Customizing ChatGPT for Second Language Speaking Practice: Genuine Support or Just a Marketing Gimmick?

TL;DR

This study evaluates how customizing ChatGPT with prompt engineering and theoretical grounding impacts its effectiveness as an ESL speaking practice tool, highlighting benefits and limitations of personalization.

Contribution

It provides an empirical comparison of customized versus uncustomized ChatGPT Voice Mode versions for ESL speaking practice, grounded in language learning theories.

Findings

Customized ChatGPT offers more balanced feedback and emotional support.

Cultural responsiveness did not significantly improve with customization.

Standard ChatGPT already meets many learning needs.

Abstract

ChatGPT, with its customization features and Voice Mode, has the potential for more engaging and peresonalized ESL (English as a Second Language) education. This study examines the efficacy of customized ChatGPT conversational features in facilitating ESL speaking practices, comparing the performance of four versions of ChatGPT Voice Mode: uncustomized Standard mode, uncustomized Advanced mode, customized Standard mode, and customized Advanced mode. Customization was guided by prompt engineering principles and grounded in relevant theories, including Motivation Theory, Culturally Responsive Teaching (CRT), Communicative Language Teaching (CLT), and the Affective Filter Hypothesis. Content analysis found that customized versions generally provided more balanced feedback and emotional support, contributing to a positive and motivating learning environment. However, cultural responsiveness did not show significant improvement despite targeted customization efforts. These initial findings suggest that customization could enhance ChatGPT's capacity as a more effective language tutor, with the standard model already capable of meeting the learning needs. The study underscores the importance of prompt engineering and AI literacy in maximizaing AI's potential in language learning.