{"schema":"BUIDL","d":{"id":21601,"members":[{"hackerId":196150,"projectMemberId":19932,"avatar":"https://cdn.dorahacks.io/static/files/1947c7d996d6fdfb3cdde7946829e1d3.png","name":"Cindyzzz616","handle":"Cindyzzz616","email":"***@***","status":"accepted","role":2,"title":null,"introduction":null},{"hackerId":195952,"projectMemberId":19931,"avatar":"https://cdn.dorahacks.io/static/files/19479e3e029c62d8d3ae0dd448aa14a1.jpeg","name":"Adrien Mery","handle":"U_6a7b03f551f02c","email":"***@***","status":"accepted","role":2,"title":null,"introduction":null},{"hackerId":195549,"projectMemberId":19930,"avatar":"https://cdn.dorahacks.io/static/files/19472d96207a74a2a494a454468bebb9.jpeg","name":"Lucie","handle":"mango","email":"***@***","status":"accepted","role":2,"title":null,"introduction":null}],"pictures":["https://cdn.dorahacks.io/static/files/1947c6088e6ef6177bd43af4eaeab944.png"],"roundProjects":[],"hackathonProjects":[{"id":23851,"hackathon":{"id":749,"tabSet":[{"id":1271,"name":"Submission Guide","slug":"submission","description":"# Tutorial Video\n\n![YouTube](https://youtu.be/yWhQPzxptg0)\n\n# **Getting Started [3-5 MIN]**\n\n**1.** **Submit your BUIDL via [DoraHacks.io](https://dorahacks.io/). You need an account with DoraHacks before you can submit.**\n\nUse the **Log in** button in the upper right corner of the page to access the sign-up options.\n\n

\n\nYou can create your account with either your **GitHub account, Google account, crypto wallet** or **email address**. We recommend connecting your account to GitHub to share your projects with a wider audience.\n\n*If asked for a verification code via email, the email may take a few minutes to arrive. The code expires 10 minutes after you click “**send code**”.\n\n**2.** **Before the submission deadline, make sure you have added your Github link to the project. You can submit the project first, and continue editing until the deadline.**\n\nClick “**Submit BUIDL**”.\n\n

\n\n\n> **→ Already have a BUIDL on DoraHacks?**\n> \n\n1. Click “**Use existing BUIDL**” and select your BUIDL project.\n2. Choose the track you want to enter. \n3. Answer the questions set by the organizer in the input field if applicable.\n\n

\n\n\n> **→ Submitting a new BUIDL?**\n> \n> Click **“Create new BUIDL”** and fill out the form with your project details.\n\n

\n\nBe sure to include **URLs (with http/https://)** for your demo, demo link, and social media.\n\n

\n\n

\n\nOnce you’ve completed the new BUIDL setup, select the relevant track, and click **“Submit for review”**.\n\n

\n\nAfter submitting successfully, you'll see this notification.\n\n

\n\n# **Manage BUIDL submission**\n\nAfter submitting your application, the \"Submit\" button will update to \"Manage Submission\". Click the button to manage your BUIDL's Track/Bounty submission.\n\n

\n\n# **Project Approval**\n\nAfter submission, your project needs to be approved by the Hackathon Organizer before it becomes publicly visible in the Hackathon [BUIDLs gallery](https://dorahacks.io/hackathon/749/buidl).\n\n

\n\n# **Getting Support**\n\nIf you have any questions for the hackathon organizers, feel free to contact them via their dedicated Telegram, Discord, or Slack communication channel. You can also click the \"**Message**\" button next to the organizer's logo to DM them on DoraHacks.\n\n# Need to Update Your BUIDL?\n\nTo make changes to your project, click [Avatar] -> [Profile] to access your Account Center. Then, click the \"**Edit**\" button on the top right of your BUIDL to update your BUIDL information.\n\n

\n\n

"},{"id":1334,"name":"Rules","slug":"rules","description":"1. Be kind and respectful. All hackers must abide by MLH's Code of Conduct.\n\n2. Any projects submitted must be started and completed during the duration of UofTHacks12.\n\n3. 4 hackers maximum per team (anything less including 1 is okay but we encourage finding a full team as you can get a lot more done with 4 people!)\n\n4. Only submit to UofTHacks 12 — projects that submit to other hackathons will be disqualified.\n\n5. All code must be uploaded BEFORE the deadline and linked to DoraHacks — project demos with a working product yet have no code uploaded will be disqualified. The recommend way to upload code is to a PUBLIC Github repository. THIS MUST BE INCLUDED.\n\n6. Public frameworks and libraries are allowed, but submitting mostly copied code will result in project disqualification. We run of the 70-30 rule, where AT LEAST 70% of the code must be yours written during this hackathon, and AT MOST 30% of your code can be code not written during the hackathon.\n\n7. Taking code from any open source repository must be attributed.\n\n8. Each hacker is only allowed to be a part of and create ONE project during this hackathon.\n\n9. Everyone is entered into the main judging track. All opt in prizes/challenges must be submitted in the opt in section before the judging deadline. After this deadline, there are no guarantees we can accommodate last minute changes.\n\n10. You can only apply to a maximum of 3 bounties. This includes MLH bounties, sponsor bounties, and UofThacks bounties. Again, everyone is entered into the main judging track.\n\n11. Anything presented at judging should only be worked on from 7:00pm on Friday to 6:30 AM on Sunday. There should be no coding or building before 7:00pm on Friday, however you can ideate beforehand with your team!\n\n12. Judging will be in-person expo-style; you must have at least 1 person present at judging to qualify for a prize."