. It is expected that this study will contribute to institutions and users delivering online distance education about what a virtual classroom is and selecting virtual classroom software in line with their needs. Bu çalışmada çevrim içi öğrenme ortamlarında kullanılan eş zamanlı sanal sınıf yazılımları incelenmiştir. Alanyazın taraması yöntemi benimsenen çalışmada, öncelikle sanal sınıf yazılımının tanımı yapılmış ve özellikleri ifade edilmiştir. Ardından sanal sınıf yazılımlarının kullanım alanlarından bahsedilmiştir. Sonra sanal sınıf yazılımlarının yararları ve sınırlılıkları dile getirilmiş ve yaygın olarak kullanılan sanal sınıf yazılımları olan Adobe Connect, Perculus, Blackboard, WizIQ, GoToTraining, Electa, OpenMeetings ve Big Blue Button tanıtılmıştır. Son bölümde ise sanal sınıf yazılımları; lisanslama seçeneği, paylaşım seçeneği, video oynatma, uzaktan kontrol ve Türkçe dil desteği gibi özellikler açısından karşılaştırılmıştır. Karşılaştırmadan sonra yazılımların birbirlerine göre üstünlükleri ve sınırlılıkları olduğu bulunmuştur. Bunula birlikte bütün yazılımların temel özelliklere sahip oldukları görülmüştür. Gerçekleştirilen bu çalışmanın çevrim içi uzaktan eğitim veren kurumların ve bireylerin sanal sınıf yazılımları hakkında bilgi sahibi olmalarına ve ihtiyaçları doğrultusunda kullanacakları sanal sınıf yazılımını seçebilmelerine katkı sağlayacağı umulmaktadır.

The demand for secure, accurate, and reliable identification of individuals using facial recognition has attracted considerable interest in education, security, and many other sectors, not limited because it is robust, secure, and authentic. Recently, the demand for distance learning has increased dramatically. This increase is due to various barriers to learning that arise from enforced conditions such as seclusion and social distancing. Facial feature extraction in distance education is valuable in supporting face authenticity as it prevents the position of participants from changing, especially during the examination phase. In the field of face recognition, there is a mismatch between research and practical application. In this paper, we present a novel but highly efficient Deep Learning model for improving face recognition and registration in distance education. The technique is based on a combination of sequential and residual identity blocking. This makes it possible to evaluate the effectiveness of using deeper blocks than other models. The new model has proven to be able to extract features from faces in a high and accurate manner in compared with other state-of-the-art methods. In registration processing, there are several challenges related to training data limitation, face recognition, and verification. We present a new architecture for face recognition and registration. Experiments have shown that our registration model is capable of recognizing almost all faces and registering the corresponding labels.

The present study investigated the effect of metacognitive guidance in an online learning environment on the students' critical thinking competency. The research was carried out using experimental design with pretest-posttest control groups. The research group of the study consisted of 60 students studying at Computer and Educational Teaching Department of Educational Sciences Faculty at Ankara University during the fall semester of 2011-2012. The 51 point California Critical Thinking Disposition Inventory was used to collect pretest-posttest data. In terms of total score of critical thinking tendency, the average score of the group that received critical guidance was found to be higher than the score of the control group. The metacognitive guidance offered to the students in the online learning environment has affected their critical thinking tendency in a positive way. Findings indicate that metacognitive guidance in online learning environments can be an effective tool in developing critical thinking among preservice teachers.

The chest Computer Tomography (CT scan) is used in the diagnosis of coronavirus disease 2019 (COVID-19) and is an important complement to the Reverse Transcription Polymerase Chain Reaction (RT-PCR) test. The paper aims to improve the radiological diagnosis in the case of coronavirus disease COVID-19 pneumonia on forms of noninvasive approaches with conventional and high-resolution computer tomography (HRCT) scan images upon chest CT images of patients confirmed with mild to severe findings. The preliminary study is to compare the radiological findings of COVID-19 pneumonia in conventional chest CT images with images processed by a new tool and reviewed by expert radiologists. The researchers used a new filter called Golden Key Tool (GK-Tool) which has confirmed the improvement in the quality and diagnostic efficacy of images acquired using our modified images. Further, Convolution Neural Networks (CNNs) architecture called VGG face was used to classify chest CT images. The classification has been performed by using VGG face on various datasets which are considered as a protocol to diagnose COVID-19, Non-COVID-19 (other lung diseases), and normal cases (no findings on chest CT). Accordingly, the performance evaluation of the GK-Tool was fairly good as shown in the first set of results, where 8095 of participants show a good to excellent assessment of the new images view in the case of COVID-19 patients. The results, in general, illustrate good recognition rates in the diagnosis and, therefore, would be significantly higher in normal cases with COVID-19. These results could reduce the radiologists workload burden and play a major role in the decision-making process.