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4 Broad Participation in Data Science
Pages 26-30

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From page 26...
... There are also numerous skill sets that are currently captured under a data scientist label that span multiple training and education levels. There are many current and recent efforts aimed at increasing diversity, inclusion, and broadening participation in fields related to data science.
From page 27...
... For inherently inteerdisciplinary ddegree programs with multiple potential routes for student su w p s uccess, such a m metaphor strucctures a more o open, collabora ative approach toward building programs tha attract divers students than a fixed pipeli metaphor. g at se n ine SOURCE: Library of Vir rginia (2014)
From page 28...
... For example, it may be necessary to do targeted outreach to recruit students who are interested in enrolling in data science courses but may not find course titles immediately relevant or appealing. It may also encourage such students to know that a lack of preparation in data science does not equate to a lack of ability; developing multiple pathways to incorporate data science concepts into varied curricula via specialized connector courses or other "on ramps" could address these students' concerns about knowledge gaps and allow them to gain the level of expertise appropriate for their interests and career goals.
From page 29...
... PUBLIC OUTREACH In addition to efforts that could be achieved in formal educational spaces, there are outreach efforts to students in more informal spaces, including year-long afterschool programs, summer camps, high school internship programs, competitions, and websites designed to foster motivation and interest in 6 See the Next Generation Science Standards website at https://www.nextgenscience.org/, accessed August 21, 2017. 7 See the Common Core State Standards website at http://www.corestandards.org/, accessed August 21, 2017.
From page 30...
... It is useful for program evaluation to follow established best practices, including following an appropriate model for inclusion of metrics for participation in the overall goals of the program, clearly articulating these to all participants from the beginning of the program, establishing procedures for assessing these metrics on a regular basis, and specifying adaptation and modification procedures based on these formative and summative assessments. In establishing approaches for measuring success, the tools of experimental design and analysis can be incorporated when appropriate (using, for example, comparison of treatment and control, randomized trials, nationally normed instruments, exploitation of natural experiments, appropriate descriptive analyses of observational data accounting for confounding factors, etc.)


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