Development of an Artificial Intelligence Based Computerized Adaptive Scale and Applicability Test (Trends in Data Engineering Methods for Intelligent Systems)
Yazarlar (1)
Prof. Dr. Mustafa YAĞCI Kırşehir Ahi Evran Üniversitesi, Türkiye
| Kitap Adı | Trends in Data Engineering Methods for Intelligent Systems | ||
| Bölüm(ler) | Development of an Artificial Intelligence Based Computerized Adaptive Scale and Applicability Test | ||
| Bölüm Sayfaları | 292-303 | ||
| Kitap Türü | Kitap Bölümü | ||
| Kitap Alt Türü | Alanında uluslararası yayınlanan kitap bölümü | ||
| Kitap Niteliği | Scopus indeksinde taranan bilimsel kitap | ||
| Kitap Dili | İngilizce | Basım Tarihi | 01-2021 |
| DOI Numarası | 10.1007/978-3-030-79357-9_29 | ISBN | ISSN: 2367-4512 ISSN (Electronic): 2367-4520 |
| Basıldığı Ülke | İspanya | Basıldığı Şehir | Barcelona |
| Kitap Linki | https://www.springer.com/series/15362 | ||
| Özet |
| The number of questions in the scales used to determine the attitudes of individuals is one of the biggest problems with this type of scale. Because the number of questions is high, individuals may be distracted, and their motivation may decrease. This has a negative effect on the reliability and validity of the scale. In this study, a decision tree algorithm with an artificial neural networks (ANN) model was developed to determine the learning approaches of students. Thus, the number of questions students will have to answer will be minimized. The research was conducted in two phases. In the first phase, the decision tree model was developed with the ANN J48 algorithm for the data obtained from the original form of the scale in a previous study by the researcher. This phase was carried out with 186 students. In the second phase, an artificial intelligence-based computerized adaptive scale (CAS) was designed by … |
| Anahtar Kelimeler |
| Artificial intelligence | Artificial neural networks | Computerized adaptive scale | Decision trees | Learning approaches |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Google Scholar | 1 |