SmartFlash: The AI Study Tool

That Knows What You Don't Know

Revolutionary AI-powered learning tool that identifies your knowledge gaps and creates personalized flashcards targeting exactly what you need to learn.

SmartFlash

See SmartFlash in Action

Try Functional Prototype

This is a functional prototype for demonstration purposes. We kindly ask you to use it responsibly. For feedback and suggestions, please contact info@viablelab.org

Meet Our Team

Our diverse team brings together expertise in AI, education technology, user experience design, and learning sciences to create the next generation of study tools.

Hongming (Chip) Li

Founder | Lead Developer | System Architect

Initiated the SmartFlash concept. Leads development and system architecture, focusing on AI-powered educational technology to transform learning experiences.

Hai Li

Algorithm Engineer | Technical Lead

Contributes to user experience design and develops core algorithms, focusing on big data learning analytics and educational data mining.

Nazanin Adhami

UX Research | Product Coordination Lead

Focuses on user experience through interviews and design, bringing human-centered design principles to ensure SmartFlash meets real user needs.

Salah Esmaeiligoujar

Marketing | Operations Manager

Manages operational aspects and marketing strategies, ensuring the project stays on track through effective task management and communication.

Advisor

Dr. Rui (Tammy) Huang

Dr. Rui (Tammy) Huang

Clinical Assistant Professor, University of Florida

Provided invaluable guidance drawing from expertise in Educational Technology, CS Education, and game-based learning design, helping the team apply design thinking principles throughout the project.

Project Overview

Team Introduction

Our interdisciplinary team combines expertise in educational technology, instructional design, computer science, and AI ethics. We came together with a shared vision of transforming how students learn and retain information through personalized, AI-driven tools that adapt to individual learning needs.

Initial Idea

SmartFlash began as a concept to help students create better flashcards. We recognized that traditional flashcard methods often fail to target specific knowledge gaps, leading to inefficient studying.

Our initial vision was to develop an AI tool that could analyze educational materials and automatically generate relevant flashcards, saving students time while improving the quality of their study materials.

"We wanted to create something that would fundamentally change how students approach studying by leveraging AI to identify what they don't know."

Evolved Design

As we developed SmartFlash, it evolved into a comprehensive learning ecosystem that not only creates flashcards but also analyzes learning patterns, identifies knowledge gaps, and adapts to each user's unique learning style.

The final design incorporates advanced natural language processing to extract key concepts from any learning material, personalized assessment algorithms, and interactive learning games that reinforce knowledge retention.

"The platform now intelligently adapts to each learner, creating a personalized learning journey that focuses precisely on what they need to master."

Project Purpose & Target Learners

Our Purpose

SmartFlash aims to revolutionize how students learn by creating a personalized, adaptive learning experience that identifies and targets knowledge gaps, making studying more efficient and effective.

We're committed to helping learners master complex material faster, retain information longer, and develop deeper understanding through AI-powered learning tools that adapt to individual needs.

Target Learners

  • University Students - Both undergraduate and graduate students who need to process large volumes of reading materials and course content efficiently.
  • Medical Students - Who need to memorize extensive terminology, procedures, and concepts in a structured and efficient manner.
  • Researchers - Who want to quickly grasp key concepts from new articles or remember critical information from classic papers in their field.

Real-World Use Cases

Course Material Mastery

Students can upload course readings, lecture notes, and textbook chapters to quickly generate focused flashcards that target the most important concepts.

Exam Preparation

SmartFlash identifies knowledge gaps through practice tests and creates personalized flashcard sets focusing specifically on areas needing improvement.

Research Literature Review

Researchers can upload academic papers to extract key findings, methodologies, and conclusions, creating a personalized knowledge base of their field's literature.

Key Features

Flexible Material Upload

Upload PDFs, documents, or paste text directly. SmartFlash processes various formats to extract key information for learning.

AI Knowledge Assessment

Our AI analyzes your responses to identify knowledge gaps and adjusts flashcard difficulty to focus on what you need to learn most.

Learning Games

Turn studying into an engaging experience with games designed to reinforce memory and test understanding in interactive ways.

Our Development Journey

Using agile development principles, we evolved our product from initial concept to final prototype through a series of sprints, each focused on specific aspects of the design thinking process.

