/flashcard-notes

Subject: Flashcards Chrome Extension PRD - Competing with Rememberry

Topic: Flashcards Chrome Extension

Introduction:

Our goal is to develop a Chrome extension that helps users translate and memorize foreign language words and phrases while browsing the web. The extension will aim to compete with Rememberry, which has a poor user interface and over 10,000 users. We will focus on improving user experience and adding features based on the feedback from Rememberry's users.

Problem Statement:

Rememberry, despite having a considerable user base, suffers from a poor user interface and lacks certain features that users have requested in their reviews. There is a need for a more intuitive, user-friendly flashcards Chrome extension that addresses these issues and enhances the overall learning experience.

Goals and Objectives:

  • Develop a more user-friendly and visually appealing user interface.
  • Address user feedback and implement features requested by Rememberry's users.
  • Attract and retain users by offering a superior learning experience.

User Stories:

  • As a user, I want to be able to translate words and phrases while browsing the web.
  • As a user, I want to save translated words and phrases to flashcards for easy memorization.
  • As a user, I want to have the option to edit the source text and translations.
  • As a user, I want to listen to the pronunciation of translated words in the target language.
  • As a user, I want to be able to export my flashcards in a readable format.

Technical Requirements:

  • Develop a Chrome extension compatible with the latest version of Google Chrome.
  • Implement a user-friendly and visually appealing UI/UX design.
  • Integrate translation capabilities for 100+ languages.
  • Enable text-to-speech functionality for translated words and phrases.
  • Develop a system for organizing flashcards into decks.
  • Implement a repetition algorithm based on scientific research of human memory.
  • Develop an offline mode for repetition sessions

Benefits:

  • Improved user experience with an intuitive UI/UX design.
  • Enhanced learning experience by addressing user feedback and feature requests.
  • Increased user engagement and retention.

KPIs:

  • Achieve a minimum of 15,000 users within the first 6 months after launch.
  • Maintain a minimum average rating of 4.5 stars on the Chrome Web Store.
  • Achieve a minimum of 80% user retention within the first 3 months after launch.

Development Risks:

  • Potential delays in development due to unforeseen technical issues.
  • Possible difficulties in integrating third-party APIs for translation and text-to-speech functionalities.
  • Competition from other language learning extensions and apps.

Conclusion:

Developing a flashcards Chrome extension that addresses the shortcomings of Rememberry presents an opportunity to attract a large user base and offer a superior language learning experience. By focusing on user feedback, implementing requested features, and delivering an intuitive user interface, we can successfully compete with Rememberry and establish our extension as a leading language learning tool in the market.


> A spaced repetition algorithm is a learning technique that schedules the review of content at increasing intervals to optimize long-term retention. This method is based on the observation that people are more likely to remember information when it is studied and reviewed at spaced intervals, rather than crammed in a short period.

The algorithm works by adjusting the intervals between reviews according to the learner's performance. When the learner successfully recalls a piece of information, the interval before the next review is increased. If the learner struggles or fails to recall the information, the interval is decreased.

Here's a basic outline of how a spaced repetition algorithm works:

Introduce new content: The learner is presented with new material (e.g., vocabulary words, grammar rules, etc.).

Initial review: The learner reviews the new content after a short interval (e.g., a day).

Assess performance: The learner's performance is evaluated through quizzes or other forms of assessment.

Schedule next review: Based on the learner's performance, the algorithm determines the optimal time for the next review.

Repeat steps 3-4: The process of assessing performance and scheduling reviews is repeated, with intervals increasing for correct responses and decreasing for incorrect ones.

To implement a spaced repetition algorithm in your app, you can use an existing algorithm like the Leitner System or the SuperMemo algorithm (SM-2, SM-15, etc.), or develop your own based on scientific research in memory and learning.