The software "Making Choices" was developed as a result of a long term interest in modelling software that we shared and a dissatisfaction with the mathematical and quantitative nature of much of the software available. Most software does not allow the modeller to design a model which is simple enough to match the weak knowledge available about the matter under consideration. In general, quantification can only be successful in situations where it is possible to measure on some kind of scale. The fine detail and hard mathematical laws of the real number scale make it inappropriate and misleading where all that you can actually measure is the order of elements in a model in relation to each other. An example of the kind of problem where this approach is useful are those where a decision between alternative choices has to be made and where the choices are capable of being ranked in relation to some factors on the basis of subjective judgment.
In looking for resources which can help people to learn about such problems we found a range of software to support decision making activities, such as the Computers in the Curriculum Geography program "Choosing Sites"  - an inspiration for this work, The Careers and Occupational Information Centre's "Resolve" software , The Work Sciences Associates "Priority Decision System" and the Institute of Educational Technology's software "WOMBAT" .
All of these decision support systems expect users to make judgments about choices using numerical scales of measurement (Ratio scales or Interval scales in statistician's terms). In creating Making Choices we deliberately tried to avoid numbers by designing a graphical user interface to support Ordinal scales for judgments about choices (in plain words, you move the choices into relative position to indicate their value). The reason for this is that the information available is frequently not enough for making a precise judgment with a number (and if do give struggle for a number, is it appropriate?).
So we designed Making Choices particularly for decision making problems where it is impossible or inappropriate to make numerical measurements.