Can We Make Definite Categorization of Student Attitudes? A Rough Set Approach to Investigate Students' Implicit Attitudinal Typologies toward Living Things

Autor/inn/en	Narli, Serkan; Yorek, Nurettin; Sahin, Mehmet; Usak, Muhammet
Titel	Can We Make Definite Categorization of Student Attitudes? A Rough Set Approach to Investigate Students' Implicit Attitudinal Typologies toward Living Things
Quelle	In: Journal of Science Education and Technology, 19 (2010) 5, S.456-469 (14 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1059-0145
DOI	10.1007/s10956-010-9213-z
Schlagwörter	Student Attitudes; Data Analysis; High School Students; Classification; Attitude Measures; Student Characteristics; Wildlife; Biology + Suchen Sie Ihr Suchwort? Schülerverhalten; Auswertung; High school; High schools; Student; Students; Oberschule; Schüler; Schülerin; Studentin; Classification system; Klassifikation; Klassifikationssystem; Biologie
Abstract	This study investigates the possibility of analyzing educational data using the theory of rough sets which is mostly employed in the fields of data analysis and data mining. Data were collected using an open-ended conceptual understanding test of the living things administered to first-year high school students. The responses of randomly selected 60 students among the participants were analyzed using rough set approach on the basis of "nine attitudinal typologies toward wildlife" defined by Kellert (1996). Student responses were tabulated to be used in rough sets and upper and lower approximation analyses were carried out. Students were found to display the characteristics of four out of nine typologies. Analyses revealed that some students who possessed characteristics of a certain typology may partially display the characteristics of other typologies and these typologies could be determined using rough set theory. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10