}],"skills":null,"applied":false,"isCurrentHackerRegistered":false,"buidlsCount":126,"applicationsCount":128,"organization":{"id":2991,"name":"UofTHacks","logo":"https://cdn.dorahacks.io/static/files/193cb37c5ab573d31dd78cf409388681.jpg"},"description":"# Canada’s 1st Student-Run Hackathon \n\nAt UofTHacks, we’re focused on creating a space where everyone feels supported, motivated, and encouraged to bring their ideas to life. Whether you’re an experienced developer or new to hackathons, we’re here to help you grow and turn your ideas into reality. \n\nJoin a vibrant community of over 500 developers, designers, and entrepreneurs for a 36-hour in-person hackathon. From brainstorming creative solutions to building meaningful projects, UofTHacks is where ideas meet action. \n\n**Our application period for UofTHacks 12 has already closed.** Stay up to date with the latest UofTHacks news by following us on [Instagram](https://www.instagram.com/uofthacks/). \n\n[Learn more about UofTHacks here!](https://uofthacks.com/) \n\n\n# ⚠️ **Important Reminder**\n\nBefore submitting your project, make sure to check out the [submission guide](https://dorahacks.io/hackathon/uofthacks/submission) for detailed instructions and requirements. \n\n# 🏃🏻‍♀️ Tracks and Bounties \n\nCheck out our bounties and prize tracks [here](https://dorahacks.io/hackathon/uofthacks/bounties). \n\nThis year, we’re excited to announce our top three overall prizes for the winning teams. Every team member will receive the prize! \n\n- **1st Place**: Meta Quest 3S VR Headset \n *(Includes Batman: Arkham Shadow)* \n- **2nd Place**: Anycubic Kobra 3D Printer \n- **3rd Place**: Fujifilm Instax Polaroid \n\n\n# 💼 Our Sponsors \n\n### Corporate Sponsors \n- [Tech@RBC](https://jobs.rbc.com/ca/en/early-tech-talent) \n- [Ubisoft](https://www.ubisoft.com/en-us/) \n- [1Password](https://1password.com/) \n- [Google DeepMind](https://deepmind.google/) \n- [Google](https://www.google.com/) \n- [DoraHacks](https://dorahacks.io) \n- [Warp](https://www.warp.dev/) \n- [P&G](https://www.pg.ca/en-ca/) \n\n### Academic and Community Partners \n- [Computer Science @ University of Toronto](https://web.cs.toronto.edu/) \n- [SKULE (University of Toronto Engineering Society)](https://skule.ca/) \n- [The Entrepreneurship Hatchery - University of Toronto Faculty of Applied Science and Engineering](https://hatchery.engineering.utoronto.ca/) \n- [University of Toronto Entrepreneurship](https://entrepreneurs.utoronto.ca/) \n- [Red Bull](https://www.redbull.com/ca-en) \n- [MLH](https://mlh.io)\n\n# 📷 Social Media \n\nStay in the loop with the latest updates, announcements, and community highlights by following us on our social media platforms: \n\n- **Instagram**: [@uofthacks](https://www.instagram.com/uofthacks) \n- **X (Twitter)**: [@uofthacks](https://x.com/uofthacks) \n- **LinkedIn**: [UofT Hacks](https://www.linkedin.com/company/uoftorontohacks/)","onboardingCompleted":false,"registerFormUrl":null,"preRegisterTime":0,"publicContactHackerHandle":"uofthacks_offici","hackersCount":339,"winnerAnnounced":true,"teamCount":1,"title":"UofTHacks 12","uname":"uofthacks","imageUrl":"https://cdn.dorahacks.io/static/files/194513683adededb34df9b7486e8d027.png","originUrl":null,"startTime":1737158400,"endTime":1737288000,"timezone":"300","city":null,"visible":true,"approvalStatus":6,"state":1,"voteUrl":null,"voteMechanism":null,"bonusPrice":10000,"bonusMechanism":null,"followersCount":0,"ecosystem":null,"applyGuide":null,"weight":131,"participationForm":"IRL","field":"student run","email":"official@uofthacks.com","contacts":"Email,official@uofthacks.com","externalContacts":null,"telegram":null,"discord":null,"whatsapp":null,"wechat":null,"prizeFundingEscrowed":0,"token":"CAD","prizeSafeForm":0,"prizeSafeNetwork":null,"prizeSafeOwner":null,"prizeSafeWallet":null,"prizeSafePublishDate":null,"hasOnboarding":false,"isPublicTrackJudging":false,"isEndedTrackJudging":false,"question":"[{\"id\":1,\"text\":\"What is your team ID from UofTHacks' Hacker Portal? (number)\",\"required\":true},{\"id\":2,\"text\":\"List all of the Universities or Schools that your team members currently attend.\",\"required\":true},{\"id\":3,\"text\":\"List all the domain names your team has registered with GoDaddy Registry during this hackathon.\",\"required\":false},{\"id\":4,\"text\":\"Share feedback about any technology you interacted with as this hackathon. Remember to mention what tech you're reviewing (e.g. Twilio, Github, DeSo, etc.)\",\"required\":false},{\"id\":5,\"text\":\"Please list every team member names, email address, phone number. Members not listed here will not be eligible for prizes\",\"required\":true},{\"id\":6,\"text\":\"Please confirm that you have read, understood, and agree to all the rules (https://dorahacks.io/hackathon/uofthacks/rules) listed here. You will not be eligible for prizes if you do not confirm. If you have any questions, reach out to an organizer.\",\"required\":true},{\"id\":7,\"text\":\"Which of the following GenAI tools did you use this weekend? OpenAI, Anthropic, Hugging Face, Llama, IBM Watson, Gemini, or None?