Every Rose Has Its Thorn: Secondary Teachers' Reasoning about Statistical Models

Autor/inn/en	Justice, Nicola; Zieffler, Andrew; Huberty, Michael D.; delMas, Robert
Titel	Every Rose Has Its Thorn: Secondary Teachers' Reasoning about Statistical Models
Quelle	In: ZDM: The International Journal on Mathematics Education, 50 (2018) 7, S.1253-1265 (13 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Justice, Nicola)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1863-9690
DOI	10.1007/s11858-018-0953-1
Schlagwörter	Statistics; Secondary School Teachers; Teacher Attitudes; Teacher Role; Mathematics Instruction; Problem Solving; Inferences; Thinking Skills; Simulation; Introductory Courses; Decision Making; Data Collection; Mathematical Models + Suchen Sie Ihr Suchwort? Statistik; Lehrerverhalten; Lehrerrolle; Mathematics lessons; Mathematikunterricht; Problemlösen; Inference; Inferenz; Denkfähigkeit; Simulation program; Simulationsprogramm; Einführungskurs; Decision-making; Entscheidungsfindung; Data capture; Datensammlung; Mathematical model; Mathematisches Modell
Abstract	Statistical modeling is a core component of statistical thinking and has been identified by several countries as a curricular goal for secondary education. However, many secondary teachers have minimal preparation for teaching this topic. The goal of this research study is to learn about teachers' perceptions of the role statistical models play in statistical inference and how these perceived purposes affect their reasoning about statistical models and inference. Problem-solving interviews were conducted with four in-service teachers who had recently taught a modeling and simulation-based introductory statistics course. Teachers' responses suggest they may not see modeling variation as the primary purpose of statistical modeling and instead substitute two other purposes: making a decision and replicating the data collection process. Suggestions for how to build on teachers' transitional conceptions and refocus attention on modeling variation are discussed. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01