# Introduction to Program Evaluation Course (Self-Paced)

Canonical URL: <https://www.graduateschool.edu/courses/introduction-to-program-evaluation-course-self-paced>

## Overview

Evaluation identifies, discovers, generates, and displays information about an organization's program effectiveness. The information shows what the organization produces, how those products affect society, and how much the effect is worth. Budget hearings before Congress, as well as OMB, often require information generated by evaluations. Legislation commonly requires a formal evaluation of some type as a condition for a program's existence or funding. Learn to describe programs, identify information useful in evaluation, collect reliable data, and analyze it effectively.

## What you'll learn

- Identify and apply critical elements of the evaluation process.
- Identify the phases of research design.
- Evaluate the strengths and weaknesses of different data-gathering techniques.
- Interpret statistical data.
- Identify the costs and benefits of a program.

## Curriculum

#### Module 1: Introduction to Program Evaluation

- Understand the definition, purpose, and scope of program evaluation.
- Differentiate between formative, process, and summative evaluations.
- Identify stakeholders, evaluation questions, and intended uses of evaluation results.
- Review ethical considerations and professional standards in evaluation practice.

#### Module 2: Data Collection

- Explore various data sources, including qualitative and quantitative methods.
- Understand the strengths and limitations of surveys, interviews, focus groups, and observation.
- Plan data collection strategies that align with evaluation objectives.
- Address issues of data quality, reliability, and validity.

#### Module 3: Evaluation Design

- Examine experimental, quasi-experimental, and non-experimental designs.
- Select designs appropriate for program context and resources.
- Understand threats to internal and external validity.
- Plan for feasible, rigorous, and ethical evaluation implementation.

#### Module 4: Sampling

- Understand probability and non-probability sampling methods.
- Determine appropriate sample size for evaluation purposes.
- Address representativeness, bias, and sampling error.
- Apply sampling strategies to various evaluation scenarios.

#### Module 5: Data Analysis

- Apply descriptive statistics to summarize data (measures of central tendency and dispersion).
- Use inferential statistics to test hypotheses and determine significance.
- Interpret findings in the context of evaluation questions and program goals.
- Communicate results effectively to stakeholders.

#### Module 6: Cost-Benefit Analysis

- Understand the principles and steps of cost-benefit analysis in program evaluation.
- Identify and quantify program costs and benefits.
- Calculate cost-benefit ratios and interpret results for decision-making.
- Recognize the limitations and challenges of applying cost-benefit analysis.

## Pricing

**Tuition:** $1629