This year, REC blogs will focus on how to increase response rates. In the past, we explored Data Collection Methods and Collecting Quality Data, but how do you make sure you are capturing data that truly reflects the experiences of the people you serve? This blog series will describe how to reach your target audience, […]
How to Increase Response Rates with These Expert Tips: 2024 Blog Series Read More »
Surveying children is necessary for planning and evaluating youth programs. However, it can also present unique challenges from those encountered when surveying adults. It is important to understand what to avoid and what to implement when surveying youth so that you can get better response rates and data. 4 Dos and Don’ts to guide you
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In our last post we discussed different survey mistakes, now we provide some solutions to these common survey mistakes! Please note that it is always important to consider organizational and evaluation goals when creating surveys. Know that these are simply a few of the ways to avoid common survey mistakes. Mistake #1: Using All Qualitative
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Surveys are an excellent source of information that help organizations understand the communities they serve. Unfortunately, not all surveys generate quality data due to common survey mistakes and ineffective survey designs. Here are 6 survey mistakes that organizations commonly make: Mistake #1: Using All Qualitative or All Quantitative Questions Using all qualitative or quantitative survey
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Surveys are fantastic tools for evaluation. They help your organization determine what is working, what can be improved, and provide information to tell your story of impact. Surveys also allow for more complex analyses using descriptive and inferential statistics. This blog provides 5 tips for creating a survey when your organization is ready for evaluation and
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Two Types of Data When people discuss data, they typically describe it as either quantitative or qualitative. Yet, what is quantitative data? What is qualitative data? How are these two types of data different? Is one type of data better to use than the other? Why should this topic matter to purpose-driven organizations? This blog
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