Modeling Course Achievements of Elementary Education Teacher Candidates with Artificial Neural Networks

Autor/inn/en	Akgün, Ergün; Demir, Metin
Titel	Modeling Course Achievements of Elementary Education Teacher Candidates with Artificial Neural Networks
Quelle	5 (2018) 3, S.491-509 (19 Seiten)Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Verfügbarkeit
Zusatzinformation	ORCID (Akgün, Ergün)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	2148-7456
Schlagwörter	Elementary School Teachers; Preservice Teachers; Artificial Intelligence; Science Education; Technology Education; Gender Differences; Intellectual Disciplines; Student Records; Grades (Scholastic); Foreign Countries; Academic Achievement; Research Methodology; Turkey + Suchen Sie Ihr Suchwort? Elementary school; Teacher; Teachers; Grundschule; Volksschule; Lehrer; Lehrerin; Lehrende; Künstliche Intelligenz; Naturwissenschaftliche Bildung; Technisch-naturwissenschaftlicher Unterricht; Geschlechterkonflikt; Geisteswissenschaften; Schülerakte; Notenspiegel; Ausland; Schulleistung; Research method; Forschungsmethode; Türkei
Abstract	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. (As Provided).
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01