Deep learning-based course recommendation systems often suffer from a lack of interpretability, limiting their practical utility for students and academic advisors. To address this challenge, we propose a modular, post-hoc explanation framework leveraging Large Language Models (LLMs) to enhance the transparency of deep learning-driven…

There is now a well-established literature showing that people anticipate upcoming concepts and words during language processing. Commonsense knowledge about typical event sequences and verbal selectional preferences can contribute to anticipating what will be mentioned next. We here investigate how temporal discourse connectives…