\",\"required\":true}]","countryId":37,"cityId":1124279679,"venueName":"University of Toronto - Myhal Centre for Engineering Innovation and Entrepreneurship","venueAddress":"55 St George St, Toronto, ON M5S 0C9","category":3,"isEnableBounty":true,"isBountyRequired":false,"isEndedBountyJudging":false,"bountiesLimitForBuidl":3,"isPublicBountyJudging":false,"isMultiTracksAllowed":true,"tracksLimitForBuidl":3,"showIdeaTab":false,"showQuestionTab":false,"showTeamTab":true,"bonusDescription":[],"askHackers":[],"isEnabledQuestions":true,"isEnabledAskHackers":false,"isBuidlsPrivate":false,"trackJudgingMaxScore":20,"bountyJudgingMaxScore":100,"isExtended":true,"oldEndTime":1737286200,"status":2},"status":4,"bounty":null,"track":null,"table":"0","trackObj":{"id":1935,"name":"General Prize","judgingCriteria":"- Design: Quality of UI/UX, aesthetics, and accessibility\n- Completion: Functionality and level of polish\n- Theme Relevance: Creativity and alignment with the theme, Perspective\n- Idea & Originality: Usefulness, innovation, and uniqueness\n- Practicality & Impact: Feasibility and potential impact\n- Pitching: Clarity, organization, and effectiveness of your presentation.","weight":1},"bountyObjs":[{"id":907,"name":"Best \"University of Toronto\" Hack","token":"ONRamp Memberships","bonus":4,"link":"","description":"Four one-year ONRamp memberships will be awarded to prize winners at the event. To be eligible, recipients must be **current University of Toronto full-time students**. We’re still considering ideas for a potential challenge. The prizes include access to the startup office workspace in the Schwartz Reisman Innovation Building, the newest building on campus."},{"id":936,"name":"Best Use of Generative AI","token":"FitBits + Glorious™ KBs","bonus":4,"link":"","description":"Generative AI is rapidly changing the landscape of software development. This category challenges you to build novel applications that leverage the power of Generative AI APIs. Think outside the box and integrate cutting-edge AI models to create innovative solutions with real-world impact.\n\nTo participate, utilize publicly available Generative AI APIs (like those from OpenAI, Anthropic, Hugging Face, Llama, IBM Watson, or Google Gemini) to develop a unique and functional application. This could include:\nAI-powered creative tools: Design an app that allows users to generate unique marketing copy, translate languages in real-time, or create personalized learning experiences.\nIntelligent assistants and automation: Build a chatbot that can provide insightful customer support, or a system that automates complex tasks using natural language processing.\nNext-generation content creation platforms: Develop a platform that empowers users to generate high-quality images, write different kinds of creative text formats, or compose original music with AI assistance.\nThis is your chance to get hands on with cutting edge tech, put your skills on display, and of course, win some awesome prizes!"},{"id":943,"name":"Best Beginner Hack","token":"Amazon Gift Card","bonus":4,"link":"","description":"UofTHacks wants to help encourage beginner students to pursue a pathway in STEM. As such, we have decided to make our UofTHacks challenge, the Best Beginner Hack. These are for students that have been to less than 3 hackathons prior and have no internship experience.\n\nPrize: $50 Amazon Gift Cards for each team member"}]}],"chain":[],"chainList":[],"appliedGrant":false,"acceptRewards":false,"owner":195772,"ownerInfo":{"nickname":"r-weng","username":"U_eb36bb662e2ecc","avatar":"https://cdn.dorahacks.io/static/files/19477353ac8745795336bf04d2b83b1e.png"},"visible":true,"deleted":false,"continuousSponsoring":false,"pageView":0,"sponsoredCount":0,"starCount":0,"sponsoredAmount":"0.00","sponsoredPersons":0,"followers":1,"voteCount":0,"projectMembers":[{"id":19932,"member":{"id":196150,"username":"Cindyzzz616","avatarUrl":"https://cdn.dorahacks.io/static/files/1947c7d996d6fdfb3cdde7946829e1d3.png","nickName":"Cindyzzz616"},"email":"***@***","status":"accepted","role":2,"title":null,"introduction":null},{"id":19931,"member":{"id":195952,"username":"U_6a7b03f551f02c","avatarUrl":"https://cdn.dorahacks.io/static/files/19479e3e029c62d8d3ae0dd448aa14a1.jpeg","nickName":"Adrien Mery"},"email":"***@***","status":"accepted","role":2,"title":null,"introduction":null},{"id":19930,"member":{"id":195549,"username":"mango","avatarUrl":"https://cdn.dorahacks.io/static/files/19472d96207a74a2a494a454468bebb9.jpeg","nickName":"Lucie"},"email":"***@***","status":"accepted","role":2,"title":null,"introduction":null}],"bnbRound":null,"doraGrantDaoTags":[],"techTrees":[-1],"infrastructureTags":[],"otherInfrastructures":[],"lastEditor":{"id":196150,"username":"Cindyzzz616","date":1737593312000},"upvoted":false,"followed":false,"upvoters":{"count":1,"list":[{"id":24324,"hacker":{"username":"mango","avatarUrl":"https://cdn.dorahacks.io/static/files/19472d96207a74a2a494a454468bebb9.jpeg","nickName":"Lucie","introduction":"Hi! I like data :)"},"createdAt":"2025-01-19T17:41:03.081166+08:00","upvotes":"0.00","followed":false}]},"kycStatus":0,"ideas":[],"name":"YouLingo","techniqueField":"","source":"-","vision":"A new perspective on language learning, YouLingo helps users master languages one YouTube video at a time.","projectDescription":"YouLingo is a dynamic web application that offers a fresh perspective on language learning by transforming YouTube videos into engaging language lessons tailored to the user's interests. From cooking to sports, gaming to K-pop, YouLingo empowers users to build fundamental language skills while exploring the content that they love. Through the application, users can explore a diverse library of videos, add their own video URLs to customize their experience, and organize their favourite videos for easy access. By blending entertainment with education, YouLingo makes language learning immersive, personalized, and fun—one video at a time.