When ChatGPT can't Chat

The Quest for Naturalness

Datos Bibliográficos

ID7169337
AutoresErik Vo (0000-0001-7011-3084, Teachers College Columbia University New York New York City USA, autor de correspondencia), H Z Waring (0000-0002-0652-568X, Teachers College Columbia University New York New York City USA)
Año2025
Volumen59
Número2
Páginas1064-1075
Fecha de publicación2025-06-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaTESOL Quarterly (JOURNAL)
Identificadores de la revistaISSN: 0039-8322 • E-ISSN: 1545-7249
EditorialWiley (PUBLISHER • GB)
DOI10.1002/tesq.3374
OpenAlexW4405449830
IdiomaEN
Citas recibidas4
Referencias citadas16

Significant advancements in voice chatbots have spurred interest into their role in second language learning (Conium, 2008), particularly their ability to assist in the development of learners' conversation skills in a target language. Many efforts have been made to explore AI's potential to act as conversation partners for language learners. Of central concern is its “naturalness” in such an endeavor (Yang et al., 2022). Despite the importance of gauging “naturalness” in researching human–AI interaction, we are yet to find a systematic way of doing so. In this report, drawing upon half‐a‐century of conversation analytic findings as well as 15 recordings of human–AI interaction, we propose a framework that features three principles of natural human interaction: emergence, indexicality, and recipient design. Our goal is to support empirical research aimed at improving “naturalness” of AI conversational partners with language learners

Conversation · Conversation analysis · Indexicality · Linguistics · Natural (archaeology · Naturalness · AI in Service Interactions · Communication · Computer Science · History · Psychology · Speech and dialogue systems · Topic Modeling