Evaluation Manual

Financial Education Evaluation Design and Data Collection 

After developing a logic model and evaluation questions, the next step is to finalize the evaluation design and data collection.

Section Summary

Primary Sections Section Summary

What type of evaluation should be conducted?

The evaluation questions and priorities should inform the type of evaluation conducted. A good evaluation design addresses the evaluation questions, is appropriate for the evaluation context (e.g., time, resources), and provides sufficient and critical data. Evaluations commonly conducted by financial educators likely will employ descriptive or correlations designs.

What type of data should be collected?

It is most beneficial to collect both qualitative and quantitative data during the evaluation so these data sources can be used in conjunction to develop a clear and accurate answer to the evaluation questions.

Who should be a part of the evaluation study sample?

The educator will need to decide who is available to participate in the evaluation and how many participants are feasible based on the evaluation timeline and budget. Prior to conducting the evaluation, the educator should plan who will provide data for the evaluation, and how to gain access to data for these participants.

What evaluation methods should be employed?

Formative evaluations typically employ observations, attendance analyses and surveys to clarify the presence and quality of early components of the logic model, including adequacy of resources, needs of the target population, fidelity (or conformity to the curriculum/programs as developed), and quality of implementation. Summative evaluations typically focus on participant outcomes, so it is common to employ surveys, tests/assessments, financial indicators, and focus groups or interviews.


The quality of the evaluation design and data collection plan largely determines the quality of the evaluation data gathered. The following factors are important guidelines in designing evaluations and creating data collection systems.