Massive Open Online Courses (MOOCs) have broadened educational access but often overlook the diverse needs of learners, especially those with disabilities. This paper introduces the RECMOOC4ALL conversational chatbot, a Generative AI-powered tool crafted to enhance personalization, engagement, and accessibility within online learning environments. Unlike general-purpose chatbots, it collects user preferences, accessibility needs, and interaction patterns to support other components of the RECMOOC4ALL system such as the recommendation system and accessibility checker in delivering inclusive learning experiences. Leveraging technologies such as Speech-to-Text (STT), Text-to-Speech (TTS), multilingual support, and advanced AI models like GPT-3 and Whisper, the system fosters adaptive learning experiences tailored to individual requirements. This paper highlights the transformative potential of Generative AI in mitigating accessibility challenges and outlines the system's technical architecture and capabilities. Preliminary findings regarding user satisfaction and interaction efficacy, detailed in subsequent sections, underscore the tool's potential to significantly improve engagement and learning outcomes for students with disabilities.

In the dynamically evolving of Massive Open Online Courses (MOOCs), the imperative for real-time and the efficient evaluation of learner engagement has never been more pronounced. Traditional methodologies, while providing foundational insights, often fall short in terms of objectivity and immediacy. This paper introduces an innovative system that uses advanced computer vision and machine learning algorithms to dynamically detect and analyze learner emotions and engagement levels during MOOC sessions. Additionally, this system facilitates the identification of areas for improvement and supports the design of personalized and engaging learning experiences, particularly for learners with disabilities. Our findings reveal that this system not only monitors the duration and intensity of learner engagement but also actively identifies moments of peak engagement and discerns learning patterns. This information enables the personalization of educational paths to suit individual learning styles, significantly enhancing engagement and overall MOOC effectiveness. Powered by affective computing, this technology seeks to make a difference in the field of education technology, transforming MOOCs into personalized learning environments that match the specific interests, goals and needs of each user.

Massive Open Online Courses (MOOCs) providers deliver courses to all students in a largely uniform manner, regardless of their individual needs. This ‘massiveness’ characteristic presents a number of challenges, most of which are connected to the lack of accessibility, inclusiveness, and personalization factors, particularly for learners with impairments and the elderly. Specifically, bridging the gap between learners' skills and individual variance owing to the lack of personalization and digital accessibility compliance, still remains burdensome. For this reason, incorporating accessibility and Universal Design for Learning (UDL) into online learning in general and MOOCs in particular might help establishing flexible learning experiences for all, taking into consideration learner variability and educational requirements by design. This paper sheds light on UDL and digital accessibility considerations within MOOCs and summarizes a literature review on MOOCs accessibility, paving the way to present our ongoing research aiming at enhancing MOOC accessibility harnessing artificial intelligence.