Milan Houška

Computer supported knowledge in distance learning

Knowledge is crucially important both in organizations and in schools. Different models have been created for varied environments and purposes. The paper deals with several models of knowledge with the aim to construct a simple model which can be used for design and management of distance courses in higher education. The model consists of several parts: Problem definition, Involvement, Exploitation of existing sources, Implementation of new ideas, Course design and Practical Application. The conception of a knowledge life cycle and necessary transformation of tacit and explicit knowledge is substantial for the model. An example of practical implementation in Moodle platform is embodied

Towards the definition of knowledge interoperability

The paper deals with different approaches to the definition of knowledge interoperability. The aim of the paper is to define the process of a knowledge transfer, well-known also as knowledge interoperability. The definition of knowledge interoperability is based on the understanding of knowledge as a tool for problem solving. The knowledge interoperability is the transfer of knowledge between heterogeneous environments and it is a powerful tool for the acquisition of new knowledge. In this paper, we suggest unified processes of the knowledge interoperability for well-structured, ill-structured and unstructured problems based on soft systems approaches. We specify four cases of a problem situation and describe procedures for their conversion in order to unify the knowledge interoperability process.

The conversion of cost and benefit criteria in the TOPSIS method

Multiple attribute decision making (MADM) models involve both cost and benefit criteria. However, it is convenient to unify criteria type; this means to convert the cost criteria into benefit criteria or vice versa. There are several procedures for criteria type conversion. Unfortunately, these procedures are usually outside of the MADM methods’ algorithms and some combinations of criteria type conversion method and the MADM method provide incorrect results. We focus on the method ‘technique for order preference by similarity to ideal solution’ (TOPSIS method) and the subtraction-based conversion procedure, which converts criterion type using the differences between criterion values and the maximum value in the criterion column. We find that this widely used procedure for criteria conversion can completely distort the results of the analysis. In this paper, we suggest a new subtraction-based conversion procedure that is possible to combine with the TOPSIS method and receive correct results.

Unary operations with Knowledge Units

The term “Knowledge Unit” is being used in more branches of sciences dealing with knowledge such as knowledge management, knowledge engineering, but also in education and pedagogical sciences. Unfortunately, no generally accepted definition of this term has already been established. In our previous work, we defined the Knowledge Unit and its standard structure based on systems approach. The objective of the paper is to suggest such operations, which allow to the users with different initial knowledge work with these knowledge units. For this purpose, we arise from a formal definition of the knowledge unit and then we suggest unary operations for these units in order the users are able to change their level of detail. All operations will be demonstrated on illustrative examples.