Ortak Seçmeli Derslerdeki Tercihlerin İstatistiksel Analizi ve Tespiti

Mehmet Vural, Mehmet Kaplan
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引用次数: 1

Abstract

gelişmeler istatistiksel seçilip seçilmemesine olarak güncellenerek eklenmesi önlenecektir. ekleme yöntemi ile seçilen tekrar müfredata konulacak ancak seçilmemiş müfredattan kaldırılacaktır. Sonuç olarak, çalışmanın önemli direği müfredatın güncellenmesidir. güncelleme çok tercih edilen derslerin listelenmesi öngörü sistemine dönüştürülmesi hedeflenmektedir. İstatistiksel ABSTRACT This study aimed to make logical inferences and optimize the system using statistical data to determine the Common Elective Course preferences of Mersin University students. Possible developments in the curriculum were foreseen, taking into consideration the data affecting course preferences. Simulation results were tested by administering questionnaires to students. As a result of the statistical analysis conducted using the dataset, the preference structures of the courses found for the curriculum were determined according to the faculties and departments. The new semester curriculum with the derived data will be updated again depending on whether the courses are selected. The courses selected by the addition course method will be placed in the curriculum once more. However, unselected courses will be removed from the curriculum. Thus, the most important aspect of this study is the updating of the curriculum. With this update, the aim is to list the most preferred courses and turn them into a consultant foresight system. Per the statistical analysis, although the preferences of each faculty differed from each other, there were general similarities in the courses chosen. According to the test results, it was concluded that 55% of the courses should be added to the curriculum, 23% should be removed, and the remaining 22% should be rearranged.
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这些数据是通过统计分析得出的。在此基础上,该系统还提供了更多的功能。ABSTRACT This study aimed to make logical inferences and optimize the system using statistical data to determine the Common Elective Course preferences of Mersin University students.考虑到影响课程偏好的数据,对课程的可能发展进行了预测。通过向学生发放调查问卷,对模拟结果进行了检验。通过对数据集进行统计分析,根据院系确定了课程设置中的课程偏好结构。新学期的课程设置将根据课程是否被选中而再次更新。通过加选课程法选中的课程将再次放入课程表中。但是,未被选中的课程将从课程表中删除。因此,本研究最重要的方面是更新课程表。此次更新的目的是列出最受青睐的课程,并将其转化为顾问预测系统。根据统计分析,尽管各学院的偏好各不相同,但所选课程大体相似。根据测试结果,得出的结论是,55% 的课程应添加到课程中,23% 的课程应删除,其余 22% 的课程应重新安排。
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