Teaching & Mentorship

Teaching Philosophy

As a product of the liberal arts myself—I graduated summa cum laude from Middlebury College—I experienced firsthand how rigorous, small-classroom teaching can transform how students think about the world. That experience profoundly shapes my approach to teaching political science: I believe that quantitative and computational methods become most powerful when students understand why they matter, not just how to execute them.

My approach centers on active learning, methodological rigor, and practical application. In quantitative methods courses, I structure lessons around real political science questions—students learn regression not in the abstract but by analyzing actual datasets on topics like political violence, public opinion, or democratic institutions. I develop original tutorials and educational materials (available below) specifically designed to guide students with no prior coding experience through foundational concepts in R, from Greek notation to working directories. I meet students where they are and build their confidence through scaffolded assignments that progressively introduce complexity.

I also believe strongly in integrating my research into the classroom. My self-designed courses at Middlebury College and the Middlebury Institute of International Studies have all included substantial original research components, where students work with real data and produce their own analyses. In my Post-War Fascism seminar, for example, students developed original research designs on topics in contemporary fascism studies, learning both substantive expertise and methodological skills simultaneously.

Finally, I am committed to inclusive pedagogy. Quantitative methods can be intimidating for students who see themselves as “not math people.” I work to break down that barrier by connecting statistical reasoning to students’ existing intuitions about politics, by creating a classroom environment where questions are encouraged, and by developing resources—like my tutorial on using AI chatbots to learn R—that give students multiple pathways into the material.

Teaching Impact

45+ students mentored | 15 independent projects supervised | 7 courses taught | 3 institutions

Courses Taught

University of Colorado Boulder

Teaching Assistant

PSCI 2075: Quantitative Methods (Fall 2025, Spring 2024)

Comprehensive introduction to statistical analysis in political science, covering descriptive statistics, hypothesis testing, regression analysis, and research design. Emphasized practical application using R and real political datasets.

PSCI 1101: Introduction to Western Political Thought (Spring 2025)

Survey of foundational political philosophy from ancient Greece through Enlightenment thinkers, connecting classical ideas to contemporary political challenges.

PSCI 2223: Introduction to Comparative Politics (Fall 2024)

Exploration of political systems, institutions, and processes across different countries and regions, with emphasis on democratization, authoritarianism, and political development.

PSCI 1824: Introduction to International Relations (Fall 2023)

Comprehensive overview of international relations theory and practice, covering security studies, international political economy, and global governance challenges.

Middlebury Institute of International Studies

Adjunct Professor

Digital Extremism (Spring 2023)

Self-designed course examining the intersection of technology and political violence. Covered online radicalization processes, platform dynamics, and content moderation strategies. Students conducted original research on extremist communities across digital platforms.

Middlebury College

Adjunct Professor

INTD 1027: The Study of Post-War Fascism (Winter 2026)

Self-designed interdisciplinary course examining the transformation of fascism and fascist movements following World War II. Covered philosophical and political roots, activism, violence, and research ethics across Italy, Russia, the UK, and the US. Students produced original research designs on topics in contemporary fascism studies.

Online Extremism (January 2021)

Intensive winter term course on digital radicalization and online political violence. Integrated computational methods with political science theory, providing students hands-on experience with social media data analysis.

Courses Prepared to Teach

In addition to the courses I have already taught, I am prepared to teach the following:

  • Introduction to Political Science / American Government
  • Introduction to Comparative Politics
  • Quantitative Research Methods (introductory and advanced)
  • Data Science for Social Scientists
  • Political Violence & Extremism
  • Technology, Media & Politics
  • Senior Seminar / Capstone in Computational Social Science

Teaching Resources

Quantitative Methods Materials

I develop original, open-source educational materials for my courses, designed to make quantitative methods accessible to students with no prior coding or statistics experience. These tutorials are used in CU Boulder’s PSCI 2075 course and are freely available:

Sample Syllabi

Student Research Mentorship

I have supervised 45 undergraduate and graduate research assistants and 15 independent projects since 2019. My mentorship philosophy emphasizes methodological rigor, ethical research practices, and practical skill development.

Current Projects

  • Apocalyptic Language Analysis: Four undergraduate RAs working on qualitative coding for social media research

Past Student Projects

  • Italian Neofascism & Political Violence
  • Militant Accelerationism & Coalition-Building
  • French Far-Right on Encrypted Platforms
  • AI Implications for Domestic Counterterrorism
  • Christian Identity Movements
  • Gaming Platform Radicalization

Research-Teaching Integration

My courses integrate cutting-edge research methods with substantive political science questions. Students learn to:

  • Apply computational methods to real political phenomena using Python, R, and specialized software
  • Critically evaluate digital media, online communities, and algorithmic systems
  • Navigate ethical challenges of studying sensitive political topics
  • Connect theoretical frameworks to empirical analysis through hands-on projects
  • Develop professional skills in data visualization, statistical analysis, and research communication

Signature Approach: Each course includes substantial research components where students collect and analyze original data, preparing them for graduate study or professional research roles.

Interested in collaboration or guest lectures? Contact alex.newhouse@colorado.edu