Mediated Approach to Addressing Reading Diversity in German Classrooms

Abstract

The LATILL (Level-Adequate Texts in Language Learning) project was initiated to address these educational needs, primarily focusing on German as a Foreign Language (GFL) and Second Language (GSL) teachers. This initiative is particularly timely given the academic commitment to improving reading comprehension within German language curricula. One of the fundamental challenges in language education is the sourcing of suitable authentic texts. Educators often turn to news articles, blogs, or literary excerpts, but these sources may have complex syntactic structures, specialized jargon, or cultural references that exceed the learners’ proficiency levels. Moreover, copyright laws restrict the reproduction and distribution of many high-quality materials, limiting the diversity of texts educators can offer to their students. Recognizing these challenges, LATILL offers a personalized learning platform designed to enhance German language reading comprehension among European youth. Developed around a centralized corpus of texts sourced from public domains and open-access materials, the platform addresses the limitations of traditional teaching methods. LATILL integrates various AI technologies to streamline the creation of educational resources, especially utilizing generative AI to provide real-time translations, summaries, and visual aids. This paper explores the design, implementation, and evaluation of LATILL, with a specific focus on its use of generative AI and human-computer interaction (HCI) to address these challenges. It will highlight the design decisions, the integration of AI features, and the user feedback that informed its iterative development.