Evaluating the Performance of Conversational AI Tools
Deepika Chauhan, Chaitanya Singh, Romil Rawat, Manoj Dhawan · 2024
In recent years, conversational AI has gained significant attention as a promising tool for enhancing various aspects of education and training. Despite the growing popularity of these tools, there is limited research that compares the efficacy of different conversational AI platforms. This study aims to address this gap by conducting a comparative analysis of leading conversational AI tools and evaluating their performance in terms of natural language processing (NLP) accuracy, personalization, interactivity, and overall user experience. The results of this study provide valuable insights into the strengths and limitations of different conversational AI tools and can help educators and trainers make informed decisions when selecting these tools for educational and training purposes. The findings also suggest areas for future research, such as improving NLP accuracy and personalization capabilities as well as exploring ethical considerations related to the use of conversational AI in education and training.