Χρήση ευφυών μεθόδων για προσαρμοστική αξιολόγηση σε ευφυές σύστημα διδασκαλίας
Smart technologies for personalized evaluation in a smart application for education
Abstract
Intelligent Teaching Systems are systems that use Artificial Intelligence methods to provide personalized teaching, especially in recent years and have evolve through the Internet. These systems offer training tailored to the potentials and needs of students. An important objective of these systems, through which innovative technologies are developed, involves the evaluation of students by the teaching system itself. The evaluation is about determining a student's knowledge, usually by measuring his performance in one or more tests that contain questions-exercises of scale difficulty referring to a set of terms. In this case it is important to define correctly the level of difficulty of the questions-exercises. A second objective is the proper design of the tests to meet the needs of the successfully assess each student, based on the content of the lesson he is attending. A third objective concerns intelligent methods, i.e. technology or combined technology and algorithm, used to achieve the two above mentioned objectives. Simple methods are usually used, such as production rules or important networks. An interesting research approach is the use of hybrid intelligent techniques, i.e. techniques combining at least two known intelligent techniques, the combination of production rules and genetic algorithms. The subject of this postgraduate diploma thesis is the study of technologies that can be applied independently and combined for the development of integrated Intelligent Teaching Systems. In addition, there is a study of technologies that can be used to adapt Intelligent Teaching Systems according to the particularity and need for improvement of the student after evaluation of the teaching system itself.