AI Summary
[DOCUMENT_TYPE: syllabus]
**What This Document Is**
This is a syllabus for a graduate-level course focused on Meta-Analysis, offered within the Evaluation program at Western Michigan University. It outlines the structure, expectations, and learning objectives for a semester-long exploration of research synthesis techniques. The course delves into the methodologies used to systematically combine findings from multiple studies to arrive at more robust conclusions. It’s designed for students seeking advanced training in applied research and evaluation.
**Why This Document Matters**
This syllabus is essential for prospective students considering enrollment in EVAL 6970. It’s also valuable for researchers and practitioners interested in understanding the scope and depth of a rigorous meta-analysis training program. Anyone looking to build expertise in evidence-based practices, policy evaluation, or advanced quantitative analysis will find this overview helpful in determining if the course aligns with their professional development goals. Understanding the course’s focus will help you assess if your existing skillset meets the prerequisites for success.
**Common Limitations or Challenges**
This syllabus provides a high-level overview of the course. It does *not* contain the specific readings, assignments, or datasets used throughout the semester. It also doesn’t offer detailed instruction on *how* to perform meta-analytic techniques – that content is delivered within the course itself. The syllabus also doesn’t provide a substitute for a foundational understanding of statistics and research design.
**What This Document Provides**
* A detailed course description outlining the core topics covered.
* Information regarding course logistics, including meeting times and location.
* Instructor contact information and office hour policies.
* A comprehensive list of student learning objectives, detailing the skills students will develop.
* An overview of required resources, including textbooks and supplemental readings.
* Prerequisite recommendations to ensure student preparedness.
* A description of the software utilized in the course.