\n\n### Theoretical Foundations\nThis application is based on the language acquisition theory posited by Stephen Krashen, a renowned American linguist who has written more than 500 articles and books on the second language acquisition and related fields. [1]\nIn his theory, he outlined six hypotheses about how to effectively gain fluency in a second language. They are: \n1. **The Acquisition-Learning Hypothesis:** learning a language involves consciously obtaining knowledge _about_ a language, while the\nprocess of acquisition is unconscious and involves direct interaction _with_ a language. The former approach is used in formal\nlanguage education, which often yields unsatisfactory results. In comparison, the latter approach is the process through which\nchildren come to master their native language.\n2. **The Monitor Hypothesis:** when we are consciously learning a language, there is an internal monitor that judges and corrects the every\nutterance. As a result, fluency is sacrificed to maximize accuracy, which hinders the progress of the learner in the long run.\n3. **The Natural Order hypothesis:** children first acquire the comprehension capacities, then production capacities; they also master languages\nin spoken forms before learning the written forms. Therefore, the natural order of language acquisition is _listening_, _speaking_, _reading_,\nthen _writing_. There are also orders of acquiring different grammatical structures. When adults follow the same order, they are able to\ncommunicate more fluently and effectively.\n4. **The Input Hypothesis:** language input can only be helpful to a learner when they are comprehensible. When they wish to progress,\nthey must take small steps by consuming content that encompass the previous material with small additions. This can be described by the\nanalogy \"i+1\", where i represents the current knowledge and 1 represents the small addition on that basis.\n5. **The Affective Filter Hypothesis:** when learners are in stressful surroundings, their brains filter out the input\nand render it useless. Their interest in the content they consume can also affect how well they internalize the language. \nTherefore, it is important for them to be in a relaxed environment where they can engage with the materials of their choosing and make mistakes.\n6. **The Reading Hypothesis:** our vocabulary expands when we read materials from real-life contexts, rather than engage in rote\nmemorization of vocabulary lists. [2]\nThese hypotheses have proven to be effective from their significant transformation of language instruction and successful results.\n\n### Our Implementation\nYouLingo instantiates these hypotheses in concrete and innovative ways:\n1. It does not explicitly instruct users to learn and memorize grammar rules, conjugations and vocabulary lists. Instead, it provides\nusers with natural input sourced from the wealth of videos on YouTube, which are created by real individuals in real-life contexts.\nThis is similar to how a child picks up their native language from listening to conversations in their surroundings.\n2. When a user is focused on the content of their favourite videos, they are subconsciously taking in their target language without\npressure to perform in a grammatically impeccable manner.\n3. Our application focuses on the first stage of the language acquisition process, since that is the key stage that is often skipped\nor skimmed through. When users are ready, it also provides the potential for them to practice other aspects of the language - for\nexample, they can read the transcripts and hone their production abilities with the quizzes the app generates. Overall, they\nare grounded in the practice of content consumption to ensure sufficient input.\n4. This hypothesis is implemented by the flagship feature of our application, the recommendation system that compares videos with the user's\nknowledge base using a variety of quantifiable linguistic metrics.\n5. Similar to the second hypothesis, this principle emphasizes the importance of a good environment and emotional state in efficacy\nof acquisition. Our application provides content tailored to the user's preferences and expertise, so they can feel at ease with\nthe subject of the materials.\n6. While our application does not focus on reading, the principles from the sixth hypothesis can be generalized to listening materials.\nAs mentioned, we provide users with a large amount of video data that strategically introduce new vocabulary in real-life contexts.\n\n### Why CEFR?\nAt the present stage, we assess the language level of users and the difficulty of videos using the CEFR framework. This system is chosen\nbecause it is used around the world and is a shorthand for quantifying the linguistic complexity of materials. It has six broad levels\nas outlined below:\n- **A1:** Can understand and use familiar everyday expressions and very basic phrases aimed at the satisfaction of needs of a concrete type. Can introduce him/herself and others and can ask and answer questions about personal details such as where he/she lives, people he/she knows and things he/she has. Can interact in a simple way provided the other person talks slowly and clearly and is prepared to help.\n- **A2:** Can understand sentences and frequently used expressions related to areas of most immediate relevance (e.g. very basic personal and family information, shopping, local geography, employment). Can communicate in simple and routine tasks requiring a simple and direct exchange of information on familiar and routine matters. Can describe in simple terms aspects of his/her background, immediate environment and matters in areas of immediate need.