Sprint 1: Empathize & Define

We began by understanding our users through interviews, empathy maps, and creating detailed personas to identify the real problems students face when studying.

Conducted 5 detailed user interviews
Created 4 empathy maps
Developed 3 distinct personas
Formulated key problem statements
Persona 1 Persona 2 Persona 3

Sprint 2: Ideate

We brainstormed solutions using "How Might We" questions and the Crazy 8s technique, then created detailed storyboards to visualize the user experience with our product.

Developed 6 "How Might We" questions
Generated 12 solution ideas
Created 4 detailed storyboards
Designed comprehensive user flow diagram
Storyboard 1 Storyboard 2
3

Sprint 3: Low-Fi Prototype

We created a series of low-fidelity prototypes to visualize our solution and gather early feedback before investing in high-fidelity designs.

Created hand-drawn paper prototypes
Conducted first round of expert evaluations
Developed Figma wireframes based on feedback
Conducted second round of expert evaluations
Revised design based on expert feedback

Our Low-Fi Prototyping Process

Paper
Sketches
Expert
Feedback
Figma
Wireframes
Second
Evaluation
Final
Revisions
"The iterative expert evaluation process was crucial in identifying usability issues early, saving significant development time and resources."
Paper Prototype 1 Paper Prototype 2 Paper Prototype 3 Paper Prototype 4
4

Sprint 4: Hi-Fi Prototype

We transformed our wireframes into a high-fidelity interactive prototype with polished UI elements, realistic content, and functional interactions.

Created detailed high-fidelity prototype
Developed think-aloud testing protocol
Conducted user testing sessions
Analyzed usability metrics and user feedback
Finalized prototype based on user feedback

Key Findings from User Testing

Users found the AI-generated flashcards highly relevant to their learning needs

The knowledge assessment feature received positive feedback for its accuracy

Some users requested more customization options for the flashcard interface

Navigation between study and assessment needed improvement

"User testing revealed that our prototype successfully addressed the core pain points identified in our research."

Learner-Centered Design

Throughout our development process, we continuously engaged with target learners and experts to ensure our design meets real user needs.

What We Learned From Users

Information Overwhelm

Students struggle with extracting key concepts from large volumes of study material, leading to inefficient learning.

Time Constraints

Many learners have limited time for creating study materials, preferring automation that doesn't sacrifice quality.

Need for Personalization

Learners want tools that adapt to their existing knowledge and focus on areas where they're struggling.

How User Feedback Shaped Our Design

  • Simplified Upload Process

    Based on cognitive walkthrough feedback, we streamlined the material upload process to reduce overwhelm.

  • Clearer Card Interactions

    User testing revealed confusion with card flipping, so we improved the interaction model.

  • Enhanced Navigation

    Added a clear navigation system after early testers struggled to find key features.

  • Gamification Elements

    Added game modes and achievements based on user feedback about motivation.

Expert Insight

"The integration of AI with proven learning science principles creates a powerful tool for targeted studying. SmartFlash's ability to identify knowledge gaps addresses a critical need in education."

- Educational Technology Expert

Design Principles

Our development process was guided by these core principles, ensuring that SmartFlash delivers an effective, engaging, and personalized learning experience.

Agile Development

We embraced iterative development with short sprints, allowing us to continuously refine our product based on feedback and changing requirements.

  • Regular sprint planning and reviews
  • Continuous integration of user feedback
  • Adaptive planning as requirements evolved

Design Thinking

We followed a human-centered approach, deeply understanding user needs before developing solutions through empathy, ideation, and prototyping.

  • Empathize through user interviews and research
  • Define clear problem statements
  • Ideate multiple potential solutions
  • Prototype and test with real users

Learning Science

Our features are grounded in proven educational theories and cognitive science principles to maximize learning effectiveness.

  • Spaced repetition for optimal memory retention
  • Active recall through interactive flashcards
  • Knowledge assessment to identify learning gaps
  • Gamification to increase motivation and engagement

AI Ethics & Responsibility

We prioritized ethical considerations in our AI implementation, ensuring transparency, fairness, and user control throughout the learning process.

  • Transparent assessment and recommendation processes
  • User control over personal data and learning paths
  • Continuous evaluation to prevent algorithmic bias
  • Privacy-first approach to data collection and storage