What This Document Is
This is a detailed syllabus for PM 536: Program Evaluation, a graduate-level course offered at the University of Southern California’s Keck School of Medicine. It outlines the structure, expectations, and core components of a semester-long exploration into the field of health program evaluation. The syllabus provides a comprehensive overview of the course’s administrative details, learning objectives, and weekly schedule. It’s designed to equip students with a foundational understanding of how to assess the effectiveness of public health initiatives.
Why This Document Matters
This syllabus is crucial for anyone considering enrolling in PM 536, as well as students already registered who need a clear roadmap for the course. Prospective students can use it to determine if the course aligns with their academic and professional goals. Current students will benefit from regularly referencing it to stay on track with assignments, readings, and exam dates. Individuals interested in the core principles of program evaluation within a public health context will also find the outlined learning objectives valuable for understanding the scope of the field.
Common Limitations or Challenges
This syllabus provides a high-level overview of the course. It does *not* contain the actual course readings, lecture materials, data sets used for analysis, or specific assignment instructions. It also doesn’t offer detailed explanations of evaluation methodologies or statistical techniques – those are explored within the course itself. The syllabus outlines the topics covered each week, but doesn’t provide the in-depth analysis or practical application of those concepts.
What This Document Provides
* Instructor and Teaching Assistant contact information
* A clear description of the course’s focus on evaluating health promotion programs.
* Defined learning objectives outlining the skills students will develop.
* A breakdown of grading components and their respective weights.
* A week-by-week course outline indicating key topics and associated readings.
* Information regarding required texts and supplementary materials.
* Details on the use of statistical software for data analysis.