\n- **B1:** Can understand the main points of clear standard input on familiar matters regularly encountered in work, school, leisure, etc. Can deal with most situations likely to arise whilst travelling in an area where the language is spoken. Can produce simple connected text on topics which are familiar or of personal interest. Can describe experiences and events, dreams, hopes & ambitions and briefly give reasons and explanations for opinions and plans.\n- **B2:** Can understand the main ideas of complex text on both concrete and abstract topics, including technical discussions in his/her field of specialisation. Can interact with a degree of fluency and spontaneity that makes regular interaction with native speakers quite possible without strain for either party. Can produce clear, detailed text on a wide range of subjects and explain a viewpoint on a topical issue giving the advantages and disadvantages of various options.\n- **C1:** Can understand a wide range of demanding, longer texts, and recognise implicit meaning. Can express him/herself fluently and spontaneously without much obvious searching for expressions. Can use language flexibly and effectively for social, academic and professional purposes. Can produce clear, well-structured, detailed text on complex subjects, showing controlled use of organisational patterns, connectors and cohesive devices.\n- **C2:** Can understand with ease virtually everything heard or read. Can summarise information from different spoken and written sources, reconstructing arguments and accounts in a coherent presentation. Can express him/herself spontaneously, very fluently and precisely, differentiating finer shades of meaning even in more complex situations. [3] \n\nIn the application, these levels are represented by floating point numbers, which makes it possible to more precisely specify the difficulty of a video, word, tense or clause to a greater precision. A1 is quantified as 1.0, A2 as 2.0 and so on, up to C2 as 5.0.\n\n### Sources \n[1] https://rossier.usc.edu/faculty-research/directory/stephen-krashen \n[2] https://sites.ualberta.ca/~obilash/krashen.html#:~:text=Application%20for%20Teaching-,The%20Acquisition%2DLearning%20hypothesis,of%20just%20'learning'%20it \n[3] https://www.coe.int/en/web/common-european-framework-reference-languages/level-descriptions\n\n### Features\n_NOTE: due to time constraints, some of these features have not been fully implemented. The following is a description of the intended design of the application\nwith the core features available for demonstration._\n\n#### User Database\nYouLingo allows users to input topics of interest as tags, and save videos as a list. It also stores a range of linguistic competency data for each user. This includes:\n* Overall CEFR level: This is stored as a floating point number from 0.0 to 5.0, representing levels from A1 to C2. Upon sign-up, the user \n* Lexicon: This is a list of the vocabulary that the user has accumulated from videos they have watched. Each word has an associated CEFR score, and the application keeps\na tally of the number of times the user has encountered that word.\n* Record of Tenses: Similar to the Lexicon, this is a record of the tenses the user has encountered. The following tenses are tracked by the application:\n\n | Available Tenses | |\n |-------------------------------|---------------------------|\n | Infinitive | Present simple |\n | Infinitive passive | Past simple |\n | Infinitive continuous | Present continuous |\n | Infinitive perfect | Present perfect |\n | Infinitive perfect passive | Past perfect |\n | Infinitive perfect continuous | Present perfect continuous |\n | Unbound modal verb | Present perfect passive |\n | Imperative | Present continuous passive |\n | Gerund simple | Gerund perfect |\n | Past participle simple | Past perfect continuous |\n | Gerund perfect passive | Past perfect passive |\n | Gerund perfect continuous | Past continuous passive |\n | Gerund perfect passive | |\n\n* Record of Clauses: This is a record of the types of clauses the user has encountered. They include:\n\n | Available Clause Types |\n |-------------------------------|\n | Adjective clauses |\n | Adverbial clauses |\n | Relative clauses |\n | Noun clauses |\n | Sentences inside parentheses |\n\n[intended but not implemented] Like the lexicon, the record of the types of tenses and clauses also keeps track of the number of times they have been encountered by the user.\nEach time the user watches a video, new words, tenses and clause types are added to their knowledge base, and the tally for existing entries increases.\nAs the user accumulate experience, their overall CEFR level increases automatically based on the tally and average CEFR score of the words in their lexicon, as well as \ntheir familiarity with tenses and clause types. This in turn increases the average difficulty of videos recommended to them, as discussed below.\n\n#### Video Recommendation\nThe user's home page is populated by a series of recommended videos based on the user's topics of interest, their CEFR level and [intended but\nnot implemented] the similarity between the video's language content and the user's knowledge base. The precision of the recommendations can be\nadjusted (for example, users can choose to view videos with a general difficulty level that is within ±0.5 CEFR-score of their personal level,\nand with a word list that has an 80% overlap with their lexicon of familiar vocabulary). The videos are ranked based on these metrics, and new videos are shown upon refreshing the page.