Data-Based Decision-Making for School Improvement: Research Insights and Gaps

Autor/in	Schildkamp, Kim
Titel	Data-Based Decision-Making for School Improvement: Research Insights and Gaps
Quelle	In: Educational Research, 61 (2019) 3, S.257-273 (17 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Schildkamp, Kim)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0013-1881
DOI	10.1080/00131881.2019.1625716
Schlagwörter	Data Use; School Effectiveness; Educational Improvement; Formative Evaluation; Barriers; Information Literacy; Data Collection; Goal Orientation; Data Interpretation; Educational Quality; Evidence Based Practice; Educational Research + Suchen Sie Ihr Suchwort? Schuleffizienz; Teaching improvement; Unterrichtsentwicklung; Informationskompetenz; Data capture; Datensammlung; Zielorientierung; Zielvorstellung; Data evaluation; Datenauswertung; Quality of education; Bildungsqualität; Bildungsforschung; Pädagogische Forschung
Abstract	Background: Data-based decision-making in education often focuses on the use of summative assessment data in order to bring about improvements in student achievement. However, many other sources of evidence are available across a wide range of indicators. There is potential for school leaders, teachers and students to use these diverse sources more fully to support their work on a range of school improvement goals. Purpose and sources of evidence: To explore data-based decision-making for school improvement, this theoretical paper discusses recent research and literature from different areas of data use in education. These areas include the use of formative assessment data, educational research study findings and 'big data'. In particular, the discussion focuses on how school leaders and teachers can use different sources of data to improve the quality of education. Main argument: Based on the literature reviewed, an iterative model of data use for school improvement is described, consisting of defining goals for data use, collecting different types of data or evidence (e.g. formal data, informal data, research evidence and 'big data'), sense-making, taking improvement actions and evaluation. Drawing on the literature, research insights are discussed for each of these components, as well as identification of the research gaps that still exist. It is noted that the process of data use does not happen in isolation: data use is influenced by system, organisation and team/individual level factors. Conclusions: When it comes to using data to improve the quality of teaching and learning, it is evident that some of the most important enablers and barriers include data literacy and leadership. However, what is less well understood is how we can promote the enablers and remove the barriers to unlock, more fully, the potential of data use. Only then can data use lead to sustainable school improvement. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01