This study explores the challenges of enhancing English fluency among students at vocational high schools and evaluates the potential of integrating artificial intelligence (AI) tools with teacher collaboration as a strategy for improvement. In a region marked by limited teaching resources, geographical isolation, and a shortage of qualified educators, traditional English instruction often fails to meet students’ communicative needs. The research aimed to determine whether the combined use of AI-based interventions and collaborative teaching practices could yield more effective outcomes in speaking fluency compared to conventional methods. Utilizing a quasi-experimental design without random assignment due to logistical constraints, the study involved 200 participants from five vocational schools. Data were collected through surveys and in-depth interviews. Quantitative analysis, using independent t-tests and ANOVA, revealed a statistically significant improvement in fluency scores for the experimental group. Pre-test mean scores were 18.2 (experimental) and 17.9 (control), while post-test scores increased to 24.5 and 20.1, respectively, with Cohen’s d values indicating a strong effect (1.21 for experimental, 0.42 for control). Qualitative findings showed that students developed greater confidence and motivation, influenced by the interactive and adaptive features of AI, while teachers reported increased instructional alignment through collaborative efforts. The study concludes that integrating AI tools with teacher collaboration creates a supportive, engaging, and effective environment for developing fluency. It recommends broader implementation of such models in similar educational contexts and suggests future research focus on long-term impacts and sustainable strategies for embedding AI in teacher training and classroom practices.
Pratama et al. (Mon,) studied this question.
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