AI-Powered Personalized Learning to Improve Engagement and Reduce Dropout

Use Case:

AI-enhanced student engagement through tailored content delivery and adaptive communication strategies in online education environments.

Outcome:

AI-powered system designed to reduce dropout rates via behavioral analysis; Personalized learning journeys based on student behavior and preferred communication channels; Technical readiness at TRL-5, with feasibility and implementation roadmap delivered; Foundation for commercial uptake and testing with real user pilots.

Ecosystem Support:

StairwAI support in shaping the technical feasibility plan, refining the business model through a structured methodology, and providing expert mentorship for AI adoption.

AI Relevance:

This use case showcases the democratization of AI for SMEs through: I) structured business modeling for AI integration; II) lightweight, scalable personalization mechanisms; III) focus on human-centric design and educational impact; IV) support in early-stage experimentation toward sustainable business adoption.

Summary:

DÍCARO GFD S.L., a Spanish SME focused on educational technologies, successfully completed the Improve Personal Learning Project under the StairwAI support program. The project aimed to enhance online learning engagement by leveraging artificial intelligence to tailor learning experiences to individual users. Through a behavioral analysis system embedded in virtual classrooms, the solution identifies how each student interacts with content and dynamically adjusts the delivery of educational resources. This matching process improves communication efficiency and helps boost adherence and reduce dropout rates. The company delivered all milestones on time, including a Feasibility Plan and a comprehensive Business Model for AI adoption. The AI system design focuses on three core challenges: improving the data ingestion pipeline, integrating academic-grade AI tools, and designing mechanisms to ensure AI quality and relevance. Technically, the project reached TRL-5, providing a solid base for upcoming pilot phases. From a business perspective, the team adopted a structured validation approach that included defining product-market fit, assessing key assumptions, and designing experiments for customer engagement. While the current business model is assumption-driven, a roadmap for market testing and iterative refinement is already in place. These commercial explorations will be carried forward beyond the StairwAI program, aiming to fully integrate the AI solution into scalable EdTech services for improved learning outcomes.