LearnIsle: A Web-Based Interactive Personalized Learning Platform for an Effective Learning Experience
Mohammed Ayish 1, Shiza Agha 2, Ayesha Katkar 3
Department of Computer Engineering 1, Viva Institute of Technology, Maharashtra, India.
Department of Computer Engineering 2, Viva Institute of Technology, Maharashtra, India.
Department of Computer Engineering 3, Viva Institute of Technology, Maharashtra, India.
mohammedayish007@gmail.com
shizaagha985@gmail.com
ayeshaskatkar201@gmail.com
Abstract – Traditional study methods often struggle to maintain student engagement, particularly in an era characterized by digital distractions and reduced attention spans. This paper presents LearnIsle, a web-based AI-powered personalized learning platform designed to transform uploaded study materials, such as PDF documents, into structured and interactive learning resources including summarized notes, flashcards, podcast-style audio explanations, and AI-generated mini-games.
The platform operates through a dual-environment model consisting of a Learning World and an Arcade World. In the Learning World, users engage in document reading, audio-based learning, and active recall activities, which generate limited “lives” based on sustained study effort. These lives are then utilized in the Arcade World, where learners reinforce their understanding through AI-driven educational mini-games such as multiple-choice challenges, memory matching, speed recall exercises, and fill-in-the-blank tasks.
LearnIsle integrates intelligent content extraction, automated question generation, experience points, achievement-based progress tracking, and visual feedback mechanisms to promote consistent study habits. Developed using scalable modern web technologies, the system ensures accessibility, reliability, and cross-device compatibility. By combining structured learning with controlled, personalized and guided mascot-based support, LearnIsle enhances motivation, strengthens knowledge retention, and delivers a more engaging and effective study experience.
Keywords - personalized learning, educational technology, intelligent document processing, interactive learning systems, adaptive study platforms, web-based applications.
