Scaling is the process of assigning numbers or other symbols to an attribute or characteristic for the purpose of measuring that attribute or characteristic. Scales are often arbitrary and may not be unique. For example, temperature is measured in a number of ways; the two most common are the Fahrenheit scale (where water freezes at 32 degrees and boils at 212 degrees) and the Celsius scale (where freezing occurs at 0 degrees and boiling at 100 degrees).
There are two different forms of measurement scales commonly used by systems analysts:
- nominal scales and
- interval scales.
Nominal scales are used to classify things. A question such as:
What type of software do you use the most?
- = A Word Processor
- = A Spreadsheet
- = A Database
- = An Email Program
uses a nominal scale. Obviously, nominal scales are the weakest forms of measurement. Generally, all the analyst can do with them is obtain totals for each classification.
Interval scales possess the characteristic that the intervals between each of the numbers are equal. Due to this characteristic, mathematical operations can be performed on the questionnaire data, resulting in a more complete analysis. Examples of interval scales are the Fahrenheit and Celsius scales, which measure temperature.
The foregoing example of the Information Center is definitely not that of an interval scale, but by anchoring the scale on either end, the analyst may want to assume the respondent perceives the intervals to be equal:
How useful is the support given by the Technical Support Group?
If the systems analyst makes this assumption, more quantitative analysis is possible.
Validity and Reliability
There are two measures of performance in constructing scales: validity and reliability. The systems analyst should be aware of these concerns.
Validity is the degree to which the question measures what the analyst intends to measure. For example, if the purpose of the questionnaire is to determine whether the organization is ready for a major change in computer operations, do the questions measure that?
Reliability measures consistency. If the questionnaire was administered once and then again under the same conditions and if the same results were obtained both times, the instrument is said to have external consistency. If the questionnaire contains sub-parts and these parts have equivalent results, the instrument is said to have internal consistency. Both external and internal consistency are important.
The actual construction of scales is a serious task. Careless construction of scales can result in one of the following problems:
- Central tendency.
- Halo effect.
Leniency is a problem caused by respondents who are easy raters. A systems analyst can avoid the problem of leniency by moving the “average” category to the left (or right) of center.
Central tendency is a problem that occurs when respondents rate everything as average. The analyst can improve the scale (1) by making the differences smaller at the two ends, (2) by adjusting the strength of the descriptors, or (3) by creating a scale with more points.
The halo effect is a problem that arises when the impression formed in one question carries into the next question. For example, if you are rating an employee about whom you have a very favorable impression, you may give a high rating in every category or trait, regardless of whether or not it is a strong point of the employee’s. The solution is to place one trait and several employees on each page, rather than one employee and several traits on a page.
- Interviewing in Information Gathering
- Five Steps in Interview Preparation
- Open-Ended and Closed Type Interview Questions
- Arranging Interview Questions in a Logical Sequence
- Joint Application Design (JAD) in Information Gathering
- Using Questionnaires in Information Gathering
- Writing Questions for Questionnaires
- Using Scales in Questionnaires
- Designing and Administering the Questionnaires