The Mastery Rubric for Evidence-Based Medicine: Institutional Validation via Multidimensional Scaling

Tractenberg, Rochelle E.; Gushta, Matthew; Weinfeld, Jeffrey M.

doi:10.1080/10401334.2016.1146599

Cited by 11 publications

(15 citation statements)

References 11 publications

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“…Related to the Mastery Rubric is the concept of a "learning progression" (e.g., [39] (p. 1)) which describes shifts from naïve to "more expert understanding" and is based on how children learn the concepts of interest (but see [40] for an example with law students). Whereas a learning progression represents a curricular segment (e.g., Schwarz et al 2009 [41]), the Mastery Rubric [37,42,43] represents the entire (predominantly) post-baccalaureate curriculum. Like the Mastery Rubric for Statistical Literacy (MR-SL, Table 2), two others were designed to capture and encourage development throughout the career [42,43].…”

Section: The Mastery Rubricmentioning

confidence: 99%

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

Tractenberg

2016

Education Sciences

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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.

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Section: The Mastery Rubricmentioning

confidence: 99%

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

Tractenberg

2016

Education Sciences

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“…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%

The preparation of stewards with the Mastery Rubric for Stewardship: Re-envisioning the formation of scholars and practitioners

Rios¹,

Golde²,

Tractenberg³

2019

Preprint

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A steward of the discipline was originally defined as “someone who will creatively generate new knowledge, critically conserve valuable and useful ideas, and responsibly transform those understandings through writing, teaching, and application”. This construct was articulated to support and strengthen doctoral education. This paper expands the construct of stewardship so that it can be applied to both scholars and non-academic practitioners, and can be initiated earlier than doctoral education. To accomplish this, we describe a general developmental trajectory supporting cross-curriculum teaching for stewardship of a discipline as well as of a profession. We argue that the most important features of stewardship, comprising the public trust for the future of their discipline or profession, are obtainable by all practitioners, and are not limited to those who have completed doctoral training. The developmental trajectory is a Mastery Rubric, which requires articulating the knowledge, skills, and abilities (KSAs) to be targeted with a curriculum; recognizable stages of performance of these KSAs; and performance level descriptors of each KSA at each stage. Concrete KSAs of stewardship that can be taught and practiced throughout the career (professional or scholarly) were derived directly from the original definition. We used the European guild structure’s stages of Novice, Apprentice, Journeyman, and Master for the trajectory, and through a consensus-based standard setting exercise, created performance level descriptors featuring development of Bloom’s taxonometric cognitive abilities for each KSA. Together, these create the Mastery Rubric for Stewardship (MR-S). The MR-S articulates how stewardly behaviour can be cultivated and documented for individuals in any disciplinary curriculum, whether research-intensive (preparing “scholars”) or professional (preparing members of a profession or more generally for the work force). We qualitatively assess the validity of the MR-S by examining its applicability to, and concordance with professional practice standards in three diverse disciplinary examples: 1) History; 2) Statistics and Data Science; and 3) Neurosciences. These domains differ dramatically in terms of content and methodologies, but students in each discipline could either continue on to doctoral training and scholarship, or utilize doctoral or pre-doctoral training in other professions. The MR-S is highly aligned with the practice standards of all three of these domains, suggesting that stewardship can be meaningfully cultivated and utilized by those working in or outside of academia. The MR-S can be used for curriculum development or revision in order to purposefully promote stewardship at all levels of higher education and beyond.

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“…In a MR, KSAs are described across a developmental continuum of increasing complexity. The specific developmental stages, derived from the European guild structure, are Novice, Beginner, Apprentice and Journeyman ( [30]; [48]; see also [49] for a recent similar strategy). In the MR-Bi, these stages use Bloom's taxonomy explicitly to characterize the interactions of the individual with scientific knowledge (and its falsifiability).…”

Section: Identification Of Stagesmentioning

confidence: 99%

“…This alignment is explored in Table 3. The results in Table 3 are derived from the design features of any MR, but are also based on curriculum development, evaluation, or revision experiences in other MR development projects (i.e., [30]; [48]; [57], respectively). Table 3.…”

Section: Alignment Of the Mr-bi With The Principles Of Andragogymentioning

confidence: 99%

The Mastery Rubric for Bioinformatics: supporting design and evaluation of career-spanning education and training

Tractenberg

Lindvall

Attwood

et al. 2019

Preprint

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As the life sciences have become more data intensive, the pressure to incorporate the requisite training into life-science education and training programs has increased. To facilitate curriculum development, various sets of (bio)informatics competencies have been articulated; however, these have proved difficult to implement in practice. Addressing this issue, we have created a curriculum-design and -evaluation tool to support the development of specific Knowledge, Skills and Abilities (KSAs) that reflect the scientific method and promote both bioinformatics practice and the achievement of competencies. Twelve KSAs were extracted via formal analysis, and stages along a developmental trajectory, from uninitiated student to independent practitioner, were identified. Demonstration of each KSA by a performer at each stage was initially described (Performance Level Descriptors, PLDs), evaluated, and revised at an international workshop. This work was subsequently extended and further refined to yield the Mastery Rubric for Bioinformatics (MR-Bi). The MR-Bi was validated by demonstrating alignment between the KSAs and competencies, and its consistency with principles of adult learning. The MR-Bi tool provides a formal framework to support curriculum building, training, and self-directed learning. It prioritizes the development of independence and scientific reasoning, and is structured to allow individuals (regardless of career stage, disciplinary background, or skill level) to locate themselves within the framework. The KSAs and their PLDs promote scientific problem formulation and problem solving, lending the MR-Bi durability and flexibility. With its explicit developmental trajectory, the tool can be used by developing or practicing scientists to direct their (and their team's) acquisition of new, or to deepen existing, bioinformatics KSAs. The MR-Bi can thereby contribute to the cultivation of a next generation of bioinformaticians who are able to design reproducible and rigorous research, and to critically analyze results from their own, and others', work.the world began developing curriculum guidelines, defining core (bio)informatics competencies necessary to underpin life-science and biomedical degree programs (e.g., [16]; [17]; [18]; [19]; [20]; [21]). Competencies represent what individuals can do when they bring their Knowledge, Skills and Abilities (KSAs) together appropriately [22], and at the right level(s), for the right application, to achieve a given task. Competencies are thus multidimensional, highly complex, task-specific, behaviors.Using competencies to guide curriculum development has proved problematic (e.g., [23];[24]; [25]; [26]; [27]). In consequence, the Accreditation Council for Graduate Medical Education in the United States has shifted their definition of "competencies-based medical education" towards a specifically developmental approach that specifies and implements "milestones" [28]; [29]. This is a shift of focus for curriculum design (whether recognized or not) from the end-state of ed...

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The Mastery Rubric for Evidence-Based Medicine: Institutional Validation via Multidimensional Scaling

Cited by 11 publications

References 11 publications

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

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

The preparation of stewards with the Mastery Rubric for Stewardship: Re-envisioning the formation of scholars and practitioners

The Mastery Rubric for Bioinformatics: supporting design and evaluation of career-spanning education and training

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