The GREW Project’s resource library contains more than 40 examples of survey tools, reports, assessments and logic models being used by organizations serving beginning farmers and ranchers. Many of these tools and resources are easily adapted to evaluating other types of sustainable agriculture education programs and projects.
This online tool from Custom Insight will help you calculate how many people you need for a random sample. It provides calculators to help you determine how many survey respondents are needed, how many people you need to send the survey to, and to determine the accuracy of your survey results.
This 2020 guide is designed to help staff at beginning farmer and rancher (BFR) training organizations identify practical outcomes for program evaluation. It provides examples of outcomes, indicators and data collection questions to assist with the development and implementation of a meaningful evaluation plan. Examples are provided for production, marketing, business and financial, land access, succession, labor financing and materials, community support topics. Many of the examples are relevant to and easily adaptable to other types of farmer education programming.
Self assessment can help learners more clearly identify their learning needs at the beginning of a program, create their own learning plans to meet these needs, and monitor changes in their knowledge and skills over time. This webpage provides resources for learning about and using self assessment in beginning farmer programs.
While oriented to proposals to the USDA Beginning Farmer and Rancher Development Program (BFRDP), the key points are applicable to developing an outcome focused evaluation plan for any project or initiative.
This webpage from the Graining Results through Evaluation (GREW) project provides several resources help with follow up evaluation, including webinars, data collection tools, and budgets. Resources are geared to beginning farmer programs, but are easily adaptable to many other farmer education and training programs.