Scaling AI Learning Tools
Expanding proven AI study tools across History, French, English, and Science to reach more students.
Currently in development.
Project Overview
Role: Senior Product Designer (sole designer)
Timeline: Ongoing (started [month/year])
Company: UK EdTech platform
Team: Development Lead, Front-end Developer, Content Specialists (per subject), Product Manager
The Challenge: After the success of our AI Exam Feedback Tool in History (20% to 55% confidence boost, 90% UX satisfaction), we needed to scale this proven concept across multiple GCSE subjects—French, English, and Science—while adapting to each subject's unique requirements and maintaining the educational, confidence-building tone that made the original successful.
Strategic Scaling Approach
Leveraging Proven Success: Rather than starting from scratch, I'm adapting the successful History AI model to new subjects—keeping what worked (encouraging tone, structured feedback, confidence-building) while customizing for subject-specific needs.
Subject-Specific Challenges:
French: AI feedback needs to handle language nuances, grammar explanations, and pronunciation guidance differently than History's essay-based answers.
English: Literary analysis requires different feedback structure than historical arguments—students need help with textual evidence, interpretation, and analytical writing.
Design Considerations:
Maintaining Consistency: Students use multiple subjects—the interface and interaction patterns stay familiar across all subjects.
Adapting Feedback Structure: While the UI is consistent, the AI prompt design and feedback templates are customised per subject to address discipline-specific requirements.
Design Process:
Cross-Subject Consideration: Analysing how feedback needs differ across disciplines while maintaining a unified student experience.
Cross-Subject Research: Researching current competitors within this very specific area to see where we can meet students needs whilst staying competitive.
AI Prompt Collaboration: Conversing with project managers and subject-matter content specialists to ensure AI prompts deliver accurate, understandable feedback for each discipline.
Current Status & Impact
In Development: Actively designing and testing AI tools across French and English with iterative releases planned throughout 2026.
Building on Proven Success: Leveraging the History tool's results (20% to 55% confidence boost) as the foundation—adapting what worked while customising for each subject's unique needs.
Strategic Impact: This expansion demonstrates thinking beyond single features to scalable product strategy. By proving the concept in History first, we've built confidence to invest in multi-subject rollout.
What's Next: Continuing prompt refinement with subject specialists, testing across disciplines, and iterating based on real feedback to ensure each subject delivers the same confidence-building experience that made History successful.