\n\n#### Viewing Videos\nEach video is accompanied by the following components:\n- A transcript in the user's target language, and a translation into the language of the user's choice.\n- [intended but not implemented] A matching score that indicates the video's similarity to the \nlinguistic information that the user has already encountered. This breaks down into three categories:\n - vocabulary\n - tenses\n - clause types\nwith the same set of available tenses and clause types as the one in the user database.\n- A general difficulty score, rated in terms of CEFR levels. This is also expanded into the same categories as above.\n- A counter that keeps track of the number of times the user has watched the video.\n- A button to save the video.\n \n#### Saving Videos\nSaved videos can be retrieved under a \"My Videos\" tab. This encourages users to review videos to ensure sufficient repetition.\n[intended but not implemented] Videos would be considered as complete after a custom number of replays and the user would be \nallowed to add newer, more challenging videos to their rotation.\n\n#### Quizzing\nA short quiz is generated for each video, and the user can input their answer to be assessed on their reading and writing abilities.","teamDescription":"YouLingo by Adrien Mery, Cindy Zhang, Lucie Yang, and Rui Weng.\n\nContact us at:\nadrien.mery@mail.utoronto.ca\ncxy.zhang@mail.utoronto.ca\nlucie.yang@mail.utoronto.ca\nrui.weng@mail.utoronto.ca\n\nDiscord: le5610","githubPage":"https://github.com/Cindyzzz616/YouLingo","githubVerify":0,"demoLink":null,"demoVideo":null,"ownerTitle":null,"ownerIntroduction":null,"twitterVerified":false,"weibo":null,"nft":null,"scOwner":"","editTime":1737593312,"upvotes":"0.00","isRecruitingEnabled":false,"recruitingInfo":"","recruitingLink":null,"twitter":null,"facebook":null,"instagram":null,"socialTelegram":null,"socialDiscord":null,"socialLinks":["https://youtu.be/Blfl3Y93Z-4?si=I17V-iv0eG_5Su-k"],"showedFunding":false,"agentStatus":null,"createdAt":"2025-01-19T11:17:08.881921+08:00","updatedAt":"2025-01-23T08:48:32.503865+08:00","milestoneEditor":null,"path":"/buidl/21601","techField":"","techFieldAry":[],"techTree":[-1],"tags":[],"otherTags":[],"origin":"-","intro":"YouLingo is a dynamic web application that offers a fresh perspective on language learning by transforming YouTube videos into engaging language lessons tailored to the user's interests. From cooking to sports, gaming to K-pop, YouLingo empowers users to build fundamental language skills while exploring the content that they love. Through the application, users can explore a diverse library of videos, add their own video URLs to customize their experience, and organize their favourite videos for easy access. By blending entertainment with education, YouLingo makes language learning immersive, personalized, and fun—one video at a time.\n\n### Theoretical Foundations\nThis application is based on the language acquisition theory posited by Stephen Krashen, a renowned American linguist who has written more than 500 articles and books on the second language acquisition and related fields. [1]\nIn his theory, he outlined six hypotheses about how to effectively gain fluency in a second language. They are: \n1. **The Acquisition-Learning Hypothesis:** learning a language involves consciously obtaining knowledge _about_ a language, while the\nprocess of acquisition is unconscious and involves direct interaction _with_ a language. The former approach is used in formal\nlanguage education, which often yields unsatisfactory results. In comparison, the latter approach is the process through which\nchildren come to master their native language.\n2. **The Monitor Hypothesis:** when we are consciously learning a language, there is an internal monitor that judges and corrects the every\nutterance. As a result, fluency is sacrificed to maximize accuracy, which hinders the progress of the learner in the long run.\n3. **The Natural Order hypothesis:** children first acquire the comprehension capacities, then production capacities; they also master languages\nin spoken forms before learning the written forms. Therefore, the natural order of language acquisition is _listening_, _speaking_, _reading_,\nthen _writing_. There are also orders of acquiring different grammatical structures. When adults follow the same order, they are able to\ncommunicate more fluently and effectively.\n4. **The Input Hypothesis:** language input can only be helpful to a learner when they are comprehensible. When they wish to progress,\nthey must take small steps by consuming content that encompass the previous material with small additions. This can be described by the\nanalogy \"i+1\", where i represents the current knowledge and 1 represents the small addition on that basis.\n5. **The Affective Filter Hypothesis:** when learners are in stressful surroundings, their brains filter out the input\nand render it useless. Their interest in the content they consume can also affect how well they internalize the language. \nTherefore, it is important for them to be in a relaxed environment where they can engage with the materials of their choosing and make mistakes.\n6. **The Reading Hypothesis:** our vocabulary expands when we read materials from real-life contexts, rather than engage in rote\nmemorization of vocabulary lists. [2]\nThese hypotheses have proven to be effective from their significant transformation of language instruction and successful results.