Teaching & Mentorship
Teaching Philosophy
My approach centers on active learning, methodological rigor, and practical application—helping students develop both theoretical understanding and technical skills they can apply to pressing societal challenges.
I believe in making complex political science concepts accessible through hands-on learning and real-world applications, particularly in quantitative methods and comparative politics.
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)
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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)
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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)
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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)
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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)
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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
- Online Extremism (January 2021)
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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.
Teaching Resources
Quantitative Methods Materials
- Tutorial 1: Getting Started with Greek Notation and Descriptive Stats
- Tutorial 2: An Introduction to R’s pipe operator
- Tutorial 4: Variable Transformations in R - Understanding distributions, log transforms, and data recoding
- Tutorial 5: Using AI Chatbots to Learn R Programming - Effective strategies for LLM-assisted coding and learning
- Tutorial 6: Understanding File Systems and Working Directories in R and RStudio
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