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Business Application 1. In this white paper we present a model of personal knowledge which is based on the number of dots the person can see, and thus the dimensions of knowledge. E.g. one dot indicates di-mensionless knowledge, two dots indicate one-dimensional knowledge, then the three dots for two-dimensional knowledge, and the highest knowledge level is the three-dimensional knowl-edge indicated by four dots. Based on qualitative examination of this model we determine which part of deliverable knowledge is appropriate for e-learning at the different knowledge levels of the teacher.
2. Our solution – MABE Methodological Framework – aims to understand Value-Based Learning Organizations. The e-leaders (decision takers of these organizations) can only communicate using a hazy hierarchy of metaphors as the new ideas cannot be expressed using the old terminology. They and their organizations exist in a business world, in which the functioning is dominated by software; the employees are expected to be skilled searchers. We assume that the decision takers can change their attitude towards the set of expectations and their relations when facing a new solution; thus, they can achieve to get an objectionless solution. This requires a new mode of cognition, which we call the opportunistic browsing. Furthermore, they have to ensure that the decision they have taken is ethically correct, and as there is no single truth they need to adopt pluralistic ethics. The established framework is used to analyze the decisions of the e-leader, who keeps the original decisions to herself/himself and delegates the routine ones, thus achieving increased efficiency and effectiveness resulting in cost reduction and time savings. 3. Making an attempt to develop a curriculum for web-based learning, we have realized that the existing solutions have adopted the traditional content management principles of printed books. By doing so, these solutions do not make use of benefits of a web-based system, namely the multimedia and the interactivity. Our new solution puts these benefits into the focus. Combining the features of semantic networks, cognitive maps and machine learning, we have developed a new generation knowledge visualization tool called Doctus Knowledge Galaxy shell. In our solution the topics and keywords are not in a sequential order, thus ena-bling the e-learner to choose her/his own learning route. The monitoring system of Doctus Knowledge Galaxy also allow us to observe how much time the learner spends on particular keywords and which next keyword she/he chooses after concluding a previous one by passing the test. The most important achievement of Doctus Knowledge Galaxy is its clear and trans-parent structure, which enables the learners into fast navigation and provides the developers with useful information about the learning routes and performance of the learner. 4. Today one of the most challenging problems of an organization is how to make the decision taking faster in order to improve efficiency. Excellence resides in the differences of people’s tacit knowledge. In Knowledge Management excellence can be achieved if the leader delegates the Routine Decisions to others, while the Original Decisions are taken on basis of tacit knowledge. With Expert System Shell DoctuS, we can reduce the expressed rules to those meta-schemata that actually affect the decision. These meta-schemata are derived from a blend of explicit and tacit knowledge. The process of reducing the number rules we call reduction, which is the third kind of reasoning beside deduction and induction. The achievement is that we can get the same decision using the values of fewer attributes. According to our experience the benefits include knowledge discovery in every application (i.e. a part of tacit knowledge is made explicit) and the process of decision taking becomes faster and its cost is reduced. 5. Many practising Knowledge Engineers feel that being familiar with knowledge-based systems is not enough for knowledge building from the information angle. We have put our, for a knowledge engineer defined, features and their degrees into the inductive learning of Doctus KBS combined with the expertise of our knowledge engineer colleagues. The outcome is stunningly simple. Paying attention and emotional consciousness, as features are the most informative. [full abstract] [full text.pdf]
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