Large Language Models (LLMs) have prompted widespread application across diverse domains. In some applications, human-like quality in output is essential for optimal user experience and credibility. This is particularly evident in applications such as Chatbots. Conversely, concerns arise regarding LLM use in contexts where human authenticity is…

A child's ability to understand text (reading comprehension) can greatly impact both their ability to learn in the classroom and their future contributions to society. Reading comprehension draws on oral language; behavioural measures of knowledge at the word and sentence levels have been shown to be related to children's reading comprehension. In…

Reading comprehension is key to knowledge acquisition and to reinforcing memory for previous information. While reading, a mental representation is constructed in the reader's mind. The mental model comprises the words in the text, the relations between the words, and inferences linking to concepts in prior knowledge. The automated model of…

The ability to automatically assess the quality of paraphrases can be very useful for facilitating literacy skills and providing timely feedback to learners. Our aim is twofold: a) to automatically evaluate the quality of paraphrases across four dimensions: lexical similarity, syntactic similarity, semantic similarity and paraphrase quality, and…

COMPASS is an e-learning system that can visualize grammar errors during sentence production in German as a first or second language. Via drag-and-drop dialogues, it allows users to freely select word forms from a lexicon and to combine them into phrases and sentences. The system's core component is a natural-language generator that, for every new…

This study expands upon an existing model of students' reading comprehension ability within an intelligent tutoring system. The current system evaluates students' natural language input using a local student model. We examine the potential to expand this model by assessing the linguistic features of self-explanations aggregated across entire…