Ruffle&Riley: Insights from Designing and Evaluating a Large Language Model-Based Conversational Tutoring System

arXiv:2404.17460v1 Announce Type: new
Abstract: Conversational tutoring systems (CTSs) offer learning experiences through interactions based on natural language. They are recognized for promoting cognitive engagement and improving learning outcomes, especially in reasoning tasks. Nonetheless, the cost associated with authoring CTS content is a major obstacle to widespread adoption and to research on effective instructional design. In this paper, we discuss and evaluate a novel type of CTS that leverages recent advances in large language models (LLMs) in two ways: First, …

abstract arxiv cognitive conversational cost cs.cl designing engagement improving insights interactions language language model large language large language model major natural natural language reasoning systems tasks through tutoring type