In this study, a student-based placement model using the A* algorithm is proposed and applied to solve the problem of placing the courses in exam sessions. The application area of the model is midterm and final exams, conducted by the Open Education Faculty. The reason for choosing open education exams for the practice is that the exams are applied across the country and more than 100,000 students participate. The main problem is to obtain a suitable distribution that can satisfy many constraints simultaneously. In the current system, the lessons in the sessions were placed once using the curriculum knowledge. This placement plan is applied in all exams. When the placement is done according to the curriculum information, the courses in the sessions cannot be placed effectively and efficiently due to a large number of common courses and the large number of students taking the exam. This makes the booklets more expensive and the organization more prone to errors. Both the opening of new programs and the increase in the number of students regularly lead to the necessity of placing the classes in sessions dynamically each semester. In addition, to prevent conflicts with the calendars of other central exams, it is necessary to conduct all exams in three sessions. A better solution was obtained by using a different model than the currently used model in the study. With this solution, distribution of the courses of successful students with few courses to all sessions is provided, and difficult courses of unsuccessful students who have a large number of courses were gathered in the same session. This study can support future studies on two issues: the first issue is the approach of using the course that will be taken by most students instead of the courses taught in most departments in the selection of the course to be placed in the booklet. The second issue is to try to find the most suitable solution by performing performance tests on many algorithms whose performance has been determined by many academic studies.
Bu çalışmanın amacı Açıköğretim Fakülteleri için gerçekleştirilen sınavlarda kullanılan kitapçıklardaki ders tekrarlarını azaltarak, toplamda üretilen farklı kitapçık sayısını düşürmektir. Bu şekilde baskı maliyetlerini ve işlem karmaşıklığını azaltarak işlem süresini ve bu süreçteki olası hataların azaltılması hedeflenmektedir. Kitapçıklara dersler tanımlanırken, derslere ilişkin sınavların hangi oturumlarda yapılacağı bilgisi ile öğrenci ders alma bilgisi kullanılmaktadır. Diğer taraftan herhangi bir öğrencinin tüm derslerinin bir kitapçıkta bulunması ve bir kitapçıkta en fazla 15 ders bulunması kısıtlarına uyulmaktadır. Kitapçıklara ders ataması probleminin çözümü için A* algoritması kullanılmıştır. İlk kitapçığa ilk ders ataması yapılırken öğrenci ders alma bilgisi kullanılmış ve en fazla öğrenci tarafından alınan ders ilk kitapçığa yerleştirilmiştir. Kitapçıkta yer alacak diğer tüm derslerin seçiminde ise seçilecek dersle birlikte kitapçıktaki derslerden başka dersi kalmayan öğrenci sayısının maksimum olması hedeflenmiştir. Çalışma öncesi durumda, üç oturumda gerçekleştirilen sınavlar için 1. oturumda 18, 2. Oturumda 18 ve 3. Oturumda 8 olmak üzere toplamda 44 adet farklı kitapçık bulunmaktadır. Çalışma sonucunda ise toplamda 24 tür kitapçık üretilmiştir. Tekrar eden ders sayısı artmasına rağmen kitapçık sayısı nerdeyse yarı yarıya azaltılabilmiştir.
The aim of this study is to investigate the factors that affect the preference of e-learning systems used as a basic or supportive tool in both open education and formal education. The data set used in this study was obtained from a questionnaire applied to randomly selected university students who took courses with the e-learning system. The questionnaire was applied to 561 people and descriptive statistics were calculated based on the obtained data. For modeling and analyzing the relationships of the factors that directly and indirectly affect the preference of e-learning systems, Structural Equation Modeling was established. As a result of the analysis, the variables that directly or indirectly affect the preferability of the e-learning systems were determined. In addition to the positive effect of the information system infrastructure on other variables in the model, the mediation effect of the learning management system on the information system infrastructure and preferability was revealed.
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