How do we know what we know? What is truth? What is reality? Is there one reality or they are multiple realities? What is objective reality? What is a subjective reality?
It seems that the answers to these questions are found in models of thinking that each of us adopted. The philosophers are those who influenced our world perceptions, our ways of thinking and ways of application of our thoughts. They engaged us, for centuries, with questions about the reality in which we live.
Trying to understand the reality stems from the desire to control situations of life. Control over life situations allows us to reduce the sense of uncertainty of existence and realization of human desires (Arieli, 1992). However, the development of science and technology have created two paradoxes: The first reflects the gap between sophisticated methods of gathering information and the ability to understand the events and processes taking place before our eyes;
Second, lies in the fact that the uncertainty and the inability to predict the future is growing at a time when we have almost unlimited possibility to accumulate and analyze data simultaneously with contemporary processes and events.
Organization of knowledge is based on thinking models, organized by categories, that enable guided approach to complex questions which every scientist is trying to answer. Distinct using of thinking models expresses the nature of knowledge, the way knowledge is organized and the way the knowledge is implemented by different scientist that depend on various thinking models. Guba & Lincoln (1994) see thinking modelsas basic belief system (or metaphysics) which represents a set of world perceptions of a person and the range of possible relations with this world and its parts.
Choosing a way of thinking would be simple if living conditions were fixed and not variable. But the reality is that not all relevant information is in our hands, and the information in our hands is quite confusing and not necessarily relevant (Bhatnagar & Kanal, 1992). When we are in such a situation we are building data networks, or models, by choosing the less accurate ideas. In practice, instead of disabling certain input we are trying to find a little less accurate version of the model which can be included in the input. Such way of thinking is called “approximate reasoning”. Such thinking is expressed through vague thinking.