Adjusting the tests according to the perception of greek students who are taught russian motion verbs via distance learning

Nowadays, the quantity of digital data is so large that its analysis and evaluation can only be performed through (semi-) automatic methods. In a distance learning context, such problems arise for the teacher who needs to personalize the educational material for specific students. The present study focuses on the personalization of the educational material for Greek students learning the Russian language in a distance learning environment. We discovered that it is important for the Intelligent Tutoring System and more specifically for the Intelligent Agents (IA) to have a set of key-characteristics for a proper representation of the states. By having more features an agent has more accurate results whereas useless features are ignored. © IFIP International Federation for Information Processing 2014.