In this study, it was aimed to predict elementary education teacher candidates’ achievements in “Science and Technology Education I and II” courses by using artificial neural networks. It was also aimed to show the independent variables importance in the prediction. In the data set used in this study, variables of gender, type of education, field of study in high school and transcript information of 14 courses including end-of-term letter grades were collected. The fact that the artificial neural network performance in this study was R=0.84 for the Science and Technology Education I course, and R=0.84 for the Science and Technology Education II course shows that the network performance overlaps with the findings obtained from the related studies.
Elementary Education Science and Technology Teaching Data Mining Artificial Neural Networks
In this study, it was aimed to predict
elementary education teacher candidates’ achievements in “Science and
Technology Education I and II” courses by using artificial neural networks. It
was also aimed to show the independent variables importance in the prediction.
In the data set used in this study, variables of gender, type of education,
field of study in high school and transcript information of 14 courses
including end-of-term letter grades were collected. The fact that the
artificial neural network performance in this study was R=0.84 for the Science
and Technology Education I course, and R=0.84 for the Science and Technology
Education II course shows that the network performance overlaps with the
findings obtained from the related studies.
Elementary Education Science and Technology Teaching Data Mining Artificial Neural Networks
Primary Language | English |
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Subjects | Studies on Education |
Journal Section | Articles |
Authors | |
Publication Date | September 19, 2018 |
Submission Date | April 16, 2018 |
Published in Issue | Year 2018 Volume: 5 Issue: 3 |