Academic Experience

At the heart of the FSI program is an immersive and rewarding academic experience. In the summer of 2021, students will have the option of taking one or two virtual, full credit-bearing courses that count toward graduation requirements. 

All FSI students will take Ways of Knowing, an introduction to scholarly thinking, reading, and writing. In addition, students will have the option to enroll in a second quantitative/STEM course based on their academic interests, including Introduction to Laboratory Research in the Natural Sciences; Introduction to Engineering; Data Visualization and Statistics; and Humanistic Approaches to Data

Scholars Academic

FSI students read and learn scholarship from the world's top thinkers through the Ways of Knowing course.


As a Freshman Scholar, you’ll be enrolled in a for-credit humanities course titled Ways of Knowing. This seminar emphasizes critical thinking, reading, and writing, and allows you to engage with texts, fellow scholars, and your course instructor to dig deeply and creatively into questions about power, institutions, and identity. Having this course under your belt will help prepare you for text- and writing-intensive classes in the fall, and give you additional curricular flexibility to pursue other meaningful experiences, like scholarly research, service work, or mentorship opportunities. Finally, Ways of Knowing meets your Epistemology and Cognition and Culture and Difference general education requirements.

The synchronous components of Ways of Knowing include classes on Tuesdays and Thursdays, and weekly small group and one-on-one meetings with faculty and undergraduate course fellows. Scholars can expect approximately 6 hours per week of synchronous work. The asynchronous components include reading, module work, and writing assignments. Scholars can expect to spend another 10-12 hours of time per week in asynchronous work.


Lab pic


Depending on their academic interests, students choosing to take two FSI courses will also be placed into one of the following four quantitative courses. Each of these courses will meet on Monday and Wednesday afternoons and Friday mornings (EDT).  Scholars can expect to spend about 8-10 hours of time in synchronous work, with an additional 8 hours of time per week in asynchronous work. The asynchronous components include watching lecture, reading, lab work, module work, problem sets, and writing assignments.

The following courses will be offered:

EGR 150: Foundations of Engineering 

This course provides a hands-on introduction to the foundational principles of engineering. The purpose of this course is two-fold. First, it provides a project-based introduction to engineering that mixes electronics, mechanical construction, and computational data analysis. Second, it provides a firm theoretical foundation for the project in both math and physics. In lab, students will have the opportunity to build, test, and iterate the design of a rocket. Complimenting the lab experience, students will engage in lectures and precepts to enhance their physics and mathematics content knowledge. (Distribution requirement fulfilled: Science and Engineering with a Lab)


MOL 152: Laboratory Research in the Life Sciences 

This course will introduce students to laboratory research through a 6-week original research investigation. Although lecture and discussion will be incorporated as needed, by far the largest part of the course will consist of authentic hands-on research. Students will learn how to perform essential laboratory techniques, to design experiments, and to analyze and interpret experimental data. Students will gain experience in both written and oral presentation of scientific results. Students will use synthetic biology tools to conduct original promoter analysis research. (Distribution requirement fulfilled: Science and Engineering with a Lab)

SOC/POL 245: Visualizing Data 

Equal parts art, programming, and statistical reasoning, data visualization is critical for anyone who seeks to analyze data. Data analysis skills have become essential for those pursuing careers in policy evaluation, business consulting, and research in fields like public health, social science, or education.  This course introduces students to the powerful R programming language, the basics of creating data analysis graphics in R, and reasoning about what data visualizations can tell us. We will learn these topics through the lens of a single social scientific subject: intergenerational mobility, the relationship between social and economic origins and destinations over the life course. We will use real life data to describe, visualize, and understand intergenerational mobility in the United States. (Distribution requirement fulfilled: Quantitative and Computational Reasoning) 


HUM 295: Humanistic Approaches to Media and Data 

This course introduces students to critical approaches to media and data with the goal of helping students better assess media and data's permeating role in society, culture, and politics today. Through modules covering visual culture, science and technology studies, and digital humanities, student will learn to analyze mass-circulated images and text; examine the historical and social context of technoscientific innovation; and experiment with data sets and visualization. As we explore these approaches to the study of media, culture, and technology, we will consider the stakes of such inquiry from the standpoint of justice and equity. (Distribution requirement fulfilled: Social Analysis)