LearnStamp — U2U-powered social learning for every video

LearnStamp is a crowdsourced, timestamped quiz layer for YouTube and short-form educational videos that turns passive watching into verifiable “proof-of-understanding” stamped on-chain, tailored for U2U’s DAG + EVM to showcase real-time scale and AI-assisted learning at hackathon-grade polish.

Problem

Educational videos are hard to trust and measure: studies show wide variance in quality and reliability, forcing teachers and learners to spend time validating content rather than learning. Crowdsourced checks and open innovation systematically improve instructional resources but lack verifiable provenance and incentives across platforms. YouTube’s scale demands a lightweight, social, and portable layer that verifies learning effectiveness at the moment of viewing.

Solution

LearnStamp lets viewers drop “learning stamps” at exact timestamps by creating or answering short questions, surfacing the community’s best checkpoints in-video while minting non-transferable proof-of-understanding credentials on U2U. AI proposes draft questions and clarifications from transcripts, while the crowd upvotes, refines, and verifies the best ones to build a living concept map per video and per topic. The result is a self-improving, verifiable layer for social learning that travels with the content and its community.

Why U2U

U2U’s DAG-based Layer-1 with EVM compatibility supports high-throughput, low-latency micro-interactions (answers, votes, stamps) at scale, ideal for millions of concurrent learning events. Its modular architecture and subnets enable dedicated learning rails for institutions or partners without sacrificing mainnet settlement and ecosystem reach. The hackathon explicitly targets EVM-deployable MVPs and rewards real user impact, making LearnStamp a strong SocialFi + AI fit.

Core user flow

• Watch a video, and see the top community “stamps” appear at relevant timestamps as optional micro-quizzes or clarifications.

• Answer to verify understanding; correct answers mint a non-transferable “Stamp” NFT tied to the concept and video segment on U2U.

• Create new questions when something is unclear; the crowd refines and ranks them, building a concept graph and difficulty map for future learners.

What makes it brilliant and simple

• Timestamp-first: tiny, focused checks precisely where confusion happens, not after the video.

• Crowd-improves content: unclear parts attract more clarifying questions, naturally ranking videos by learning effectiveness.

• Verifiable learning: on-chain stamps form a portable, audit-friendly proof-of-understanding trail for learners and creators.

AI integration

• Auto-suggest questions and distractors from transcripts and chapters; the crowd edits and approves, keeping AI as a draft assistant.

• Summarize confusion hotspots by clustering high-failure stamps, giving creators targeted fix suggestions.

• Personalized practice pulls similar stamps across videos to reinforce weak concepts.

SocialFi mechanics

• Streaks and topic badges reward consistent learning, not speculation, encouraging healthy, repeatable engagement

• Leaderboards by concept and course playlists surface community experts and helpful explainers.

• Creators get learning analytics they can’t access today, driving organic adoption and sharing with their audiences.

U2U architecture

• Smart contracts (Solidity) for Stamp SBTs, reputation scores, and checkpoint registries deployed on U2U’s EVM.

• High-frequency writes (answers/upvotes) benefit from DAG’s parallel processing and fast finality for a smooth UX.

• Optional subnets for campuses or enterprise partners with custom policies while anchoring proofs to U2U mainnet.