Reducing English speaking anxiety through voice-based AI chatbots: Evidence from classroom implementation - Daniel Ari Widhiatama; Elysa Hartati; Lu'luil Maknun (International Journal on Education Insight, 2026)
This study investigates the effectiveness of voice-based AI chatbots, such as C-AI, Parlalingo, and Copilot in reducing foreign language classroom anxiety among English Language Education students. Speaking anxiety remains a major barrier to students’ willingness to communicate, particularly in EFL contexts where opportunities for authentic interaction are limited and fear of negative evaluation is high. Hence, this research aims to examine whether incorporating voice-based AI chatbots over a ten-week period can significantly reduce students’ anxiety levels. A quantitative pre-experimental design was employed involving 33 students. Before conducting pre-test and post-test, data were collected using an adapted version of the Foreign Language Classroom Anxiety Scale (FLCAS). Descriptive statistics, Shapiro–Wilk normality test, and paired-samples t-test were used to analyse the data. The results showed  that the mean anxiety score declined from 3.31 (SD = 0.37) in the pre-test to 3.03 (SD = 0.38) in the post-test. The paired-samples t-test showed that this decrease was statistically significant (p < .001) with a moderate-to-large effect size (Cohen’s d = 0.74).  However, challenges such as occasional technical problems and the need to verify AI-generated responses were also described. Overall, the findings suggest that voice-based AI chatbots have the potential to reduce speaking anxiety and foster positive learning experiences. This study highlights the promising role of voice-based AI chatbots in supporting both affective and pedagogical aspects of language learning. Further study employing more rigorous experimental designs is recommended to establish their effectiveness more conclusively.