2016
DOI: 10.3390/educsci7010003
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How the Mastery Rubric for Statistical Literacy Can Generate Actionable Evidence about Statistical and Quantitative Learning Outcomes

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… Show more

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Cited by 19 publications
(35 citation statements)
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“…Because we were interested in students’ perceptions of their skill level, we used a modified mastery rubric rather than the “confidence” scale rating system. Our modified mastery rubric ( Appendix 4 ) articulates a developmental trajectory with explicit criteria describing each stage ( 25 , 26 ). Students completed the Personal Skills rating in Lab 1 (Pre) and Lab 12 (Post).…”
Section: Methodsmentioning
confidence: 99%
“…Because we were interested in students’ perceptions of their skill level, we used a modified mastery rubric rather than the “confidence” scale rating system. Our modified mastery rubric ( Appendix 4 ) articulates a developmental trajectory with explicit criteria describing each stage ( 25 , 26 ). Students completed the Personal Skills rating in Lab 1 (Pre) and Lab 12 (Post).…”
Section: Methodsmentioning
confidence: 99%
“…Mastery Rubrics have been published for clinical research [16], ethical reasoning [17], evidence-based medicine [18], and statistical literacy [19]. The construct is described in detail by [15].…”
Section: A Developmental Path For Stewardshipmentioning
confidence: 99%
“…A CTA generated KSAs following the procedure described in the Supplementary Materials (S2). KSAs that characterize the scientific method, reflecting what is requisite in scientific work (derived from [44] and [45], and adapted by [46]), were assumed to be essential to bioinformatics education and training [47]. These KSAs were refined with respect to community-derived competencies.…”
Section: Ksa Derivation Via Cognitive Task Analysismentioning
confidence: 99%
“…This KSA supports the definition of a bioinformatician as a scientist who uses computational resources to address fundamental questions in biology [55]; [56] -i.e., it is intended to promote the bioinformatician's ability to solve biological problems. It also derives implicitly from the competencies, and explicitly from the Wild & Pfannkuch (1999) [44] model of scientific reasoning (and highlighted in [46]). Hypothesis generation also emerged from the CTA by appeal to theoretical and empirical scientificreasoning models.…”
Section: Ethical Practicementioning
confidence: 99%