\n\n### Our Implementation\nYouLingo instantiates these hypotheses in concrete and innovative ways:\n1. It does not explicitly instruct users to learn and memorize grammar rules, conjugations and vocabulary lists. Instead, it provides\nusers with natural input sourced from the wealth of videos on YouTube, which are created by real individuals in real-life contexts.\nThis is similar to how a child picks up their native language from listening to conversations in their surroundings.\n2. When a user is focused on the content of their favourite videos, they are subconsciously taking in their target language without\npressure to perform in a grammatically impeccable manner.\n3. Our application focuses on the first stage of the language acquisition process, since that is the key stage that is often skipped\nor skimmed through. When users are ready, it also provides the potential for them to practice other aspects of the language - for\nexample, they can read the transcripts and hone their production abilities with the quizzes the app generates. Overall, they\nare grounded in the practice of content consumption to ensure sufficient input.\n4. This hypothesis is implemented by the flagship feature of our application, the recommendation system that compares videos with the user's\nknowledge base using a variety of quantifiable linguistic metrics.\n5. Similar to the second hypothesis, this principle emphasizes the importance of a good environment and emotional state in efficacy\nof acquisition. Our application provides content tailored to the user's preferences and expertise, so they can feel at ease with\nthe subject of the materials.\n6. While our application does not focus on reading, the principles from the sixth hypothesis can be generalized to listening materials.\nAs mentioned, we provide users with a large amount of video data that strategically introduce new vocabulary in real-life contexts.\n\n### Why CEFR?\nAt the present stage, we assess the language level of users and the difficulty of videos using the CEFR framework. This system is chosen\nbecause it is used around the world and is a shorthand for quantifying the linguistic complexity of materials. It has six broad levels\nas outlined below:\n- **A1:** Can understand and use familiar everyday expressions and very basic phrases aimed at the satisfaction of needs of a concrete type. Can introduce him/herself and others and can ask and answer questions about personal details such as where he/she lives, people he/she knows and things he/she has. Can interact in a simple way provided the other person talks slowly and clearly and is prepared to help.\n- **A2:** Can understand sentences and frequently used expressions related to areas of most immediate relevance (e.g. very basic personal and family information, shopping, local geography, employment). Can communicate in simple and routine tasks requiring a simple and direct exchange of information on familiar and routine matters. Can describe in simple terms aspects of his/her background, immediate environment and matters in areas of immediate need.\n- **B1:** Can understand the main points of clear standard input on familiar matters regularly encountered in work, school, leisure, etc. Can deal with most situations likely to arise whilst travelling in an area where the language is spoken. Can produce simple connected text on topics which are familiar or of personal interest. Can describe experiences and events, dreams, hopes & ambitions and briefly give reasons and explanations for opinions and plans.\n- **B2:** Can understand the main ideas of complex text on both concrete and abstract topics, including technical discussions in his/her field of specialisation. Can interact with a degree of fluency and spontaneity that makes regular interaction with native speakers quite possible without strain for either party. Can produce clear, detailed text on a wide range of subjects and explain a viewpoint on a topical issue giving the advantages and disadvantages of various options.\n- **C1:** Can understand a wide range of demanding, longer texts, and recognise implicit meaning. Can express him/herself fluently and spontaneously without much obvious searching for expressions. Can use language flexibly and effectively for social, academic and professional purposes. Can produce clear, well-structured, detailed text on complex subjects, showing controlled use of organisational patterns, connectors and cohesive devices.\n- **C2:** Can understand with ease virtually everything heard or read. Can summarise information from different spoken and written sources, reconstructing arguments and accounts in a coherent presentation. Can express him/herself spontaneously, very fluently and precisely, differentiating finer shades of meaning even in more complex situations. [3] \n\nIn the application, these levels are represented by floating point numbers, which makes it possible to more precisely specify the difficulty of a video, word, tense or clause to a greater precision. A1 is quantified as 1.0, A2 as 2.0 and so on, up to C2 as 5.0.\n\n### Sources \n[1] https://rossier.usc.edu/faculty-research/directory/stephen-krashen \n[2] https://sites.ualberta.ca/~obilash/krashen.html#:~:text=Application%20for%20Teaching-,The%20Acquisition%2DLearning%20hypothesis,of%20just%20'learning'%20it \n[3] https://www.coe.int/en/web/common-european-framework-reference-languages/level-descriptions\n\n### Features\n_NOTE: due to time constraints, some of these features have not been fully implemented. The following is a description of the intended design of the application\nwith the core features available for demonstration._\n\n#### User Database\nYouLingo allows users to input topics of interest as tags, and save videos as a list. It also stores a range of linguistic competency data for each user. This includes:\n* Overall CEFR level: This is stored as a floating point number from 0.0 to 5.0, representing levels from A1 to C2. Upon sign-up, the user \n* Lexicon: This is a list of the vocabulary that the user has accumulated from videos they have watched. Each word has an associated CEFR score, and the application keeps\na tally of the number of times the user has encountered that word.