Choice of the survey question types used in a questionnaire is a critical design decision. Survey question type determines the type of data generated, which in turn determines the type of analysis you can do with the survey data collected. No one best survey question type exist. The appropriate question type will be one that best generates valid, reliable data to answer your research question.
Design of interval scales for surveys is a vital part of survey questionnaire design. How many points on the scale, odd number or even number, presenting the scale from high to low versus low to high, endpoint anchoring or fully anchoring each scale point are all design issues. Most important is the choice of anchors, which are those terms that describe the dimension of measurement. Importantly, a scale designed for American English audiences must be localized for other variations of the mother tongue.
We practice scale design in my survey workshops, and in a recent workshop, one attendee decided to create a localize scale for measuring relevancy, in this case for Texas: (my apologies in advance for offending anyone’s sensitivities.)
I leave it to you to add in the proper Texan accent!
A Minnesotan colleague has submitted these for the quality of service dimension:
A Massachusetts friend added these:
For non-Bostonians, “Stahted” translates to “Started”.
Have one to submit? Contact us!
The choice of a survey scale impacts setting performance goals. Scale choice and question wording will affect the way people respond. The article also discusses why (artificially) high scores are not necessarily good — if your goal is to use the survey results for continuous improvement projects, requiring Pareto Analysis.
Frequently, when business surveys try to measure importance of various factors the survey generates useless data. Everything gets rated as important, so nothing is important. This article covers methods of measuring importance showing the advantages and disadvantages of each. The key is getting the respondent to think about the trade-offs across the factors.