Learning Greek with an Adaptive and Intelligent Hypermedia System

This paper reports on a course-support system for English learners of Greek which is built around an Intelligent Language Tutoring System (ILTS). Meaningful interaction between the learner and the system is achieved by a number of means: First, students provide natural language input rather than selecting exclusively from among pre-defined answers. Second, the ILTS uses Natural Language Processing to analyze the learner’s input and to provide errorspecific feedback. Third, the system contains a Student Model which keeps a record of students’ performance histories. The information about each learner in the Student Model determines the level of specificity of feedback messages, clues, and exercise difficulty. In addition to vocabulary and grammar exercises, the system also contains oral dialogues with translations, a glossary, and cultural information. The system is designed for introductory learners of Greek and is implemented on the World Wide Web.