Write survey items that cover content areas
Survey items are composed of item stems and response sets
When it comes to writing survey items that use Likert scales as response sets, use 5-point Likert scales with increasing order. The 5-point scale is preferable to a 4-point, 3-point, or dichotomous scales because there is more chance for variance with a 5-point scale and there is a "neutral" rating.
Variance in the responses is needed in order to properly assess the diversity that may exist in a population. Increased variance is also important for the underlying mathematics associated with reliability analysis, exploratory factor analysis, validity analysis, and confirmatory factor analysis.
The use of 5-point Likert scales also works well in an aesthetic fashion for structuring a survey. Space and time can be saved in survey administration when items from similar content areas use the same 5-point Likert response set. These questions can be formatted into a matrix.
Finally, increasing order should be used when using a Likert scale, going from left to right.
For example:
Strongly Disagree, Disagree, Neither Agree Nor Disagree, Agree, Strongly Agree
Never, Rarely, Sometimes, Often, Always
Very Poor, Poor, Moderate, Good, Very Good
Variance in the responses is needed in order to properly assess the diversity that may exist in a population. Increased variance is also important for the underlying mathematics associated with reliability analysis, exploratory factor analysis, validity analysis, and confirmatory factor analysis.
The use of 5-point Likert scales also works well in an aesthetic fashion for structuring a survey. Space and time can be saved in survey administration when items from similar content areas use the same 5-point Likert response set. These questions can be formatted into a matrix.
Finally, increasing order should be used when using a Likert scale, going from left to right.
For example:
Strongly Disagree, Disagree, Neither Agree Nor Disagree, Agree, Strongly Agree
Never, Rarely, Sometimes, Often, Always
Very Poor, Poor, Moderate, Good, Very Good
