Technological Innovation for Inclusive Education

This chapter presents the design and evaluation of a digital voice assistant aimed at supporting navigation in virtual learning environments, with emphasis on accessibility for students with visual disabilities. The study highlights the barriers caused by low adoption of accessibility standards and the limitations of screen readers. The proposed prototype was developed as a Google Chrome extension, integrating natural language processing, machine learning models, and APIs for speech recognition and synthesis. A structural analysis of the NAME-PLATAFORM-HIDDEN INSTI-HIDDEN platform was conducted using web scraping to build datasets that enabled the training of LSTM-based classification models. Evaluation with visually impaired students demonstrated improvements in efficiency, autonomy, and satisfaction compared to traditional screen readers. The results indicate that digital voice assistants can complement existing tools and significantly enhance inclusive education in online environments.