Description

Concept maps are visual representation of topics and its components. Using the concept map the system can able to easily identify the relationships among the concepts. Here the system proposes a new evaluation system for student learning. We proposed an artificial intelligence based student evaluation system to analyze the student learning process. Here the system analyzes the concepts in the concept map using the probability distribution among the concepts. The evaluation results of the student learning results are shown in the form of graphs. The Department of Systems Theory and Design of the Faculty of Computer Science and Information Technology of Riga Technical University has been developing the concept map based knowledge assessment system KAS already for five years. The paper gives the outline of adaptation mechanism which is under the development and will be integrated with KAS. The adaptation mechanism is based on learners’ psychological characteristics. Learning styles have been chosen as the most widely used psychological characteristic. Several models of learning styles are overviewed and the Felder-Silverman model has been chosen as the most appropriate for IKAS. For explanation why more flexible adaptation mechanism is needed in IKAS its architecture and functionality is presented. An artificial intelligence based student evaluation system (AISLE) is one of the methods of education that uses computers and interactive learning. Computers are equipped with educational material displays the information needed by the students and focus on addressing weaknesses in the topics that students could not understand properly, which was reflected by their answers on a sheet of questions.