Learning patterns/Using ordered response scales

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Using ordered response scales

problemSurvey questions often ask for ordered responses, but it can be hard to think of them on the spot

solutionUse these example responses scales for your surveys

creator• EGalvez (WMF)

created on20:23, 3 June 2016 (UTC)

status:DRAFT

What problem does this solve?

Survey questions often ask for ordered responses. These are questions that have responses like: strongly agree/strongly disagree, or Very important/Not important. These can be hard to think up when you are doing a survey.

What is the solution?

Researchers have done a lot of research on this topic and there are responses that are often accepted as established. View the list below to find responses that work for you! Note: If the words do not translate well from English into another language, use number scales instead of words. See this learning pattern. --learning pattern needed-- for more information.

Dichotomous (Forced –choice or anchor points)

NOTE: Dichotomous pairs are not recommended for most survey questions. These options should only be used for filtering people to the right questions (e.g. did you attend the event? Yes/No), or for voting. You should often include "not sure/don't know" or "not applicable" as an option as well for these lists."

Fair	Unfair
Agree	Disagree
True	False
Yes	No
Pass	Fail
Minimally	Maximally
Not at all	Completely

Three-point scales

Agree	Neither agree nor disagree	Neutral Disagree
More than I would like	About right	Less than I would like
Too harsh	About right	Too lenient
Too heavy	About right	Too light
Too much	About right	Too little
Not at all	Moderately	Extremely
Too Strict	About right	Too lax
None	Some	A lot
Increased	No Change	Decreased
Improved	Stayed the same	Digressed
Not at all	Occasionally	Frequently

Four-point Scales (Forced -choice)

Poor	Fair	Good	Excellent
Most of the time	Some of the time	Hardly ever	Very seldom/Never
Strongly agree	Agree	Disagree	Strongly disagree
Exceeded	Met	Nearly met	Missed
Below standard	Approaching standard	At standard	Above standard
Definitely will not	Probably will not	Probably will	Definitely will
Not important	Somewhat important	Very important	Essential
None	Little	Some	Substantial
Not at all	Not very well	Fairly well	Very well
A lot	Quite a bit	A little	None

Five-point Scales

Excellent	Above average	Average	Below average	Very poor
Much better	Somewhat better	Stayed the same	Somewhat worse	Much worse
Much stronger	Somewhat stronger	No change	Somewhat weaker	Much weaker
Strongly agree	(Somewhat) Agree	Neither agree nor disagree/Neutral	(Somewhat) Disagree	Strongly disagree
Very high	Above average	Average	Below average	Very low
Way too little	Too little	About right	Too much	Way too much
Far too little	Too little	About right	Too much	Far too much
Much higher	Somewhat Higher	About the same	Somewhat lower	Much lower
Not at all	Slightly	Moderately	Mostly	Completely
One of the best	About average	Average	Below average	One of the worst
Completely satisfied	Very satisfied	Fairly well satisfied	Somewhat dissatisfied	Very dissatisfied
Very satisfied	Satisfied	Neither satisfied nor dissatisfied	Dissatisfied	Very dissatisfied
Almost always	Often	Sometimes	Seldom	Never
Always	Very often	Fairly many times	Occasionally	Never
All of the time	Most of the time	Sometimes	Rarely	Never
All	A lot/ An extreme amount	Quite a bit	A little/ Some	None
Very good	Good	Fair	Poor	Very poor
Very often	Regularly	Sometimes	Once or twice	Never
Very important	Quite important	Fairly important	Slightly important	Not at all important
Not like	Somewhat	Moderately	Very much	Totally
Definitely True	True	Do not know	False	Definitely false
Severe	Moderate	Mild	Very mild	None

Six-point Scales (Forced -choice)

Always	Very often	Fairly often	Sometimes	Almost never	Never
Always	Most of the time	Often	Occasionally	Rarely	Never
Completely satisfied	Very satisfied	Somewhat satisfied	Somewhat dissatisfied	Very dissatisfied	Completely dissatisfied

Seven-point Scales

Very dissatisfied	Moderately dissatisfied	Slightly dissatisfied	Neutral	Slightly satisfied	Moderately satisfied	Very Satisfied
Far below	Moderately below	Slightly below	Met expectation	Slightly above	Moderately above	Far above
Very poor	Poor	Fair	Good	Very good	Excellent	Exceptional

Words to watch out for

The following words can bias scale if not careful to balance depending on number of responses:

• Slightly vs. Somewhat
• Very/Extremely
• Completely/Totally
• Excellent vs. Exceptional

Scales for international use

Translating these scales into another language can be very challenging. There are always slight differences in the meanings of words based on the language and culture. If a survey is being translated or used in multiple countries, it is best to use a number scale and show the extremes only. For example:

• 0 - Very poor
• 1
• 2 - Average
• 3
• 4 - Excellent