The overall objective of this study is to understand
how the fuzzy logic theory can be used in measuring the programming performance
of the undergraduate students, as well as proving the advantages of using fuzzy
logic in evaluation of students’ performance. 336 students were involved in the
sample of this quantitative study. The first group was consisted of 150 students,
whereas the second group was consisted of 186 students. Cluster analysis was also
conducted in order to ensure the neutrality of sample. The rule-based intelligent
fuzzy logic assessment logic (FLAL) system was developed. This system has a flexible
database in order to assess the academic programming performances of students. Therefore,
an absolute evaluation system was used in order to calculate the second group’s
performance. On the other hand, FLAL system was applied to the first group to determine
their programming performance. A Mamdani-type fuzzy logic algorithm mechanism having
two inputs and one output was utilized. An independent sample T test was used in
analyzing the data sets. As a result, there was a significant difference between
first and second groups’ results in favor of the first group. While 29 students comprised
of 19.3% of all the students failed in the flexible percentage system, 41 students comprised of
22% of all the students failed in the absolute evaluation system
evaluating
their grades via fuzzy logic system. By increasing the input
parameters of the fuzzy logic rules, the results can be addressed more efficiently.
Absolute evaluation system flexible percentage system fuzzy logic
The overall objective of this study is to understand how the fuzzy logic theory can be used in measuring the programming performance of the undergraduate students, as well as proving the advantages of using fuzzy logic in evaluation of students’ performance. 336 students were involved in the sample of this quantitative study. The first group was consisted of 150 students, whereas the second group was consisted of 186 students. Cluster analysis was also conducted in order to ensure the neutrality of sample. The rule-based intelligent fuzzy logic assessment logic (FLAL) system was developed. This system has a flexible database in order to assess the academic programming performances of students. Therefore, an absolute evaluation system was used in order to calculate the second group’s performance. On the other hand, FLAL system was applied to the first group to determine their programming performance. A Mamdani-type fuzzy logic algorithm mechanism having two inputs and one output was utilized. An independent sample T test was used in analyzing the data sets. As a result, there was a significant difference between first and second groups’ results in favor of the first group. While 29 students comprised of 19.3% of all the students failed in the flexible percentage system, 41 students comprised of 22% of all the students failed in the absolute evaluation system evaluating their grades via fuzzy logic system. By increasing the input parameters of the fuzzy logic rules, the results can be addressed more efficiently.
Absolute evaluation system Flexible percentage system Fuzzy logic Programming
Birincil Dil | İngilizce |
---|---|
Konular | Eğitim Üzerine Çalışmalar |
Bölüm | Makaleler |
Yazarlar | |
Yayımlanma Tarihi | 16 Aralık 2018 |
Gönderilme Tarihi | 31 Mayıs 2018 |
Yayımlandığı Sayı | Yıl 2018 |