National Academy of Sciences Starts Framing Data Science Education
- By Dian Schaffhauser
As the use of data proliferates through business, government and academia, a new job title — the data scientist — has emerged, sweeping away seemingly less compelling occupations in its wake. For the second year in a row, for example, job website Glassdoor named "data scientist" as the top career based on the number of job openings, salary and overall job satisfaction rating. PwC projected in 2015 that 2.3 million open jobs asked for the kind of analytics skills on which data scientists thrive.
That kind of workforce opportunity has inspired hundreds of colleges and universities to open certificate and undergraduate- and master's-level degree programs. Yet, no two programs are the same. As a new interim report from the National Academies of Sciences stated, the field is heaped with "new principles for data collection, storage, integration and analysis." Plus, new tools abound in the field. Yet, "the main concepts, skills and ethics powering this emerging discipline of data science" haven't been identified yet. Data science, as the report stated, "is still in its infancy."
The goal of the project is to envision what the field might look like in the future to help institutions better understand what they need to do "to move data science education in that direction." While the interim document focuses on the undergraduate level, it also examines issues at the middle and high school levels as well as community college and master's-level programs.
The report offers information and comments gathered from an extensive committee of educators through two workshops, provides perspectives on the current state of data science education and poses questions that could help shape the way data science education evolves.
Now the project leaders are seeking public input on a series of questions related to themes about data science and analytics, among them:
- Which components should be included in data science curriculum, now and in the future, and how should they be prioritized for distinct types of programs?
- How can partnerships between industry and educational programs be encouraged?
- Would a focus on real problems serve to attract more diverse students?
- How can students gain access to real-world data sets?
- How can ethical considerations be best incorporated in data science curriculum?
- What types of training would benefit faculty? And
- How can partnerships between two- and four-year institutions be facilitated?
Now the committee is hosting a series of webinars, in which speakers discuss aspects of data science education. The next one is taking place Oct. 17, and the subject is ethics. Previous webinars on building data acumen, using real-world applications, training faculty, developing communication skills and teamwork and collaboration among departments and institutions are available in recorded form.
The committee is also requesting case studies from schools that are providing data science education.
The group expects to release its final report laying out a vision for future data science education in early 2018.
The current report is available for free PDF download on the Academies website; a paperback edition of the final report is available for pre-order for $32.40.
Dian Schaffhauser is a former senior contributing editor for 1105 Media's education publications THE Journal, Campus Technology and Spaces4Learning.