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 evaluation methodologies within public health contexts.
Why This Document Matters
This syllabus is crucial for anyone considering enrolling in PM 536, or for current students seeking 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 referencing it throughout the semester to stay informed about assignment deadlines, exam dates, and the overall progression of topics. Individuals interested in the core principles of program evaluation, even outside of a formal course setting, may find the outlined learning objectives and topics valuable for self-study.
Common Limitations or Challenges
This syllabus provides a high-level overview and does *not* contain the actual course readings, lecture materials, data sets used for analysis, or specific assignment instructions. It details the *types* of assessments and the weighting of grades, but doesn’t reveal the questions or criteria used for evaluation. It also doesn’t offer completed examples of evaluations or analyses. Access to the full course content requires enrollment and purchase.
What This Document Provides
* Instructor and Teaching Assistant contact information
* A clear course description outlining the focus on health promotion program evaluation.
* Defined learning objectives, detailing skills students will develop.
* A breakdown of grading components and their respective weights.
* A week-by-week course outline, indicating key topics to be covered.
* A list of required texts and resources.
* Information regarding the use of statistical software for data analysis.