Seda Göktepe Körpeoğlu
Biographic Data
| ID | 9635778 |
|---|---|
| NAME | Seda Göktepe Körpeoğlu |
| GIVEN NAMES | Seda Göktepe |
| FAMILY NAME | Körpeoğlu |
| SIGNATURE | KÖRPEOĞLU S G |
| AFFILIATIONS | Faculty of Chemical and Metallurgical Engineering, Department of Mathematical Engineering, Yildiz Technical University, İstanbul, Turkey |
| ORCID | 0000-0001-7146-0846 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
Using artificial intelligence to predict students’ STEM attitudes
Numerous artificial intelligence methods have lately been applied in education. This study proposes an Adaptive Neural-network-based Fuzzy Logic (ANFIS) model combining fuzzy logic and artificial neural networks for predicting students' STEM attitudes. The inputs of the research were determined as grade levels and academic achievement scores, and the output was determined as STEM attitudes. The hybrid optimisation method trained the fuzzy inferen…
Examination of Middle School Students’ Interests in Stem Professions Using Educational Data Mining
Araştırmanın amacı, ortaokul öğrencilerinin STEM mesleklerine olan ilgilerini veri madenciliği kullanarak incelemektir. Veri madenciliği son yıllarda eğitim de dâhil olmak üzere farklı alanlarda başarıyla kullanılan veri analizi yöntemlerinden birisidir. Bu çalışmada eğitsel veri madenciliği yöntemlerinden sınıflandırma analizi ve karar ağacı teknikleri kullanılmıştır. Araştırmanın örneklemini İstanbul'un çeşitli semtlerinde bulunan farklı sınıfl…
No prominent works on this page.
Examination of Middle School Students’ Interests in Stem Professions Using Educational Data Mining
Araştırmanın amacı, ortaokul öğrencilerinin STEM mesleklerine olan ilgilerini veri madenciliği kullanarak incelemektir. Veri madenciliği son yıllarda eğitim de dâhil olmak üzere farklı alanlarda başarıyla kullanılan veri analizi yöntemlerinden birisidir. Bu çalışmada eğitsel veri madenciliği yöntemlerinden sınıflandırma analizi ve karar ağacı teknikleri kullanılmıştır. Araştırmanın örneklemini İstanbul'un çeşitli semtlerinde bulunan farklı sınıfl…
Using artificial intelligence to predict students’ STEM attitudes
Numerous artificial intelligence methods have lately been applied in education. This study proposes an Adaptive Neural-network-based Fuzzy Logic (ANFIS) model combining fuzzy logic and artificial neural networks for predicting students' STEM attitudes. The inputs of the research were determined as grade levels and academic achievement scores, and the output was determined as STEM attitudes. The hybrid optimisation method trained the fuzzy inferen…
Mathematics (2 works) · Online Learning and Analytics (2 works) · Psychology (2 works) · Academic achievement (1 work) · Adaptive neuro fuzzy inference system (1 work) · Artificial Intelligence (1 work) · Artificial neural network (1 work) · Computational intelligence (1 work) · Computer Science (1 work) · Correlation (1 work)