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Educ. Sci. 2017, 7(1), 3; doi:10.3390/educsci7010003

How the Mastery Rubric for Statistical Literacy Can Generate Actionable Evidence about Statistical and Quantitative Learning Outcomes

Collaborative for Research on Outcomes and Metrics; Departments of Neurology; Biostatistics, Bioinformatics & Biomathematics and Rehabilitation Medicine, Georgetown University Medical Center, Suite 207 Building D, 4000 Reservoir Road NW, Washington, DC 20057, USA
Academic Editor: James Albright
Received: 7 July 2016 / Revised: 19 October 2016 / Accepted: 12 December 2016 / Published: 24 December 2016
(This article belongs to the Special Issue Consequential Assessment of Student Learning)
View Full-Text   |   Download PDF [248 KB, uploaded 24 December 2016]

Abstract

Statistical literacy is essential to an informed citizenry; and two emerging trends highlight a growing need for training that achieves this literacy. The first trend is towards “big” data: while automated analyses can exploit massive amounts of data, the interpretation—and possibly more importantly, the replication—of results are challenging without adequate statistical literacy. The second trend is that science and scientific publishing are struggling with insufficient/inappropriate statistical reasoning in writing, reviewing, and editing. This paper describes a model for statistical literacy (SL) and its development that can support modern scientific practice. An established curriculum development and evaluation tool—the Mastery Rubric—is integrated with a new, developmental, model of statistical literacy that reflects the complexity of reasoning and habits of mind that scientists need to cultivate in order to recognize, choose, and interpret statistical methods. This developmental model provides actionable evidence, and explicit opportunities for consequential assessment that serves students, instructors, developers/reviewers/accreditors of a curriculum, and institutions. By supporting the enrichment, rather than increasing the amount, of statistical training in the basic and life sciences, this approach supports curriculum development, evaluation, and delivery to promote statistical literacy for students and a collective quantitative proficiency more broadly. View Full-Text
Keywords: statistical literacy; mastery rubric; collective quantitative proficiency; basic sciences; life sciences; scientific practice; curriculum development; curriculum evaluation; actionable evidence statistical literacy; mastery rubric; collective quantitative proficiency; basic sciences; life sciences; scientific practice; curriculum development; curriculum evaluation; actionable evidence
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Tractenberg, R.E. How the Mastery Rubric for Statistical Literacy Can Generate Actionable Evidence about Statistical and Quantitative Learning Outcomes. Educ. Sci. 2017, 7, 3.

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