Hive AI Белем картасын төзү платформасы by Hive AI

Hive AI Белем картасын төзү платформасы by Hive AI is a highly esteemed winner of the very prestigious 2025 A' Design Award Көмеш бүләге in Интерфейс, Аралашу һәм Кулланучы Тәҗрибәсе Дизайны Competition Category.

КөмешИнтерфейс· 2025

Hive AI Белем картасын төзү платформасы

by Hive AI

Client: Hive AI

A' Design Award Көмеш бүләге Winner in Интерфейс Category

57,436

Verified Award Winner

Verify Award Status for #169652

View at A' Design Award Press Release Award Badge

Colors

The Design

About Hive AI Белем картасын төзү платформасы

Hive AI — укучылар, белгечләр һәм тикшеренүчеләр өчен белем картасын төзү платформасы. Платформа таркау мәгълүматны бәйләнешле белемгә әйләндерү өчен алтыпочмаклы белем төеннәрен куллана. Кулланучылар текст, видео һәм рәсемнәр йөклиләр, ә ясалма интеллект бәйләнешләр тәкъдим итә, бәйле эчтәлекне төркемли һәм буш урыннарны ачыклый. Сызыксыз навигация билгеләнгән сорау-җавап юлларына караганда ирекле өйрәнүне тәэмин итә. Визуаль шаблоннар, мәсәлән, тарихи хронологияләр һәм өч үлчәмле алтыпочмаклы карталар, белемне ачык итеп күрсәтәләр. Җайлашучан интерфейс якты һәм караңгы темаларны хуплый.

The Recognition

About the A' Design Award Көмеш бүләге

Hive AI Белем картасын төзү платформасы – A' Design Award Көмеш бүләге җиңүчесе, бу гадәттән тыш абруйлы танып белү, ул югары класслы, чибәр һәм тәэсирле дизайннарга бирелә. Көмеш җиңүчеләре – үз дизайнерларының искиткеч белемен, талантын һәм үткенлеген күрсәтүче бик ялтыравыклы һәм иҗади эшләр. Hive AI Белем картасын төзү платформасы искиткеч, үрнәк булырлык, игътибарга лаеклы профессиональ һәм тирән яңалыклы әсәр булыр дип көтелә. A' Design Award Көмеш бүләге җиңүче бу дизайн – сәнгать, фән, дизайн һәм технология чикләрен алга җигүче файдалы, югары бәяләнгән уйлап табу. Hive AI Белем картасын төзү платформасы – күпләрнең көнләшкән, теләкләрне уятучы, уңай хисләр китерүче һәм хәйранлык һәм гаҗәпләнү тудыручы иҗат җимеше.

Behind the Design

Press Kit

Credits, team members and technical details provided by the designer.

Unique Properties: Hive AI is a transformative learning platform that enables learners to build personalized knowledge systems. With the unique “hexagon knowledge nodes” and AI-driven tools like tailored recommendations, knowledge grouping, and dynamic data visualization, Hive supports students, professionals, and researchers in fostering interdisciplinary exploration and managing complex information.
Dimensions & Packaging: Designed for adaptability, efficiency, and reliability, the platform features a responsive interface optimized for various screen sizes, supporting landscape and portrait modes. Users can personalize their experience with light and dark themes, while cross-device compatibility ensures accessibility. AI-driven adaptability enhances learning preferences, providing real-time interactions with secure performance. Hive AI integrates technical precision with user-friendly design, delivering a dynamic, intuitive experience tailored to individual needs.
Tags: Geneartive AI, Adaptive Learning, Personalization, Ed-Tech, Non-linear Interaction, Data Visualization
Production Technology: Hive AI's technology was developed through an iterative, data-driven approach leveraging advanced neural networks. The product mission guided development, ensuring the machine learning framework effectively organizes users' thoughts into structured knowledge. Rigorous testing and refinement perfected the node-based architecture for seamless non-linear exploration. The final system prioritizes adaptability, efficiency, and reliability, empowering users with a dynamic, personalized learning experience.
Design Challenge: How can node-based interactions feel as intuitive as conversation-based AI? This challenge explores motion design, iconography, and cognitive flow for seamless user adaptation. By researching existing node-based systems, the effectiveness in guiding eye movement and mental mapping was evaluated, identifying both strengths and gaps. Through user testing, motion and icons for clarity and usability were refined. The goal is to create a visually intuitive, AI-assisted system that preserves familiar interaction patterns while enhancing how users navigate complex knowledge structures with ease and engagement.
Research: Type:
Competitive & User-Centered Design Research

Objective:
Enhance exploratory, autonomous learning with AI-powered tools.

Methodology:
Surveys, interviews, and usability testing.

Tools:
Google Forms, SurveyMonkey, Zoom, Figma prototypes.

Participants:
100 technology enthusiasts

Results:
Optimized node connection interactions.
Improved accessibility with refined UI.
Prioritized key data visualization methods.

Insights & Impact:
AI-driven design enhances learning efficiency, accessibility, and critical thinking, fostering a more engaging and effective digital education experience.
Inspiration: Hive AI epitomizes usability, efficiency, speed, and reliability. Drawing on generative AI and mind-mapping, it transforms learning into a dynamic, personalized journey. Market research shows 78% of users find current tools limiting, revealing a major business opportunity. With elegant simplicity, fluid design, and smart organization, Hive AI redefines learning and unleashes creativity.
Project Duration: Research - 1 Month

Concept and Prototyping - 2 Months
Design Finalization - 1.5 Months

Evolutives & APP Development: ongoing
Operation Flow: The system structures fragmented information into interconnected knowledge. Learners upload and organize content - text, videos, and images - and AI enhances connections and identifies gaps.

- Node Expansion builds knowledge structures based on interests.
- Gap Bridging links concepts for deeper understanding.
Structured Organization groups information for easier memorization.
- Nonlinear Exploration enables dynamic navigation.

Hive AI also provides visual templates, like historical timelines and 3D hexagonal maps, making knowledge presentation more intuitive and effective.
Patents: Yongwen Dai, Xuefei Wang, Keqing (Clara) Jiao, Hanyong Yang, Huiyang Chen
Team Members: Yongwen Dai
Xuefei Wang
Keqing (Clara) Jiao
Hanyong Yang
Huiyang Chen
Image Credits: Yongwen Dai, Xuefei Wang, Keqing (Clara) Jiao, Hanyong Yang, Huiyang Chen