| Yazarlar |
Prof. Dr. Mustafa YAĞCI
Kırşehir Ahi Evran Üniversitesi, Türkiye |
| 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 using the decision tree model developed. Then, CAS and the original scale were applied to a different group of students (113 students) from the first phase, and the relationship between these two was investigated. The results of the research are very promising. Students’ learning approach preferences were estimated with very high reliability dand accuracy with only a few questions. 95.7% accuracy was achieved with very few questions. According to this result, it can be said that the validity and reliability of the scale developed by the decision tree algorithm is quite high. In addition, it was observed that all participants filled in the scale with great care as it required very few items. This is another factor that increases the reliability of the scale. |
| Anahtar Kelimeler |
| Artificial intelligence | Artificial neural networks | Computerized adaptive scale | Decision trees | Learning approaches |
| Kitap Adı | Trends in Data Engineering Methods for Intelligent Systems |
| Bölüm(ler) | Development of an Artificial Intelligence Based Computerized Adaptive Scale and Applicability Test |
| Kitap Türü | Kitap Bölümü |
| Kitap Alt Türü | Alanında uluslararası yayımlanan kitap bölümü |
| Kitap Niteliği | Scopus indeksinde taranan bilimsel kitap |
| Kitap Dili | İngilizce |
| Basım Tarihi | 01-2021 |
| ISBN | ISSN: 2367-4512 ISSN (Electronic): 2367-4520 |
| Basıldığı Ülke | İspanya |
| Basıldığı Şehir | Barcelona |
| Atıf Sayıları |
