Classification techniques used in Educational System Elena Şuşnea National Defence University "Carol I", Bucharest, 68-72 Panduri St. Bucharest 5, ROMANIA E-mail: esusnea@yahoo.com Abstract Using classification algorithms can lead to discovering relevant knowledge contained in educational databases. These findings can be used for providing feedback to learners in the educational process. Keywords: Data mining, Classification algorithms, Educational databases 1 Necessity to use data mining methods in WBI Web-based instruction (WBI) is an alternate solution for the traditional classroom-based education. WBI is ”an innovative approach for delivering instruction in online using the WWW as the instruction delivery system” [Khan, B.H..]. The tendency of using web-based educational technologies has grown a lot during the recent years, causing the development of long-distance study programs and growth of the number of students enlisted in this program. In this way, there have been created different means in order to share and present the digital content (texts, animations, simulations, graphics) as well as means for synchron and asynchron communication between teachers and students (e-mail, chat, forums, wiki). On-line platforms, known as LMS (Learning Management System), as well as WebTC, Moodle, Ilias, IBM, have been projected in order to automize and conduct WBI training activities. LMSs are software programs on installed servers used for managing, sharing and checking the activities in progress within a certain e-learning environment. The main LMS functions are: recording and management of the users, of the training resources and activities; access verifying; realizing a good management of communication means (forums teleconference). In general, an LMS does not include possibilities of content creation and management. In order to create digital contents for courses, it is necessary to use an LCMS (Learning Content Management System). An LCMS is a technology focused on ”development, management and publishing of the content” which is usually used in training via an LMS. Within WBI, the systems previously mentioned generate daily a huge quantity of information that analysed through adequate data mining methods can provide valuable information regarding understanding of students’ behavior, assessing the students’ learning process, error detecting etc.