我即将升入高中高年级(12 年级),对计算机科学和软件工程感兴趣。虽然我是一名自学成才的学生,但我的同学经常请我以更“人性化”的方式解释概念,这促使我充分利用“教会他们钓鱼”的力量,引导他们了解底层原理,而不是解释具体问题。为了解决这一教育差距,我开发了一款移动应用,让用户可以扫描教科书页面,并接收 YouTube 视频链接以供进一步学习。这样,同行就可以更轻松地学习核心概念,而不会完全迷失。 Mosaic Learn 是一个基于 React Native 和 Expo 构建的前端应用,后端则采用了 Firebase、Gemini Dev API 和 YouTube Search API。当用户在我们的界面中拍摄文档照片时,我们会使用 Google MLKit 进行跨平台文本提取。然后,我们将这些信息发送到 Gemini 1.5 Flash API 进行解析,并返回一个 JSON,其中包含文档摘要和搜索字词数组。然后,我们会将这些搜索字词馈送到 YouTube Results API,并将返回的结果保存到 Firebase,以便用户访问其扫描记录。Mosaic Learn 是我首次使用生成式 AI 来帮助像我这样的学生更快、更深入地学习概念。我们希望 Mosaic Learn 能让全球学生更轻松、更愉快、更高效地学习。
可采用以下设备打造
Firebase
YouTube Search List API 端点
团队
更新者
Reality5D
发件人
美国
[[["易于理解","easyToUnderstand","thumb-up"],["解决了我的问题","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["没有我需要的信息","missingTheInformationINeed","thumb-down"],["太复杂/步骤太多","tooComplicatedTooManySteps","thumb-down"],["内容需要更新","outOfDate","thumb-down"],["翻译问题","translationIssue","thumb-down"],["示例/代码问题","samplesCodeIssue","thumb-down"],["其他","otherDown","thumb-down"]],[],[],[],null,["# Mosaic Learn\n\n[More Apps](/competition/vote) \n\nMosaic Learn\n============\n\nScan pages, get YouTube tutorials on key concepts. \nVote \nVoted!\nWhat it does\n\nI am a rising senior in high school (12th grade) interested in computer science and software engineering. While I am a self-directed learner, my classmates often ask my help to explain concepts in a more \"user-friendly\" manner, leading me to harness the power of \"teaching them to fish\"--guiding them to understand the underlying principles, instead of explaining individual problems. To address this educational gap, I worked on a mobile application that allows users to scan textbook pages and receive links to YouTube videos for further learning. This way, my peers can more easily learn core concepts without being completely lost. \nMosaic Learn is an application built on top of React Native and Expo for the Front end and Firebase, Gemini Dev API and YouTube Search API on the backend. When a user takes a picture of a document in our UI, we use Google MLKit for cross-platform text extraction. We then send this information to the Gemini 1.5 Flash API for parsing and return a JSON with a summary of the document and an array of search terms. We then feed these search terms into the YouTube results API and save the returned results to Firebase, so users can access their scan history. Mosaic Learn is my first step into using GenAI to help students like me learn concepts more quickly and thoroughly. We hope that Mosaic Learn will make education more accessible, engaging, and effective for students worldwide. \nBuilt with\n\n- Firebase\n- YouTube Search List API Endpoint \nTeam \nBy\n\nReality5D \nFrom\n\nUnited States \n[](/competition/vote)"]]