How ChatGPT and Gemini View the Elements of Communication Competence of Large Language Models: A Pilot Study

TL;DR

This pilot study explores how ChatGPT and Gemini interpret communication competence elements based on two theoretical models, providing insights into LLM-user interactions and their alignment with communication theories.

Contribution

It is the first to analyze LLMs' understanding of communication competence through established theoretical models in a comparative case study.

Findings

Both models effectively interpret LLM-user interactions.

LLMs show alignment with communication competence elements.

The study supports using these models for future LLM communication analysis.

Abstract

A concise overview is provided of selected theoretical models of communication competence in the fields of linguistics, interpersonal communication, second language use, and human-robot interaction. The following practical research consisted of two case studies with the goals of investigating how advanced AI tools like ChatGPT and Gemini interpret elements of two communication competence theories in the context of Large Language Model (LLM) interactions with users. The focus was on these theoretical approaches: (1) an integrated linguistic-interpersonal model and (2) an interpersonal "human-humanoid" interaction model. The conclusion is that both approaches are suitable for a better understanding of LLM-user interaction.