Data Education–Inclusivity is the Word

 

As organizational and societal decisions become more data-driven academic institutions, industry, and government officials continuously identify data literacy as an important skillset for individuals currently in and entering the workforce.  Unfortunately, a dearth of qualified data literate employees exists producing a need for effective data science education and training for undergraduates. 

The National Academies of Sciences (NAS) formed a study committee to consider the core principles and skills undergraduates should learn and the pedagogical issues that must be addressed to build effective data science education programs.  The “Data Science for Undergraduates: Opportunities and Options” project underscores the importance of preparing undergraduates for a data-enabled world and recommends that academic institutions and other stakeholders take steps to meet the evolving data science needs of students.  To meet these evolving data science needs requires comprehensive inclusivity.  The project conducted two studies, “Envisioning Data Science: An Undergraduate Experience” and “Keeping Data Science Broad,” each collecting input from data science programs, institutions, and industry leaders.  During the final project webinar, “Data Science for Undergraduates: Opportunities and Options”, presenters discussed finding that inclusivity is necessary for data science education.  According to the findings, “inclusivity“, “broadening“, and “collective“, describe the future vision of data science education.

Data science is not mutually exclusive to engineers, computer scientists, statisticians, or hard scientists; data programs should focus on attracting students with varied academic backgrounds and identifying opportunities in existing curriculum for students to interact with data. Data education should expand throughout academic disciplines, but it is necessary that students trained in data science are exposed to continual curricular and co-curricular opportunities to hone vital communication and teamwork skills. Inclusivity refers not only to diversifying student’s exposure to data, but also requires faculty and institutions to think inclusively about collaboration. As an integral part of workforce development, academic institutions should encourage and incentivize faculty members not to build “hard walls” in or around their departments, but to cross-collaborate to foster experiences that include continuous student exposure to data, communication, and teamwork skills.

Building a capacity for data science education and workforce development is a key priority for the South Hub.  Along with a leading role in the execution of the Keeping Data Science Broad series and associated white paper publication, the South Hub created the DataUp program to increase the capacity to teach data science education at minority-serving institutions, primarily teaching institutions, community colleges, and four-year liberal arts colleges.  The DataUp program participants will receive one 2-day data science workshop hosted on their campus, travel funding to attend an in-person train-the-trainers workshop in Atlanta, GA, and teach a workshop, bootcamp, or course in 2019.  To learn more about the program and the participants, Click Here.

The South Hub also supported a grant proposal for the program Data Science Extension (DSX).  The program provides support for 10 faculty members at Morehouse and Spelman Colleges for data science curriculum and professional development experiences.  DSX also will provide a financial stipend for program participation and curriculum development for a fall data science course taught by Principal Investigator Brandeis Marshall, PhD, chair of the computer and information sciences department, at Spelman College.

Want to learn more about the South Hub’s role in the Keeping Data Science Broad project? Click Here

Interested in watching the Data Science for Undergraduates: Opportunities and Options webinar?  Click Here

One thought on “Data Education–Inclusivity is the Word

  1. Pingback: Data Science newsletter – June 6, 2018 | Sports.BradStenger.com

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