AINKI
Project Overview
AINKI is a mobile app concept that uses AI to summarize content and turn it into digital flashcards or quizzes, making learning more efficient. This case study covers everything from research to the final high-fidelity prototypes.
Problem Statement
In today’s information-rich era, both students and professionals struggle with the overwhelming volume of available content. The process of distilling this information into manageable, learnable chunks is time-consuming and exhausting, so I aimed to make this process easier.
Project Goal
My objective was to create a Minimum Viable Product (MVP) that enables users to efficiently summarize documents into interactive index cards or quizzes. AINKI serves as a minimalist yet powerful tool to enhance learning and information retention.
My role
As the sole UX designer on this project, I was responsible for every stage of the design process, from research and conceptualization to prototyping and usability testing.
The design process followed a mix of Design Thinking and a Lean UX approach, with a focus on rapid iterations and constant user feedback.
Key stages:
- Research: Competitive analysis, user interviews, and market research
- Define: Personas, user journey mapping, and feature prioritization
- Ideate: Wireframing and low-fidelity prototypes
- Test: Formative usability testing and iteration
- Deliver: High-fidelity UI mockups and final usability testing
Competitive Analysis: Pro and Contra of Existing Apps
The project began with a competitive analysis, examining top-rated apps like Quizlet, Anki, and other learning tools. This revealed areas of improvement and opportunities for AINKI:
- Streamlined usability: Reduce complex customization options.
- AI-assisted content creation: Automate the process of summarizing content and creating quizzes/flashcards.
- Customization for study material: Flexibility without overwhelming users with choices.
Market Research: Identifying Key Trends in Learning Apps
To complement the competitive analysis, I did market research, identifying key trends in digital education. Those insights are based on survey insights for example Artificial Intelligence in Education. 2023 Survey Insights or LinkedIn Articles from various AI specialists such as Kyle Tobin´s article Redesigning Education: The Imperative of Skill-Based Learning in the Era of Generative AI and helped me spot some key trends in learning apps:
- Personalized Learning: Adaptive technologies tailoring experiences to individual users
- AI and Automation: Leveraging AI for task automation to enhance focus on content retention
- Gamification: Incorporating game-like elements to boost user engagement
- Microlearning: Offering bite-sized, easily digestible information for on-the-go learning
These insights provided a solid foundation for developing AINKI’s core features and user experience.
Persona Development & User Journey Mapping
Due to time constraints, I conducted informal interviews with a small group of potential users—friends, family, and colleagues who were students or professionals. This uncovered some key insights with which I created 3 Personas and the respective User Journey Mapping. Through User Journey Mapping, I explored happy paths and potential pain points in the learning process, focusing on how AINKI could streamline document summarization, flashcard creation, and quiz generation. This journey mapping also led to the development of a feature backlog, where each feature corresponded to a specific user pain point.
Feature Backlog & Prioritization
The product backlog for AINKI was derived from persona-based needs and organized by priority, focusing on solving key user problems:
I developed low-fidelity wireframes to visualize the app’s core functionality. These wireframes focused on key user flows, from document upload to quiz review, ensuring that each step aligned with user needs identified in the research phase.
To make the user journey clearer, I incorporated a user flow into the wireframe stage. This diagram illustrated how users would navigate from the home screen to AI-summarized flashcards, and then to customized quizzes, ensuring that no steps were missed and that the flow was intuitive.
I tested with a small group of people to get some feedback on the prototype and received valuable feedback:
- Improve Navigation: Clear navigation within all screens
- Card and Quiz Usability: Users thought learning flashcards and the quiz was unintuitive
- Onboarding & First-Time Experience: No visible onboarding flow for new users
I addressed these issues in subsequent design iterations by improving navigation and the card and quiz usability. The onboarding even though is a really important step is not in the scope of my mvp.
A consistent design system is crucial for scaling the app and ensuring a cohesive user experience. I established this system early, including typography, color schemes, and button styles.
Accessibility Considerations:
- WCAG-compliant color contrast for legibility
- Typography optimized for readability across different screen sizes
- Button styles that were large enough for mobile devices, ensuring tap targets met industry standards for accessibility
These standards were maintained throughout the project, ensuring that AINKI was accessible to users with varying abilities.
Taking all the feedback from wireframe testing, I refined the designs into polished, high-fidelity mockups. This iteration focused on solving specific issues that arose during the wireframe testing phase:
The 2nd round of usability testing was held with high-fidelity mockups. This time 4 participants were tested with the same test script to ensure comparability:
Finalizing the design
I finalized the design with the following improvements:
- Redesigning card details for improved clarity and functionality.
- Updating the visual representation of learning progress.
- Introducing a document upload feature with clear user feedback.
- Implementing a favorites system for enhanced customization.
Changing Card Details
The card details feature was updated to improve usability. Users were confused by the options menu for decks and quizzes, so I removed the option to make it more intuitive. Additionally, the button to start a deck or quiz was revamped to have a more cohesive and fitting appearance, making it easier for users to identify and interact with.
Changing Cards
Users found the “Learned” label unclear in its current context. The color-coded progress indicator also caused confusion for most users. To address this, I replaced the color indicator with a numerical one, providing a clearer overview of how many cards or questions have already been learned from a deck or quiz.
Additionally, I implemented a “Favorites” feature, allowing users to mark specific decks or quizzes. These favorites are displayed in the home view under the corresponding “Overview” section, giving users more control and flexibility in customizing their experience.
Introducing Document Upload & Loading Indicator
Users highlighted the lack of functionality for uploading documents, creating summaries, or generating index card decks and quizzes directly from those documents. In response, I introduced a document upload feature. Now, users can upload a document, view its contents, and easily create a summary, index card deck, or quiz from that view. Once a deck or quiz is created, users can directly navigate to it by clicking the corresponding headline. Additionally, the document remains linked within the deck or quiz editor, ensuring easy access for further review or editing.
To improve user experience, I also added a loading indicator. This provides clear feedback while the system processes uploads or generates content, ensuring users are informed during longer operations.
SPLASH SCREEN
DECK-CARD-FRONT
QUIZ-OVERVIEW
DOCUMENT-OVERVIEW
HOMESCREEN
DECK-CARD-BACK
QUESTION-OVERVIEW
DOCUMENT-UPLOAD
DECK-OVERVIEW
CARD-SWIPE
QUESTION-WRONG
LOADING-SCREEN
CARD-OVERVIEW
DECK-RESULT
QUIZ-RESULT
DOCUMENT-DETAIL
Working on AINKI taught me the importance of finding the right balance – between creative ideas and practical features that users actually need. By focusing on core functionality first and continuously adapting based on user feedback, I created something that really helps people learn more efficiently.
However, one of my biggest takeaways was realizing the limitations of working solo. While I’m proud of what I built, showing the project to others revealed blind spots I hadn’t considered – like proper error handling when uploads fail. These weren’t obvious to me during development but became clear through user interactions.
This project reinforced two key lessons:
- Start with the essentials and build from there – not every cool feature needs to be in the first version
- Get your work in front of others early and often – fresh perspectives always reveal something new
Looking back, while there’s always room for improvement, this experience has significantly shaped how I approach UX design, making me a stronger designer who values user feedback more than ever.