Chatbot-Supported Implementation on Pre-Service English Language Teachers' Academic Speaking Skills
TL;DR
The qualitative findings show that pre-service teachers experienced a learning environment free from stress and anxiety, with personalised instant feedback provided by the chatbot implementation, and pre-service teachers indicated they would continue to utilize this tool in future speaking activities.
Abstract
Artificial intelligence (AI) chatbots, particularly with the advancements in generative artificial intelligence (GAI), have gained prominence in language education. In this context, the main purpose of this study, designed with a mixed-methods experimental design, is to examine the effect of the Call Annie chatbot application on the academic speaking skills of pre-service English language teachers, considering the structural limitations of the EFL context. Furthermore, it aims to examine in depth how this effect occurs through qualitative data. The study's data were collected through speaking achievement tests, response papers, and semi-structured interviews, and the validity and reliability of the research were increased by triangulating the data sources. The quantitative findings of the research revealed a statistically significant difference in the midterm and final grades of the experimental group compared to the control group after a 10-week application. The qualitative findings show that pre-service teachers experienced a learning environment free from stress and anxiety, with personalised instant feedback provided by the chatbot implementation. It was concluded that Call Annie had a positive effect on oral communication skills, and pre-service teachers indicated that they would continue to utilize this tool in future speaking activities.