Data Diggers

Dylan Poulsen, the John Allender Associate Professor of Data Ethics, is excited about the new Data Science Innovation Lab (DSIL), where student interns gain real-life research experience analyzing and organizing data for College and community projects. As well as contributing to the community by helping organizations understand and interpret data, it prepares these future data scientists for in-demand careers.

Data science, simply put, applies scientific methods and processes to glean insights from raw data. It involves gathering, analyzing, and deciphering data sets to build models that identify patterns and trends. These models are often presented in a visual way to help people understand and use them, such as graphs and charts. This approach can break down complex problems into more digestible constituent parts and show how these parts are connected.

Poulsen has woven strategic career development goals into the DSIL program. Each student intern comes out with their own robust portfolio of projects, which demonstrates experience collaborating on intricate research projects and tackling diverse analytical challenges—the skills and proven experience employers are looking for. Entry-level data science positions posted on online job boards list salary ranges of up to $160,000 per year. 

Data science has broad applications across the liberal arts curriculum. At Washington, students can take data science courses in economics, physics, sociology, political science, psychology, and more.

Why a Data Science Innovation Lab?

DSIL was spearheaded to foster a new way to learn about data science and apply its methods in practice. The data science team developed a curriculum where Washington students focus on community and ethical engagement.

Student interns on the DSIL team learn how to manage large datasets from real-life projects. They also learn how to communicate with a variety of stakeholders, from chief researchers to community leaders, and produce deliverables that are applicable and comprehensible to the many end users of the data.  

What projects has DSIL assisted with? 

DSIL was involved with the Eastern Shore opinion poll in collaboration with Professor Flavio Hickel in political science. The poll surveyed registered voters in Maryland’s 1st District on the midterm elections in 2022 and civic engagement issues. The interns were involved in analyzing the data that was collected. This is a good example of how our students can help make data interpretable for a client while developing their own data science skills along the way.

There is a lot of collaboration between on-campus data science interns and community program stakeholders. For example, we worked on the Busload of Books project in which a Chestertown author and illustrator spent a school year on an epic road trip visiting Title I schools in all 50 states and Washington, D.C. At each school, they gave presentations on creativity and collaboration and gave away 25,000 hardcover books in total to students and teachers from underserved communities. On that trip, Busload collected survey data for Washington professors from these Title I schools.

DSIL is working on evaluating the data and making it available to the public. Ideally, the Busload of Books research team wants to understand how author/illustrator visits impact attitudes about literacy and creativity among elementary school students. The data will provide critical insights on this topic—and could provide a toolkit for school administrators and teachers trying to secure funding and priority for literacy programming.

What part does ethics play in coursework that
supports DSIL?

Ethical discussion is integrated throughout the semester to encourage students to gain confidence in examining the framework of the data. Intro to Data Science includes writing about, reflecting on, and digging into ethical considerations. We encourage students to think beyond how we analyze and display the data and think about contexts, how to protect people’s privacy, and how important it is to anonymize data. For example, students consider how to avoid unethical algorithmic bias, which occurs when algorithms make decisions that systematically disadvantage certain groups of people.

Data Science Ethics and Practicum is a course where we discuss ethical issues in data science and run practical projects based on community needs. Our students get hands-on experience thinking about ethical considerations when it comes to data science.   

What is the goal for DSIL?

The main goal is for DSIL to produce well-trained data scientists who are ready for the workforce with plenty of experience and whose expertise can benefit the state of Maryland economically.