Evaluating User Experience in E-Learning Platforms: An NLP-Enhanced Analysis of Duolingo Reviews.

AbstractThis study presents a novel framework to evaluate the usability and user experience of e-learning platforms, focusing on the Duolingo language learning app. By integrating advanced Natural Language Processing (NLP) techniques such as Large Language Models (LLMs), Latent Dirichlet Allocation (LDA), and sentence embedding models, we identified thirteen key usability and user experience topics from a large dataset of user reviews. Our findings reveal that Duolingo is highly rated since users value its enjoyable learning experiences and effectiveness. However, technical issues, lack of explanations, and frustrating features were identified as areas for improvement. The study demonstrates the effectiveness of our framework in analyzing user feedback at scale, offering valuable insights for improving user experience in e-learning platforms and other domains. [ABSTRACT FROM AUTHOR]