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Data mining is one of the important and beneficial technological developments in education and its usage area is becoming widespread day by day as it includes applications that contribute positively to teaching activities. By making raw data in the field of education meaningful using data mining techniques, teaching activities can be made more effective and efficient. Studies carried out in the field of education between 2014-2020 with data mining methods were scanned from the "Science Direct" database. As a result of scanning studies, 60 papers were found to be directly related to data mining in education. The studies include issues such as the development of e-learning systems, pedagogical support, clustering of educational data, and student performance predictions. These selected articles were analyzed in terms of purpose, application area, method, and contribution to the literature. This study aims to group the studies conducted in the field of education using the data mining method under certain headings, evaluate the methods and goals and present the need in this field to the researchers who will work in this field.

The aim of this study is to present a model proposal on determining the student participation rate in synchronous courses given in Learning Management Systems (LMS). Especially in situations where equal opportunities cannot be provided or opportunities are limited, distance education provides benefits for learning anytime and anywhere (ubiquitous learning) with the support of educational technologies. When the literature is examined, thanks to distance education; It is seen that it offers a very advantageous teaching environment in terms of location, time, convenience in accessing the resources needed and cost-benefit. However, when the literature is analyzed, it is found that there is a problem in determining the participation levels and rates of students in the Learning Management Systems used in distance education. Students access the activity or course in LMS using text-based user information and passwords. Unfortunately, it is not possible to determine with the current LMS whether the participant is the real responsible person or he/she is actively/synchronously following the course. In this context, a design model has been presented using face recognition algorithms to determine attendance in distance education, to ensure more active participation and to increase success indirectly. In the proposed model, tests were made using special filters for image processing, and in cases where the number of samples was increased, more than 80% accuracy was provided. The proposed design model was developed in Visual Studio.Net platform and coded on C# programming language. SQL server is used as database management system and EmguCV library is used for the image processing stages.

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Insects are a class of the arthropod branch and the most crowded animal group in terms of species and taxonomy. Due to destruction and forest fires, some insect species could go extinct without being detected. Identifying new insects and having knowledge about insects in terms of biodiversity will contribute positively to the studies carried out, especially in entomology, agriculture, the pharmaceutical industry, medicine, robotics, and other branches. In this study, we produced a mobile-based decision support software with a deep learning model to classify and detect insects at the order level. We also presented the comparative analysis results of SSD MobileNET, YoloV4, and Faster R-CNN InceptionV3 deep learning methods and adapting processes for order-level insect classification. Our approach studies the suitability of existing models towards such an objective, and we conclude that Faster R-CNN InceptionV3 performs the best at classifying and detecting insects at the order level. In addition, we shared 25820 training and 1500 test data in the kaggle database in order to contribute studies to be carried out in this area. As a result, we believe that this research will be beneficial to entomologists, naturalists, and other researchers in related fields.

In this study, it is aimed to provide an opportunity to integrate applications made with virtual reality and augmented reality technologies for the Zeus temple of the ancient city of Aizanoi in Çavdarhisar district of Kütahya province in a way that can be used in the field of tourism and to travel with a digital platform. In the study, augmented reality and virtual reality technologies and model applications for the tourism sector were carried out. Another importance of the research is the presentation of the first augmented reality and virtual reality applications made for the temple of Zeus in the ancient city of Aizanoi in the province of Kütahya. In the study, two different augmented reality applications were made using Marker-based augmented reality (Marker-based augmented reality) techniques, namely visual target recognition and ground plane recognition applications. A gold collection game has been made for virtual reality technology as a desktop navigation application, a web-based application, and a gamification application. In addition, a virtual reality application designed to be used with Cardboard-type glasses was also presented in the study. In accordance with the study, it was seen that augmented reality and virtual reality technology can be used effectively and efficiently in the field of tourism, and there is a need for applications to be made in this field. Promotion of the technologies used in the field of tourism, obtaining ideas before the trip, getting to know the environment, etc. it is expected that it will offer many advantages such as and will also provide benefits from an economic point of view.