Data Science Course Design Institute

Data Science in My Course?

Have you ever thought about introducing your students to a new way of thinking about your discipline through data?  Is there a data related tool out there that might enhance your teaching?   Are you a little overwhelmed by thinking about ‘what is data science anyway’?   If you find yourself thinking about these issues, the Data Science Course Design Institute (DSCDI) is a great opportunity for you to begin to develop new, or enhance existing data science related content in your course.  

As a participant in the DSCDI you will:

  • Acquire a better understanding of the scope of the field of data science
  • Observe and discuss strategies to teach data science content, with an emphasis on differentiating among different levels of technical skills
  • Write a data science learning outcome for your course
  • Create a outline for a data science related teaching and learning experience 

In addition to the content knowledge, participants in the institute receive a $750.00 stipend to faculty research accounts.  Participants are also given priority to collaborate with a Data Science Fellow in Fall 2024.  The Data Science Fellow is an undergraduate student with data science skills to assist the faculty member with implementing the plan generated in the course design institute.  Data science fellow stipends are compensated by the Sheridan Center and thus no cost to you or your department. 

Past participants in the DSCDI find the implementation of their curricular innovations greatly advanced by the collaborative discussions and information in the DSCDI.  Some examples of past projects include:

  • Developing in-class tutorials on R and Python
  • Enhancing data visualizations of challenging statistical principles
  • Text mining literature corpus to identify key readings to align with learning outcomes
  • Leveraging Python to study Arabic proper name roots and cultural connections
  • Leveraging pre-scripted Python notebooks to facilitate data analysis and results for lab based courses.
  • Developing machine learning examples using domain specific data
  • Exploring image segmentation to identify a process to categorize ancient images for classroom instruction
  • Providing replicable data analysis from scholarly articles
  • Developing a web-based tool to determine foreign language proficiency standards
  • Web scraping and text mining student survey responses to provide formative feedback for curricular content
  • Developing a new DATA First Year Seminar course at Brown
  • Developing a series of instructional videos about using the pandas package in Python
  • Integrating data visualizations and better survey writing into Chinese language courses
  • Designing an easily editable Community Profile Flyer template to quickly create personalized flyers for organizations in Rhode Island that work with Black communities
  • Building an OCR model with the goal of accelerating the pace at which researchers and learners can parse massive amounts of hieroglyph data

The Spring 2024 DSCDI will be completely remote, starting in early February 2024 through April 2024.  There will be one synchronous meeting (one and a half hours long) each month (February, March and April).  There will be a total of three modules for the DSCDI, for each module participants will be expected to:

  • Read one to two articles (guiding questions provided)
  • Post a reaction to the institute discussion forum
  • Respond to a colleague’s reaction
  • Record developing data science related plans for their own teaching  
  • Complete an ‘entry ticket’ for each synchronous meeting

Faculty interested in learning more about the DSCDI are asked to complete the interest form.  

Data Science Course Design Faculty Participants


  • Christelle Alvarez, Egyptology and Assyriology
  • Pierre de Galbert, Education
  • Xan Chacko, Science and Technology Studies
  • Sakthi Swarrup, Ecology, Evolution, and Organismal Biology
  • Rebecca Nedostup, History
  • Lulei Su, East Asian Studies
  • Xingchi Yan, Math


  • Jennifer Barredo, Clinical Neuroimaging Research Core
  • Ruth Colwill, CLPS
  • Xiaojing Du, EEPS
  • Marrisa Gray, Engineering
  • Nell Lake, English
  • Pablo Leon Villagra, CLPS


  • Brenda Rubenstein, Chemistry
  • Jonathan Fine, German Studies
  • Parker VanValkenburgh, Anthropology
  • William Goedel, Epidemiology
  • Xueke Li, Institute at Brown for Environment and Society


  • Ehsan Barati, Chemistry
  • Elsa Belmont Flores, Center for Language Studies
  • Karianne Bergen, Earth, Environmental and Planetary Sciences
  • Ashley Champagne, American Studies
  • Zachary Dunseth, Joukowsky Institute for Archaeology and the Ancient World
  • Deborah Hurley, Computer Science
  • David Meyers, Health Services, Policy and Practice
  • Kevin Mwenda, Population Studies and Training Center
  • Andras Zsom, CIS
  • Robert Hackey, Public Policy/International and Public Affairs


  • Loren Albert, Institute at Brown for Environment and Society
  • Robert Campbell, Molecular Pharmacology, Physiology and Biotechnology
  • Diana Grigsby, School of Public Health
  • Jonathan Pober, Physics
  • Sydney Skybetter, Theatre Arts and Performance Studies
  • Jane Sokolosky, Language Studies/German Studies
  • Chelsea Timlin, Language Studies