Methods Café Course

Through interdisciplinarity, critical thinking, and implementation science, this course focuses on the design and execution of effective, scalable, and enduring solutions to make urban and community environments smarter, healthier, more liveable, and more resilient.

Course Description:  

This course exposes students to novel research from various fields —from computer science to health and nutrition, sociology, marketing, and ecology— to explore complex challenges that urban environments face with regards to food access, mobility, and overall population health. Drawing from Canadian (including First Nations) and global contexts, students will engage in implementation science; this is, they will learn how to move knowledge into action from early stages of conception to execution, testing, scale up, and evaluation. Students will dive into state-of-the-art implementation science methods that range from effective community engagement to computational science. Overall, the course will encourage students to think critically and integrate knowledge and practice to solve complex societal problems and find ways to make cities healthier, more liveable, and more resilient. 

Learning Outcomes

Upon successful completion of this course, students will have demonstrated the ability to:

1. Describe and integrate concepts and perspectives from diverse disciplines that are key to the study of healthy cities and implementation science.
2. Discuss and reflect on the applicability of various implementation science methods to solving challenges in urban environments.
3. Propose solutions to a specific healthy cities problem of their choice, justifying the selection of methods and predicting potential outcomes
4. Showcase leadership and networking skills with peers and instructors.
5. Demonstrate aptitude for interdisciplinary collaboration and co-learning.

Course Topics and Schedule

Week	Topic
Week 1	What is ‘Implementation Science’?
Week 2	Systems Thinking
Week 3	Healthy Cities and Smart Cities
Week 4	Convergence by Design
Week 5	Sex and Gender Based Analysis (SGBA+)
Week 6	Digital Health and Patient Centered Outcomes
Reading Week	Tentative
Week 7	Socio-spatial Epidemiology
Week 8	Introduction to Modelling (Model definitions, concepts, goals, and types)
Week 9	Community-based Participatory Research
Week 10	Introduction to Data Science and AI, Natural Language Processing, Text processing, Data Availability
Week 11	Introduction to Health Economics
Week 12	Design Methods

Testimonials

How to Apply