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      The Mastery Rubric for Bioinformatics: A tool to support design and evaluation of career-spanning education and training

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          Abstract

          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 is a tool that can 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.

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          Validating the Interpretations and Uses of Test Scores

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                26 November 2019
                2019
                : 14
                : 11
                : e0225256
                Affiliations
                [1 ] Collaborative for Research on Outcomes and –Metrics, and Departments of Neurology, Biostatistics, Biomathematics and Bioinformatics, and Rehabilitation Medicine, Georgetown University, Washington, DC, United States of America
                [2 ] National Bioinformatics Infrastructure Sweden (NBIS)/ELIXIR-SE, Science for Life Laboratory (SciLifeLab), Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden
                [3 ] Department of Computer Science, The University of Manchester, Manchester, England, United Kingdom; The GOBLET Foundation, Radboud University, Nijmegen Medical Centre, Nijmegen, The Netherlands
                [4 ] ELIXIR Italy, National Research Council of Italy, Institute of Molecular Biology and Pathology, Rome, Italy
                University of Toronto, CANADA
                Author notes

                Competing Interests: Rochelle Tractenberg has read the journal’s policy and has the following competing interest: She is a section editor for PLOS ONE; this does not alter our adherence to PLOS ONE policies on sharing data and materials. The other authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-1121-2119
                Article
                PONE-D-19-15839
                10.1371/journal.pone.0225256
                6879125
                31770418
                bdc3eec9-64e7-4369-b6c0-2a1475526eb1
                © 2019 Tractenberg et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 6 June 2019
                : 24 October 2019
                Page count
                Figures: 0, Tables: 3, Pages: 29
                Funding
                The author(s) received no specific funding for this work, however, we gratefully acknowledge the Georgetown University Department of Neurology, the GOBLET Foundation, and ELIXIR Italy for defraying the publication costs of this article.
                Categories
                Research Article
                Research and Analysis Methods
                Database and Informatics Methods
                Bioinformatics
                Biology and Life Sciences
                Neuroscience
                Cognitive Science
                Cognitive Psychology
                Learning
                Human Learning
                Biology and Life Sciences
                Psychology
                Cognitive Psychology
                Learning
                Human Learning
                Social Sciences
                Psychology
                Cognitive Psychology
                Learning
                Human Learning
                Biology and Life Sciences
                Neuroscience
                Learning and Memory
                Learning
                Human Learning
                Biology and Life Sciences
                Neuroscience
                Cognitive Science
                Cognitive Psychology
                Learning
                Biology and Life Sciences
                Psychology
                Cognitive Psychology
                Learning
                Social Sciences
                Psychology
                Cognitive Psychology
                Learning
                Biology and Life Sciences
                Neuroscience
                Learning and Memory
                Learning
                Research and Analysis Methods
                Research Design
                Experimental Design
                Research and Analysis Methods
                Database and Informatics Methods
                Health Informatics
                People and Places
                Population Groupings
                Professions
                Instructors
                Research and Analysis Methods
                Research Assessment
                Reproducibility
                Biology and Life Sciences
                Neuroscience
                Cognitive Science
                Cognition
                Custom metadata
                All of the data are included in this manuscript: the data are qualitative and are included in the tables.

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