Methods: We had used an inter-disciplinary, cross-link approach in our research, taking into account some significant aspects like:
-the financial aspect- we have tried at the begining to use just Open Source instruments- but they were not sufficient in order to build our structures. So we have obtained free access to some efficient development tools combining them with the available Open Source software.
-the need for a self-training instrument that should use knowledge instead of data- in order to efficientize the process of skills acquirement.
-the necessity for knowledge engineering – especially regarding knowledge mining and knowledge update.This lead us towards topic maps as the major way in order to obtain an efficient knowledge upgrade.
-the necessity for knowledge distributed structures- in order to assure an efficient knowledge generation/dissemination process these structures- build around knowledge seeds – could be easily developed at specific structures (like universities, important medical centers, etc.) and inter-connected in order to assure specific chunks of knowledge.
Obtained results: Till now our results were focused towards the development of a conceptual frame for such knowledge structure, modelling and testing this frame in real situations and transition towards development of a prototype.
Our conceptual frame is considering two distinct structures:
-The Front (Eduknowledge based tutorial system) based on:
-the extensive use of highly structured knowledge in order to obtain quickly the desired skills;
-the optimal inter-relation between the individual student- with his/hers
specific learning style and learning attitudes and the tutor (tutorial
system), correlated with an efficient knowledge dissemination and
imprint;
-The Logistics (knowledge storage and upgrading structures) based on:
-an inter-connected structure of specific knowledge bases, evolved from knowledge seeds , able to contribute actively at specific knowledge development (for example heuristic diagnosis methods for a specific disease- from various medical centers around the world- taking into account specific aspects regarding environmental conditions, race, age, etc.);
-upgrade on-line from other knowledge sources- through knowledge maps.
As a highly structured knowledge structure, focused towards the goal of mastering specific techniques- we found during our research eduknowledge as, perhaps the best suited tool for medical training. The learning process improved its efficiency by 17%...35.4% taking into account other computer based training systems and by 45% taking into account classic tuition. The new method uses extensively knowledge especially structured in order to achieve a peculiar goal-it is based on individual interaction between the training system and the trainee, the subject of training could individually improve his/hers training paths and rise the efficiency of personal training contributing to the increase in the whole training process. After understanding the basics in his specific activity the trainee interacts with various scenarios, in order to use the acquired knowledge and develop his abilities in virtual environments re-enacting the real ones. After the end of training the learned abilities will be naturally and efficiently imprinted in the trainee which will use them as an integrant part of the work process.
A generic image of eduknowledge is presented in the next figure.
Figure 1-Generic structure of eduknowledge
In the next figure is presented the general structure of the system
Conclusion: Our paper presents the most significant aspects of a research having as a final result a libre based, low cost eduknowledge training system, with very important applications in medical training. This system could be easy upgraded using topic maps. Also, even if it is developed especially for mastering diagnosis processes, it could be easy focused towards various specific medical techniques.
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