\n* Record of Tenses: Similar to the Lexicon, this is a record of the tenses the user has encountered. The following tenses are tracked by the application:\n\n | Available Tenses | |\n |-------------------------------|---------------------------|\n | Infinitive | Present simple |\n | Infinitive passive | Past simple |\n | Infinitive continuous | Present continuous |\n | Infinitive perfect | Present perfect |\n | Infinitive perfect passive | Past perfect |\n | Infinitive perfect continuous | Present perfect continuous |\n | Unbound modal verb | Present perfect passive |\n | Imperative | Present continuous passive |\n | Gerund simple | Gerund perfect |\n | Past participle simple | Past perfect continuous |\n | Gerund perfect passive | Past perfect passive |\n | Gerund perfect continuous | Past continuous passive |\n | Gerund perfect passive | |\n\n* Record of Clauses: This is a record of the types of clauses the user has encountered. They include:\n\n | Available Clause Types |\n |-------------------------------|\n | Adjective clauses |\n | Adverbial clauses |\n | Relative clauses |\n | Noun clauses |\n | Sentences inside parentheses |\n\n[intended but not implemented] Like the lexicon, the record of the types of tenses and clauses also keeps track of the number of times they have been encountered by the user.\nEach time the user watches a video, new words, tenses and clause types are added to their knowledge base, and the tally for existing entries increases.\nAs the user accumulate experience, their overall CEFR level increases automatically based on the tally and average CEFR score of the words in their lexicon, as well as \ntheir familiarity with tenses and clause types. This in turn increases the average difficulty of videos recommended to them, as discussed below.\n\n#### Video Recommendation\nThe user's home page is populated by a series of recommended videos based on the user's topics of interest, their CEFR level and [intended but\nnot implemented] the similarity between the video's language content and the user's knowledge base. The precision of the recommendations can be\nadjusted (for example, users can choose to view videos with a general difficulty level that is within ±0.5 CEFR-score of their personal level,\nand with a word list that has an 80% overlap with their lexicon of familiar vocabulary). The videos are ranked based on these metrics, and new videos are shown upon refreshing the page.\n\n#### Viewing Videos\nEach video is accompanied by the following components:\n- A transcript in the user's target language, and a translation into the language of the user's choice.\n- [intended but not implemented] A matching score that indicates the video's similarity to the \nlinguistic information that the user has already encountered. This breaks down into three categories:\n - vocabulary\n - tenses\n - clause types\nwith the same set of available tenses and clause types as the one in the user database.\n- A general difficulty score, rated in terms of CEFR levels. This is also expanded into the same categories as above.\n- A counter that keeps track of the number of times the user has watched the video.\n- A button to save the video.\n \n#### Saving Videos\nSaved videos can be retrieved under a \"My Videos\" tab. This encourages users to review videos to ensure sufficient repetition.\n[intended but not implemented] Videos would be considered as complete after a custom number of replays and the user would be \nallowed to add newer, more challenging videos to their rotation.\n\n#### Quizzing\nA short quiz is generated for each video, and the user can input their answer to be assessed on their reading and writing abilities.","images":["https://cdn.dorahacks.io/static/files/1947c6088e6ef6177bd43af4eaeab944.png"],"team":"YouLingo by Adrien Mery, Cindy Zhang, Lucie Yang, and Rui Weng.\n\nContact us at:\nadrien.mery@mail.utoronto.ca\ncxy.zhang@mail.utoronto.ca\nlucie.yang@mail.utoronto.ca\nrui.weng@mail.utoronto.ca\n\nDiscord: le5610","github":"https://github.com/Cindyzzz616/YouLingo","demo":null,"video":null,"socialTwitter":null,"socialFacebook":null,"socialInstagram":null,"nftId":null,"haxonBuidls":[{"id":23851,"projectId":21601,"name":"YouLingo","track":"General Prize","bounties":["Best \"University of Toronto\" Hack","Best Use of Generative AI","Best Beginner Hack"],"haxonId":749,"haxonName":"UofTHacks 12","status":2,"haxonCreateAt":"2025/01/18 00:00:00 UTC"}],"kudoData":null,"bountyObjs":[],"tracks":[],"badges":["{\"schema\":\"BADGE\",\"d\":{\"index\":\"b19442\",\"badgeType\":\"buidl\",\"path\":\"/buidl/21601/achievement/b19442\",\"ownerId\":21601,\"iconName\":\"b0\",\"updatedDate\":\"2025/01/19\",\"title\":\"UofTHacks 12\",\"detail\":\"Participation\",\"tag\":\"Hackathon\",\"imageUrl\":\"https://cdn.dorahacks.io/static/badge/b0_UofTHacks~c3212.webp\",\"shareImageUrl\":\"https://cdn.dorahacks.io/static/badge/b0_UofTHacks~c3212.jpg\",\"id\":19442,\"metaInfo\":{\"type\":\"HACKATHON_PARTICIPATION\",\"hackathonId\":749,\"title\":\"UofTHacks 12\"},\"createdAt\":1737257158,\"updatedAt\":1737257158,\"type\":0,\"subjectId\":749,\"metadata\":{},\"buidl\":21601}}"]}}