Recent advances in artificial intelligence enable new approaches to the design and delivery of digital learning. However, creating structured learning materials and providing personalised learning support at scale remain major challenges in large online courses.

This paper presents a pilot digital learning platform that applies AI to support both course creation and adaptive learning processes. The system allows educators to upload source materials such as documents, presentations, images or textual content. Based on these inputs and the instructional goals defined by the course designer, the AI generates a suggested course structure including learning elements such as explanations, examples and formative assessments.

During the learning process, the platform continuously analyses learners’ performance in short assessments. Based on these results, the system dynamically adapts revision sections and generates personalised practice activities targeting the topics where the learner demonstrates weaker performance. This approach aims to simulate the individual support typically provided by a teacher during face-to-face tutoring, but at the scale of large online courses.

The platform is currently being piloted in real learning environments and represents an emerging approach to combining AI-supported course design with adaptive learning pathways.

The presentation discusses the system architecture, the instructional design approach and early experiences from the pilot implementation.