A CFBPN Artificial Neural Network Model for Educational Qualitative Data Analyses: Example of Students' Attitudes Based on Kellerts' Typologies

Autor/inn/en	Yorek, Nurettin; Ugulu, Ilker
Titel	A CFBPN Artificial Neural Network Model for Educational Qualitative Data Analyses: Example of Students' Attitudes Based on Kellerts' Typologies
Quelle	In: Educational Research and Reviews, 10 (2015) 18, S.2606-2616 (11 Seiten) PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1990-3839
Schlagwörter	Student Attitudes; Classification; Qualitative Research; Networks; Concept Formation; Tests; Educational Research; Models; Participant Characteristics; Artificial Intelligence; Statistical Analysis; Interviews; Biology; Foreign Countries; High School Students; Scientific Concepts; Turkey + Suchen Sie Ihr Suchwort? Schülerverhalten; Classification system; Klassifikation; Klassifikationssystem; Qualitative Forschung; Concept learning; Begriffsbildung; Examination; Prüfung; Examen; Bildungsforschung; Pädagogische Forschung; Analogiemodell; Künstliche Intelligenz; Statistische Analyse; Interviewing; Interviewtechnik; Biologie; Ausland; High school; High schools; Student; Students; Oberschule; Schüler; Schülerin; Studentin; Türkei
Abstract	In this study, artificial neural networks are suggested as a model that can be "trained" to yield qualitative results out of a huge amount of categorical data. It can be said that this is a new approach applied in educational qualitative data analysis. In this direction, a cascade-forward back-propagation neural network (CFBPN) model was developed to analyze categorical data for determine students' attitudes. The data were collected using a conceptual understanding test which includes open-ended questions. The results of this study indicate that using CFBPN model in analyzing data from educational research examining attitudes, behaviors, or beliefs may help us obtain more detailed information about the data analyzed and hence about the characteristics of the participants involved. (As Provided).
Anmerkungen	Academic Journals. e-mail: err@academic.journals.org; e-mail: service@academicjournals.org; Web site: http://academicjournals.org/journal/ERR
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01