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Program evaluation models and related theories: AMEE guide no. 67.

Ann W Frye¹, Paul A Hemmer

¹Office of Educational Development, University of Texas Medical Branch, 301 University Boulevard, Galveston, Texas 77555-0408, USA. awfrye@utmb.edu

Medical Teacher

|April 21, 2012

Summary

This summary is machine-generated.

Understanding the theoretical underpinnings of educational evaluation models helps educators select appropriate tools for program improvement. This guide connects scientific theories to common evaluation models for confident application.

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Area of Science:

Educational research methodology
Philosophy of science
Program evaluation theory

Background:

Common educational evaluation models are influenced by scientific theories.
Educators need to understand theoretical bases to select appropriate evaluation models.
Theories like reductionism, system theory, and complexity theory have shaped evaluation approaches.

Purpose of the Study:

To review scientific theories influencing educational evaluation models.
To enhance educators' confidence in choosing and applying evaluation models.
To guide educators in designing evaluations that support program improvement and document outcomes.

Main Methods:

Review of scientific theories (reductionism, system theory, complexity theory).
Description of common evaluation models (experimental, quasi-experimental, Kirkpatrick's, Logic Model, CIPP).
Analysis of how theoretical influences shape model utility and limitations.

Main Results:

Evaluation models are directly linked to underlying scientific theories.
Understanding theoretical foundations aids in matching models to program complexity and evaluation needs.
Specific models discussed include experimental, quasi-experimental, Kirkpatrick's, Logic Model, and CIPP.

Conclusions:

Educators can improve program evaluation by considering theoretical underpinnings.
Matching evaluation models to program complexity and needs enhances effectiveness.
This guide aims to build educator competence in designing impactful program evaluations.