In a labor market that is increasingly globalized, knowledge of one or even more than one foreign language is more relevant than ever before. Due to increased mobility, multilingual skills are also required for private communication as friendships stretch across geographical and linguistic borders.
At the same time, learners experience that the acquired basic foreign language skills deteriorate quickly if they are not trained and improved on a regular basis. However, the static time frame of conventional language courses is often not compatible with the learners’ unstable working conditions and lifestyles. Therefore, many learners turn to online portals for self-directed learning. These portals are becoming increasingly more popular although the provided contents are rather inflexible and limited. So far, adaptive technologies that individually adjust contents to the learners‘ proficiency level, their speed of progress and their learning style are at an early stage of development. In order to generate adaptive exercises with varying difficulty, we need to be able to measure difficulty automatically. In this project, we have developed measures for predicting and manipulating the difficulty of texts, words and exercises for language learners.