Abstract
The concept of education using an evolutional-activity approach is presented. This approach resolves the problem of continuous self-development of specialists in their professional activity. The conformity of their evolution to individual and social changing needs is supported by development of skills for reliable generation of a new valuable knowledge in the right time and in the right place of the professional space. This new knowledge becomes a basis for generation of time- and energy-effective engineering solutions, including unique ones. The novelty of the proposed approach comes from the establishment of an axiomatic basis. The core categories of the basis are activity classes. The whole conceptual framework and fundamental laws are represented as consequences of initial axioms and postulates of the basis. This approach allows the higher education pedagogy to overcome the conceptual crisis, which resulted from the variety of existing conceptual frameworks.
TopBackground
Explicit modeling, as a method of scientific cognition, has the following notable feature. In phenomena under study, only essential things are modeled. A model should incorporate main characteristics, parameters, and their interrelations, so it can facilitate deeper understanding of a phenomenon. This is the outline of the conventional approach of explicit modeling.
The main drawback of the conventional deterministic decomposition method is unacceptability of losses, even of insignificant elements in the coefficient matrix of the equation system. In the selection processes, the processes of choosing the important things and eliminating the insignificant ones, according to defined criteria, are necessary. The implementation of this approach by a learning system in the real world is not effective due to difficulties to adaptation and flexibility.
Human intelligence, as a complex self-learning system, is exhibited in the following abilities.
- 1.
The ability to learn, including information acquisition from direct interaction with the outer world, integration of the information into the internal model, and achievement of understanding (i.e. perform connection of the acquired knowledge with facts and phenomena of reality). The learning aptitude is related to the desire for a system to permanently improve the internal model of the external world.
- 2.
The ability to manage the mental activity, that is, the ability to abandon conventional patterns and find new, actual, specific relationships.
- 3.
The ability to possess a mental memory, to transmit messages to other intelligent people, and to create a signal system for this purpose.
Implicit modeling is more adequate in the learning process of complex systems. Implicit modeling requires tools that allow reproduction of a desired behavior of the complex system under study. The tools by themselves may form another complex system, which can be understood more easily than the original system. An implicit model allows experimentation, but it lacks one of the features of explicit modeling, which is comprehensibility of the functioning or solubility of the result obtained. The result of the implicit modeling is not an identification of a “black box,” but creation of its model in the form of another “black box” that allows it to carry out many of the experiments necessary for research. Modeling of an intellectual activity is one of the scopes of implicit modeling.
Key Terms in this Chapter
Activity: An axiomatic form of representation of the relationship (interaction) of entities, when one entity becomes a subject of activity (an organism), and the other one in relation to the first one acquires the status of an object of activity. Activity is related to the processes of reflection (information obtaining) and management. It is the initial and universal integrity.
Evolutional-Activity (EA) Approach: The approach of creation of conditions for transition from one system of presenting information into the system of representation of activity, which is consistent system of measure (scale of relations) of changes in an object of directed activity. This approach eliminates information barriers, provides evolution of the subject's activity and conscious generation of relevant solutions.
Generation of Actual Knowledge: The generation and evolution of solutions focused on real highly demanded problems at the right time and based on the activity of subject as a backbone factor.
Event in Activity: A change in the state of an object of activity by actualization of the order parameters (directions of the subject's activity), which is, as a consequence, the reason for the appearance of new properties and new objects.
Axiomatic Representation: The simplest and most obvious for the majority of people statements of unambiguous perception taken without any proof.
System Technology of Solution: The algorithm of ordering of events represented by the parametric model. This algorithm provides the required quality of the result of the creative activity.
Convergent Representation of the Content: The formation of a consistent model of representation of the consistent world in the systematic cognitive activity of a subject during the learning process. The convergent representation of the content provides event interaction of elements of the model in the process of divergent generation of the actual solution.
Parametric Evaluation: Comparison of the two parameters, the states of an object before and after the selected impact. The difference in these parameters characterizes the achieved effect.