The public teaching archive: complete course descriptions, learning
objectives, schedules, lecture notes, and reading lists. Enrolled
students can continue into the dashboard; everyone else is welcome to
read.
7 public coursesAll teaching materials except
explicitly private courses
-
479 · Fall 2025, Term A
Towards Synthesis: Rethinking Learning in the AI Era
This course responds to a new learning reality shaped by advances in
machine learning. It traces historical tools externalizing memory, from
stylus to internet and smartphones, and highlights the reciprocal
learning relationship between humans and AI systems. Through concepts
like technosymbiosis and symbiotic pedagogy, we explore how both forms
of learning—machine and human—come together in synthesis.
-
Instructor
-
Liam Magee
-
Institution
-
University of Illinois Urbana-Champaign
-
Materials
-
9 public items
-
Credits
-
4
machine learningpedagogyAIphilosophy
Learning objectives
-
Understand the historical relationship between technology and learning
-
Explore the phenomenology of AI-mediated learning experiences
-
Develop critical frameworks for evaluating AI in educational contexts
-
Practice synthesis of human and machine learning approaches
-
490 · Spring 2025, Term B
Understanding and Applying AI in Learning Contexts
This course provides a comprehensive introduction to generative AI and
its applications in education. Students explore the history, technical
foundations, and ethical implications of AI, developing critical
frameworks for its integration into teaching and learning.
-
Instructor
-
Liam Magee
-
Institution
-
University of Illinois Urbana-Champaign
-
Materials
-
14 public items
-
Credits
-
4
generative AImachine learningpedagogycritical AIransformers
Learning objectives
-
Understand the history and development of artificial intelligence
-
Gain intuition about how machine learning works
-
Critically evaluate AI alignment and ethics
-
Apply AI tools thoughtfully in educational contexts
-
490-spring-2026 · Spring 2026
Historical, technological, practical, critical, pedagogical, and
futurological lenses
A seven-week workshop course approaching generative AI in education
through six complementary lenses. Participants connect technical
foundations and historical context with critical analysis, educational
practice, and future-facing design.
-
Instructor
-
Liam Magee
-
Institution
-
University of Illinois Urbana-Champaign
-
Materials
-
7 public items
generative AIeducationpedagogycritical AImachine learning
Learning objectives
-
Understand generative AI through historical, technological,
practitioner, critical, pedagogical, and futurological lenses
-
Develop an intervention addressing a pedagogical or social challenge
raised by AI
-
Respond thoughtfully to practical scenarios involving generative AI in
education
-
590 · Fall 2025, Term B
Developing Literature Reviews in the Age of AI
This graduate course combines foundational research skills with emerging
AI-assisted methods for academic scholarship. Students learn traditional
literature review techniques while exploring how AI tools can enhance
reading, searching, mapping, and writing processes.
-
Instructor
-
Liam Magee
-
Institution
-
University of Illinois Urbana-Champaign
-
Materials
-
9 public items
-
Credits
-
4
literature reviewresearch methodsAI toolsacademic writinggraduate studies
Learning objectives
-
Develop a comprehensive literature review on a chosen topic
-
Master techniques for close and distant reading with AI
-
Understand the sociology of knowledge and reflexivity
-
Apply AI tools ethically and effectively in scholarship
-
dissertation · Ongoing
Strategies for Navigating Research and Writing with Technology
A semi-structured collection of notes and lectures for doctoral and
advanced graduate students navigating the dissertation writing process.
-
Instructor
-
Liam Magee
-
Institution
-
University of Illinois Urbana-Champaign
-
Materials
-
10 public items
-
Credits
-
0
dissertationhesis writingacademic writingresearch methodsAI toolsgraduate studies
-
socsci_and_ai · Spring 2025
Bolashak Program: AI-Augmented Research Methods
This course explores the intersection of social science research methods
and artificial intelligence. Covering qualitative research, data
analysis, mixed methods, and critical scholarship, participants learn to
leverage AI tools like local LLMs, CAQDAS platforms, and generative AI
for rigorous academic research while maintaining methodological
integrity.
-
Instructor
-
Liam Magee
-
Institution
-
Bolashak Program
-
Materials
-
9 public items
-
Credits
-
3
social scienceresearch methodsAIqualitative researchmixed methodsCAQDAS
Learning objectives
-
Understand the capabilities and limitations of AI in social science
research
-
Apply qualitative and quantitative research methods with AI assistance
-
Use CAQDAS tools like Dedoose for systematic data analysis
-
Develop critical perspectives on AI-generated scholarship
-
Practice mixed methods research design with AI augmentation
-
test · Testing
A showcase of all LMS activity types
This test course demonstrates all available activity types in the
Machine Spirits LMS. Use it to verify that each activity type works
correctly before deploying to production. Each lecture showcases 2-3
activity types with sample configurations.
-
Instructor
-
Test Instructor
-
Institution
-
Machine Spirits LMS
-
Materials
-
4 public items
-
Credits
-
0
estactivitiesdevelopment
Learning objectives
-
Test all activity types
-
Verify submission handling
-
Check AI integrations
-
Validate progress tracking