Detail about what makes a good survey question and how to use them to your advantage.
As part of our reinforcement methodology, we like to use repeating survey questions to measure behavior change.
Asking a question at the beginning of a reinforcement program can have the goal of creating awareness, while the goal of asking the same (repeating) question in a later phase could be reflection.
Each survey needs to be effective and there are certain characteristics they must meet, such as:
- Measurable reinforcement objectives
- Effective survey question design
Reinforcement Objectives in a Survey
Reinforcement objectives are the basis for the survey and represent the need for the questions and measures that will be taken through the survey instrument. By reading the objectives, a participant should be able to identify the measures (or variables) and how best to collect the data.
Reinforcement objectives come in two forms:
- A statement
- A question
Because many of our surveys are used for descriptive purposes, the statement is the most common survey objective. However, there are times when a research question is an appropriate survey objective, particularly when the survey is intended to identify key issues that will ultimately form the basis for greater analysis.
All too often we make decisions based on results derived from the wrong questions. Even if they're the right questions, if they're poorly written the outcome is the same: decisions based on bad questions. Asking the right questions the right way to the right people in the context of an appropriate research framework generates relevant, useable information. But how do we know the right questions?
Writing good survey questions is at the heart of survey design. To create the best survey questions, you need clear objectives that reflect specific measures. You also need a solid research design approach. We often fail to remember that writing the actual survey questions takes time.
Yes, good objectives will lead the way, and if they're SMART reinforcement objectives, the survey questions literally write themselves. But still, to ensure we ask the right questions the right way, we must take a step back and ask ourselves, can the participant really respond to these questions and provide us with the most reliable data possible?
There are two parts to a survey question:
- The stem: represents the variables of interest
- The scale: represents the attributes we give those variables
Together they're the measures of survey objectives.
Writing good survey questions is a balance between art and science. This balance includes understanding various survey research designs and being familiar with the levels of measurement and what you can do mathematically to produce meaning out of each response type. It also includes developing questions so that:
- Responses reflect the data you want
- Participants understand the meaning of the question
- Participants know the answer
- Participants can answer in terms required
- Participants are willing to provide the answer
Data summary is a less intimidating way of referring to data analysis. However, if you collect survey data, you will analyze it. But fear not, it doesn't have to be difficult. Many of the surveys used in reinforcement programs lend themselves to simple descriptive statistics.
While many organizations are advancing their capabilities in more complex analytics, most survey data captured for reinforcement can be summarized using basic statistical procedures. Credible qualitative analysis can be done by simply categorizing words into themes. The Mindmarker analytical tool presents your survey results so that they're meaningful and useful.
Tip: A good survey is one where the final results are reported in such a way that the stakeholders immediately 'get it.'