Roundtable on Data Science Postsecondary Education A Compilation of Meeting Highlights (2020) / Chapter Skim
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12 Meeting #11: Data Science Education at Two-Year Colleges
12 Meeting #11: Data Science Education at Two-Year Colleges
Pages 157-178
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From page 157... ...
In light of these trends, participants explored emerging approaches for integrating data science into 2-year curricula as well as strategies to enable connections between 2-year colleges and other postsecondary institutions.
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From page 158... ...
Select recommendations from the report include ensuring that 2- and 4-year institutions work together on issues related to data science education, training, and w orkforce development; attracting and retaining students who have aried backgrounds and levels of preparation to data science programs; v and remaining flexible and developing incentives as programs evolve. The National Science Foundation (NSF)
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From page 159... ...
PANEL ON INTEGRATING DATA LITERACY INTO COURSEWORK AND DEVELOPING DATA SCIENCE PROGRAMS Randy Kochevar, Oceans of Data Institute, EDC Kochevar explained that a dramatic change has occurred during the past several years: many people now learn about the world through streams of data from remote sensors. This presents a challenge for educators who are introducing students to data.
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From page 160... ...
. Most recently, ODI established partnerships with four 2-year colleges ( ormandale Community College, Bunker Hill Community College, N Johnson County Community College, and Sinclair Community College)
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From page 161... ...
A 1-year technical certificate in data analytics4 has 2 The website for the data literacy exam is https://thedataliteracyproject.org/assessment, accessed February 13, 2020. 3 The website for this resource is https://dataliteracy.com/resources/, accessed February 13, 2020.
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Michael Harris, Bunker Hill Community College Harris described Bunker Hill Community College as a diverse campus, with a student population that is 25 percent African American, 25 percent Hispanic, 25 percent Caucasian, and 25 percent other. He explained that Bunker Hill has a three-phase data analytics program, which was devised based on ODI's stackable credentials model (mentioned above)
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As the project team tries to make predictions about the workforce in 2030, it considers the following industryagreed-upon interconnected technologies: big data, autonomous robots, simulation, system integration, Internet of Things, cybersecurity, cloud computing, additive manufacturing, and augmented reality. The project is based on five suppositions: (1)
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From page 164... ...
She described a number of pathways to develop these skills: 2-year college transfer programs, 1-year certificate programs, degree programs aligned with field specialization, stand-alone courses, microcredentials, advanced coursework for returning professionals, and bootcamps/ ontinuing edu c cation. Anderson noted that because many supervisors want to hire people with industry-relevant experience, technicians often go to work immediately after attending a 2-year college instead of pursuing a 4-year degree.
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Specifically, Ullman wondered whether emerging data science programs deemphasize the study of methods and foundations. Harris explained that after consulting with representatives from industry, Bunker Hill decided to add data science projects to fundamental courses so that students would receive a balanced education.
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From page 166... ...
To begin a partnership, Anderson suggested engaging colleagues who have technical connections as well as designing multidisciplinary courses to help build bridges within a community. In response to a question from Jennifer Travis, Lone Star College, Horton said that while buy-in from multiple programs is important, the 2-year data science landscape is heterogeneous
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From page 167... ...
In response to a question from Kelley Engle, Harrisburg Community College, Hansford responded that businesses are receptive to Sinclair's 1-year certificate program, which primarily serves students with 4-year degrees who are seeking to add a specific skill set. Treisman noted that Indian River Community College, Alamo College, and Austin Community College have long-term relationships with employers and might have best practices to share (e.g., colocation of facilities at community colleges)
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From page 168... ...
However, there are a number of areas in which Seattle Central's approach differs. Instead of offering Data 8 in its original integrated format, Seattle Central will offer the program as a set of linked courses: Introduction to Data Analytics and 12 The course website for Data 8 is http://data8.org/, accessed February 13, 2020.
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Meredith described next steps to include piloting both this new data analytics course and a certificate in data analytics in Spring 2020, developing a plan to advertise and attract a diverse student body, collaborating with the social sciences department to create connector modules and to work with its data sets, partnering with other institutions, and identifying faculty training opportunities. DataUp: Increasing the Capacity for Data Science Education Renata Rawlings-Goss, South Big Data Regional Innovation Hub Rawlings-Goss described the objective of the South Big Data Hub: to connect industry, government, and academia around larger issues for societal and economic development, such as data science education and workforce.
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Data Science: A Community College Approach Mary Rudis, Pennsylvania State University, Harrisburg Rudis described her presentation as a "story of hope for greater inclusiveness and diversity for tomorrow's coders, leaders, data practitioners, researchers, and innovators." She referenced a recent report from the Association for Computing Machinery, Lighting the Path from Community College to Computing Careers, which contains case studies about unique approaches to implementing computer science educational pathways across 2- and 4-year institutions in New Jersey, Kentucky, alifornia, regon, and Hawaii (ACM, 2018)
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Coordination and Collaboration Between Two- and Four-Year Institutions Lior Shamir, Lawrence Technological University and Kansas State University Shamir asserted that many 4-year institutions are well funded and suggested that 2- and 4-year institutions collaborate so that resources are allocated, shared, and used more effectively and equitably. Opportunities for collaboration include transfer programs; joint faculty training 14 The website for the Certificate in Practical Data Science is http://greatbay.edu/ ourses/ c certificate-programs/data-practical-data-science, accessed February 13, 2020.
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From page 172... ...
might be better suited to students' needs, he continued. Community college students can complete the CRE at a partner 4-year institution and transfer the credit toward their associates' degrees.
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Students could attend mathe atics camps hosted by community colleges; however, it is difficult m to secure funding for such activities. An online participant asked whether best practices for engaging students transfer from one 2-year college to another.
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Horton said that many data science projects involve up to 90 percent of time wrangling data; this is equally true for undergraduate students. Bapst added that tools change quickly and unpredictably; data science curricula should be agnostic to the language or tools -- which means that the coursework need not be tied 15 For more information about this data science track, see http://catalog.csueastbay.edu/ preview_program.php?
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From page 175... ...
Grisham described the BioQUEST Curriculum Consortium,16 which has 33 years of project work and resources as well as week-long workshops for high school and college life science faculty. She also cited QUBES, an NSFsupported project aimed at faculty professional development, which is comprised of a community of mathematics and biology educators.
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From page 176... ...
Two-year colleges serve a wide range of students: the average Montgomery College student is over age 25, all are exclusively commuters, and some take only a course or two. While community colleges can offer nimble customization, funding and resource constraints make it difficult to implement new programs.
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From page 177... ...
Kotz also elaborated on topics that he would like the data science community to discuss in more depth in the future: • Storytelling -- Are students being trained to communicate about data efficiently and effectively? • Data analysts and data architects -- Does data science mean "play ing in people's backyards" or "building and forming people's backyards"?
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From page 178... ...
He reiterated that "transfer" is not just from 2- to 4-year institutions; it also involves students moving from 4- to 2-year institutions and from high school to community college. Administrators need to think about models for back-office functions to enable these transitions.
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