Academic Experience

At the heart of the FSI program is an immersive and rewarding academic experience. In the summer of 2023, residential students will take two 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, residential students will 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
  • Humanistic Approaches to Data
  • Art and Science of Computer Programming
  • Mathematical Communication in the Quantitative Disciplines 

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.

Lab pic


Depending on their academic interests, FSI residential students will also be placed into one of the following four quantitative courses. The course components include attending lecture, completing readings, 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)


COS 125, The Art and Science of Computer Programming

This course is an introduction to computer programming for students with little to no previous experience. Students will learn to write, read, and reason about computer programs. Topics include conditionals, loops, sound, animation, arrays, and functions. This course offers an alternative arts-inspired presentation of the first half of the material covered in COS 126. (Distribution requirement fulfilled: Quantitative and Computational Reasoning)

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)


APC 152, Mathematical Communication in the Quantitative Disciplines

This course showcases how techniques in pure mathematics can be applied to solve problems in a variety of quantitative disciplines, including Economics, Chemistry, Ecology, Probability and Statistics, and Computer Science. The course has two main goals. First, we aim to show that mathematics is not an isolated subject, but rather a web with connections and contributions to all of science. Second, we will put great emphasis on developing students' oral and written communication skills when it comes to describing their thoughts, arguments, and solutions. Indeed, solving a math problem is not just a matter of arriving at the correct final answer, but also communicating delicate, technical arguments in such a way that others can understand precisely what we mean. This skill will prove invaluable as students go on to discuss the material in Princeton STEM courses with their classmates and professors. This course will not assume or require any calculus knowledge. (Distribution requirement fulfilled: Quantitative and Computational Reasoning)