Proceedings of the 7th International Academic Conference on Education, Teaching and Learning
Year: 2024
DOI:
[PDF]
Exploring Postgraduates’ Acceptance of an Artificial Intelligence-Powered Chatbot Mondly for EFL Speaking Practice Based on Model of Technology Acceptance
Du Jinming
ABSTRACT:
This study delves into the acceptance levels of postgraduate students regarding the integration of an Artificial Intelligence (AI)-powered chatbot, Mondly, into their English as a Foreign Language (EFL) speaking practice sessions. Drawing upon the Model of Technology Acceptance (MTA), this research seeks to investigate the factors influencing postgraduates’ acceptance of Mondly and its effectiveness in enhancing their EFL speaking skills. The proliferation of AI technologies in educational settings has sparked interest in their potential to facilitate language learning. Mondly, an AI-powered chatbot, offers an interactive platform for language learners to engage in speaking practice through simulated conversations. However, the extent to which postgraduates embrace and utilize such AI-driven tools remains underexplored. The research employs a mixed-methods approach to gather comprehensive insights into postgraduates’ perceptions and attitudes towards Mondly. Quantitative data are collected through surveys based on the MTA framework, assessing factors such as perceived usefulness, ease of use, and intention to use Mondly for EFL speaking practice. Additionally, qualitative data are gathered through in-depth interviews to delve deeper into the rationale behind postgraduates’ acceptance or resistance towards Mondly. Findings reveal several key factors influencing postgraduates’ acceptance of Mondly. Perceived usefulness emerges as a significant predictor, with participants valuing Mondly for its potential to provide personalized and immersive speaking practice experiences. Moreover, ease of use and compatibility with existing language learning practices contribute to postgraduates’ intention to integrate Mondly into their EFL speaking practice routines. However, challenges such as technical issues and concerns regarding the authenticity of AI-generated interactions also surface, warranting further investigation. Through thematic analysis of qualitative data, nuanced insights into postgraduates’ acceptance barriers and facilitators are elucidated. This study contributes to the growing body of literature on technology acceptance in language education by shedding light on postgraduates’ perceptions of an AI-powered chatbot for EFL speaking practice. The findings offer valuable implications for educators and developers seeking to optimize the integration of AI technologies into language learning contexts.
keywords: Artificial Intelligence, Chatbots, EFL, Technology Acceptance Model