Prompting an LLM Chatbot to Role Play Conversational Situations for Language Practice

Abstract

Chatbots based on Large Language Models (LLMs) have demonstrated a remarkable ability to engage in conversations that are linguistically correct and make sense from a pragmatic point of view. A significant trait of their proven abilities is that, using verbal instructions provided as contributions to an ongoing conversation, they can be configured to provide specific content and/or modify the role that they play in the exchange. The present paper explores the feasibility of developing a framework of prompts designed with such an aim in mind. The prompting should ensure that the chatbot engages a language learner in an interaction where it proposes conversational situations of appropriate complexity, takes part in them playing the role of one of the participants, while monitoring the linguistic correctness of the contributions by the learner and providing feedback on their language performance both proactively and in response to learner requests. The paper reports on an experiment tha t tested this type of functionality students of Spanish as a second language at Aligarh Muslim University in India.