Published: Nov. 13, 2020 By

Inclusive data science logoData exist all around us, from the tweets flying by on social media to the groceries being scanned at the market. This growing wealth of information, known as Big Data, provides exciting opportunities for transforming our economy, reshaping our political and social lives and impacting many, if not most, disciplines across the academy. 

But the excitement surrounding Big Data needs to be tempered by understanding its limitations. As history instructor Vilja Hulden notes “Big Data is good at answering what, but we need the humanities to help us figure out how and why.” To understand the full story behind the data, a new introductory data science course, Interdisciplinary Data Science for All (AHUM 1825), aims to empower students to view data through a humanist lens and to see the humanity within data. 

Vilja HuldenBig Data is good at answering what, but we need the humanities to help us figure out how and why.

–Vilja Hulden, Instructor of History

The course is being developed by an interdisciplinary team of arts & sciences faculty, with the support of ASSETT’s Innovation Incubator. As Eric Vance, an associate professor of applied mathematics and director of the Lab for Interdisciplinary Statistical Analysis (LISA), describes it, the course will empower students to “learn and apply humanities ways of thinking, statistical thinking, and computing to get to the heart of data to uncover the true story of data."  

Associate Professor of English David Glimp adds: “The class will provide students from the arts and humanities an opportunity to develop the data literacy that will be vital for engaged citizenship in the 21st century. By the same token, Interdisciplinary Data Science for All will help students from STEM backgrounds see the value of humanistic attention to the complexity and variety of the human experience.”  

This approach differs from the traditional introductory data science curriculum, which instructs students on how to apply data analysis but leaves the ethical concerns of why until higher-level courses. The National Academies of Science, Engineering, and Medicine advise academic institutions to "ensure that ethics is woven into the data science curriculum from the beginning and throughout," rather than placing ethics on a back burner, to be addressed when and if time allows.

Team member Nathan Pieplow, associate director of the Global Studies Residential Academic Program (RAP) and an instructor in the Program for Writing & Rhetoric, observes: “It's high time we recognized that data scientists need to be humanists, and humanists need to be data scientists. AHUM 1825 is going to break down the boundary between the qualitative and quantitative. This is the kind of course that will get [students] thinking about knowledge and problem-solving in a new way.”  

Nathan PieplowAHUM 1825 is going to break down the boundary between the qualitative and quantitative. This is the kind of course that will get [students] thinking about knowledge and problem-solving in a new way.

– Nathan Pieplow, Associate Director, Global Residential Academic Program (GRAP)

Preparations are still underway for teaching this new course on inclusive data science in fall 2021, so please stay tuned for further details as they become available.  

The ASSETT Innovation Incubator, which supported the creation of AHUM 1825, is a three-year pilot that provides a safe, resourced environment in which the arts and sciences community can grow innovative teaching and learning ideas. Via the incubator, funds provided by the College of Arts & Sciences and ASSETT support four interdisciplinary teams: Multimodal Participatory Publishing, Metacognition + Well Being, Student Success, and Inclusive Data Science. The Inclusive Data Science team is cultivating an interdisciplinary platform for data science at the university by working to weave humanistic forms of inquiry throughout the data science curriculum. 

For more information about the course, the Inclusive Data Science initiative, or the Innovation Incubator, contact Shane Schwikert, data analytics and applied learning sciences manager, or Blair Young, innovation catalyst. For more information about ASSETT, visit www.colorado.edu/assett.