Course Syllabus

Prerequisites: None 

 

Healthy Societies: Using Survey Data to Understand Well-Being

 

This is a draft syllabus 

Course Description

In this project-based course you will explore pressing public health and social questions. You will learn to use publicly available surveys as a tool for discovery, identifying patterns, testing ideas, and evaluating evidence on issues that matter to you. No prior experience with survey data is required. You will select your own research questions related to health, well-being, education, or social equity. By semester’s end, you will understand how data shape decisions about health and social policy in different cultural contexts and gain transferable skills in data literacy and applied research.

 

Expected Learning Outcomes

After successful completion of this course, you will be able to:

• Develop evidence-based questions about health, education, or social well-being
• Conduct literature reviews and situate questions in European and global contexts
• Apply data reasoning to describe patterns, test hypotheses, and interpret results
• Communicate findings clearly through writing, visual displays, and oral presentations
• Critically compare European and U.S. approaches to public health and social policy

 

Faculty

Lisa Dierker, PhD Wesleyan University

Readings

Key Readings

• Primary-source journal articles related to each student’s topic

Data Sources

• European Social Survey (ESS)
• Eurostat Public Health Indicators
• Scandinavian national health and education registries
• U.S National Epidemiological Survey of Alcohol and Related Conditions

 

Field Studies

Two field studies will take place during the semester. Field studies are typically a half-day excursion.

Potential Field Studies may include visits to institutions such as

• Danish National Research Centre for the Working Environment – How data are used to protect workers’ mental and physical health
• Local NGOs and Public Health Organizations – How community data inform prevention, outreach, and education

 

Approach to Teaching

TBA

Expectations of the Students

TBA

 

 

Evaluation and Grading

To be eligible for a passing grade in this class, all of the assigned work must be completed. Please note that 'extra credit' or 'make-up work' is not possible in this course.

The factors influencing the final grade and the proportional importance of each factor is shown below:

 

Component	Weight
Journal Entries & Project Components	50%
Research Plan (literature review, design, methods)	15%
Quizzes (application-based, open-data exercises)	10%
Poster & Oral Presentation	15%
Engagement (attendance, site visits, cross-cultural reflection)	10%

 

Further description of each component is TBA 

 

Policies

Attendance

You are expected to attend all DIS classes and activities when scheduled, and I will monitor attendance. Absences will jeopardize your grade and your standing at DIS. Excused absences include only serious illness and participation in religious holidays.

If you miss multiple classes, the Director of Academic Support, and the Director of Student Affairs will be notified and they will follow-up with you to make sure that all is well. In the case of multiple absences, you will need to provide a doctor’s note.

Missing class: You must always notify your instructor about an absence a reasonable time in advance.

Example Weekly Schedule

(Each week centers on a question students learn to answer with data.)

• Week 1: What can data tell us about health and society?
  • Introduction to the course and European data sources; pre-course survey.
• Week 2: How do we turn a social concern into a research question?
  • Literature review; defining measurable outcomes and comparisons.
• Week 3: Where does health data come from, and how do we prepare it for analysis?
  • Data management workshop; understanding variables and missing data.
• Week 4: How can visualization reveal inequities or patterns in well-being?
  • Exploratory data analysis and visualization.
• Week 5: How do workplace and environmental factors shape public health?
  • Site visit: Danish National Research Centre for the Working Environment.
• Week 6: How do we test whether differences and associations are meaningful?
  • Inference for health and social indicators.
• Week 7: How do factors like gender, income, or policy interact to affect outcomes?
  • Moderation and regression models; registry data applications.
• Week 8: How do health and social outcomes compare across countries?
  • Cross-national data comparisons using European survey data.
• Week 9: How do we communicate evidence to policymakers and the public?
  • Poster design workshop; drafting results and implications.
• Week 10: How do we refine our analyses and tell a clear story with data?
  • Peer review and revision of posters; reflection journals.
• Week 11: How do NGOs and community organizations use data to drive change?
  • Site visit: local NGO; discussion with practitioners.
• Week 12: What have we learned about using data for the public good?
  • Final poster presentations and reflections linking study abroad experiences to data-driven inquiry.