A Practical, Iterative Framework for Secondary Data Analysis in Educational Research

Autor/in	Logan, Tracy
Titel	A Practical, Iterative Framework for Secondary Data Analysis in Educational Research
Quelle	In: Australian Educational Researcher, 47 (2020) 1, S.129-148 (20 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Logan, Tracy)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0311-6999
DOI	10.1007/s13384-019-00329-z
Schlagwörter	Data Analysis; Educational Research; Databases; Mathematics Education; Research Methodology; Guidelines; Decision Making + Suchen Sie Ihr Suchwort? Auswertung; Bildungsforschung; Pädagogische Forschung; Datenbank; Mathematische Bildung; Research method; Forschungsmethode; Richtlinien; Decision-making; Entscheidungsfindung
Abstract	Secondary data analysis in educational research has been an established research method for many years. Yet, few publications outline the "how to" of undertaking the process. This paper presents an analysis framework suitable for undertaking secondary data analysis within the field of education. The framework is a modification and an application of a pre-existing data mining research process known as Knowledge Discovery in Databases (KDD). The KDD process is interactive and generative and involves a series of sequential steps and decision-making processes. The modified KDD process is described to show how it supports secondary data analysis and provides an example of how the modified KDD process was applied across a secondary analysis in mathematics education. This paper provides educational researchers with a practical and iterative framework through which to undertake secondary analysis that enhances flexibility and encourages depth and saturation. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2022/1/01