COMPARING TRADITIONAL SPEAKING PRACTICE WITH AI-SUPPORTED CONVERSATIONAL TRAINING
Keywords:
AI-supported learning, speaking practice, communicative competence, chatbot, language learning, motivation, interactionAbstract
This study explores the effectiveness of traditional speaking practice compared to AI-supported conversational training in developing learners’ oral communication skills. The research examines how artificial intelligence, particularly language models and interactive chatbots, enhances fluency, accuracy, and learner motivation. Data were collected through classroom observation, interviews, and pre- and post-tests. Results indicate that AI-based interaction provides individualized feedback, reduces anxiety, and increases speaking time, while traditional methods strengthen peer collaboration and pronunciation through face-to-face engagement. The study concludes that integrating AI tools with conventional teaching yields the most effective outcomes for developing communicative competence. AI-supported training offers continuous practice opportunities outside the classroom and adapts to individual learners’ pace. These findings emphasize the importance of balancing human interaction and technological support in modern language education.
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