Extensive Reading (ER) is a powerful approach to language learning, but maintaining engagement and providing individualized support at scale remains a challenge. This interactive workshop introduces a custom-built AI-powered platform that transforms students from passive consumers into active creators of reading material.

Participants will gain hands-on experience using the system to generate personalized ER stories across different levels with just a few clicks. The platform incorporates adaptive difficulty scaling, adjusting text complexity based on learner interaction time and feedback while maintaining coherence.

Real-time tracking of student interactions — including reading time, vocabulary lookups, and content generation patterns — provides insights into engagement and common language challenges. Features such as context-sensitive vocabulary support, AI-generated audio narration, and optional comprehension activities may further enhance autonomous learning.

A key focus will be how AI-driven analysis of student feedback informs ongoing refinements to both the system and pedagogical approaches. Participants will leave the workshop with practical experience in generating personalized ER stories, exploring learner support features, and considering how learner data can inform teaching practice.

This workshop demonstrates how integrating AI technology into ER programs can create a more engaging, personalized, and data-informed learning environment while maintaining the core principles of extensive reading methodology.