Okuma Becerilerini Yordayan Özelliklerin Belirlenmesi: Genetik Algoritma Kestirimi
Öz
Anahtar Kelimeler
Kaynakça
- Adaba, H. (2016). Assessing factors affecting the students reading speed and comprehension: Manasibu secondary school grade nineth in focus: Western Wallagga Zone. International Journal of Language and Linguistics, 4(5), 165-182.
- Adams, M. J. (1990). Beginning to read: Thinking and learning about print. Cambridge: MIT Press.
- Ahmed, A. B. ve Elaraby, I. S. (2014). Data mining: A prediction for student's performance using classification method. World Journal of Computer Application and Technology, 2(2), 43-47.
- Altunkaynak, A. (2009). Sediment load prediction by genetic algorithms. Advances in Engineering Software, 40(9), 928-934.
- Bozkuş, K. (2021). Digital devices and student achievement: The relationship in PISA 2018 data. International Online Journal of Education and Teaching (IOJET), 8(3), 1560-1579.
- Brownlee, J. (2020). Data preparation for machine learning: Data cleaning, feature selection, and data transforms in Python. Machine Learning Mastery.
- Büyüköztürk, Ş., Çakmak, E. K., Akgün, Ö. E., Karadeniz, Ş. ve Demirel, F. (2014). Bilimsel araştırma yöntemleri (16. bs.). Ankara: Pegem.
- Carretti, B., Toffalini, E., Saponaro, C., Viola, F. ve Cornoldi, C. (2020). Text reading speed in a language with a shallow orthography benefits less from comprehension as reading ability matures. British Journal of Educational Psychology, 90(Suppl 1), 91-104.
Ayrıntılar
Birincil Dil
Türkçe
Konular
Alan Eğitimleri
Bölüm
Araştırma Makalesi
Yazarlar
Selahattin Gelbal
0000-0001-5181-7262
Türkiye
Yayımlanma Tarihi
28 Ocak 2022
Gönderilme Tarihi
1 Aralık 2021
Kabul Tarihi
6 Ocak 2022
Yayımlandığı Sayı
Yıl 2022 Cilt: 10 Sayı: 1
