Yale Center for Teaching and Learning

Program Assessment

Program evaluation looks at the parameters, needs, components, and outcomes of program design with an eye towards improving student learning. It involves a complex approach, taking into consideration needs assessment, curriculum mapping, and various models of program review.

Program Assessment

Program evaluation is the process of systematically collecting, analyzing, and using data to review the effectiveness and efficiency of programs.

Needs Assessment

The goals of a needs assessment include: examining how an initiative is functioning in relation to its goals or objectives, determining the current status of operations, or deciding what future direction the program might take.

Curriculum Mapping

Curriculum maps identify when and how various skills, content, and objectives are addressed across multiple courses. A curriculum map helps instructors and adminstrators determine how to modify instruction or program requirements to ensure that the curriculum has the appropriate breadth and depth.

Program Review

Program review at institutions became widespread in higher education in the late 1960s as a formal data collection method to inform decision making on resource allocation and setting priorities, to assist in starting up or sunsetting programs or courses, or to determine modifications for alignment with institutional strategic planning.

Kirkpatrick Model

The Kirkpatrick Model is one of the most widely used methods for evaluating the effectiveness of training programs, and has a review-oriented approach to evaluating what occurred and what the end results of training were.

CIPP Model

The CIPP model was created in the 1960s by Daniel Stufflebeam and is considered a decision-oriented model that systematically collects information about a program to identify strengths and limitations in content or delivery, to improve program effectiveness or plan for the future of a program.

SEP Model

SEP was developed in 2012 as a standardized protocol developed primarily in relation to STEM education programs, and draws on literature from evaluation theory, systems theory and evolutionary epistemology.

Data Collection

In program evaluation, measurement methods are best categorized into direct and indirect measures. Both measures can provide a more holistic view of the impacts of a program. There are also four common types of data that are analyzed in educational research and evaluation: observations, artifacts, historical or institutional records, and self-report.