NomaDamas

Show GN: EBS Gurapinggala Teacher - 거짓말 에이전트 EBS Gurapingala Teacher - AI 거짓말 에이전트와 교사용 모니터링 대시보드 GitHub: NomaDamas/EBS-Gurapingala-teacher 소개: EBS <생각의 멸종>에서 학생 대상 AI 실험을 위해 개발한 거짓말 AI 챗봇 및 교사용 모니터링 도구...

Teaching students to question authority - including the authority of AI: a classroom misinformation experiment (tools open-sourced) Hi everyone! I'm an undergraduate student and independent developer from South Korea. I'm sharing this here because the experiment touches something this community thinks about deeply: how students relate to authority - including the new authority of AI systems. I recently participated in an educational experiment featured in The Extinction of Thinking (생각의 멸종), a documentary by EBS, South Korea's public educational broadcaster. The question was simple: Can students recognize misinformation when it comes from a confident, convincing AI chatbot? What we did We conducted an experiment in real middle school history and ethics classes. Teachers prepared false claims and examples in advance. I helped design the experiment and developed two tools: - AI misinformation chatbot: intentionally delivers misleading information based on teacher-provided scenarios, with randomized difficulty levels. - Teacher dashboard: allows teachers to monitor students' conversations and responses during the activity. The goal wasn't to build a better chatbot. It was to create an environment where students could experience how easily AI-generated information might influence their understanding. What happened In the classroom experiment, the participating students failed to identify the misinformation, even while attending lessons, completing assignments, and discussing the material. This wasn't a large-scale scientific study, and I wouldn't generalize the results to all students. But seeing this happen in an actual classroom raised some uncomfortable questions. Are students learning to understand information, or simply learning to obtain answers? And how do we teach critical thinking when AI can generate convincing explanations for things that aren't true? Open source I decided to make the classroom tools available as an open-source project through NomaDamas so other educators and developers can experiment with similar activities. GitHub: NomaDamas/EBS-Gurapingala-teacher The experiment is featured in an EBS documentary premiering on November 2, 2026. Official program page: docuprime.ebs.co.kr --- I'd love to hear this community's perspective: How do we teach students to question AI-generated answers rather than automatically trust them - without teaching them to distrust everything? Have you tried anything similar in your classrooms?

An activity design challenge: teaching students to distrust a confident AI chatbot - we ran it in real classrooms and open-sourced the tools Hi everyone! I'm an undergraduate student and independent developer from South Korea, posting here because this project is at its core an instructional design problem. I recently participated in an educational experiment featured in The Extinction of Thinking (생각의 멸종), a documentary by EBS, South Korea's public educational broadcaster. The design question was: Can students recognize misinformation when it comes from a confident, convincing AI chatbot? What we did We conducted an experiment in real middle school history and ethics classes. Teachers prepared false claims and examples in advance. I helped design the experiment and developed two tools: - AI misinformation chatbot: intentionally delivers misleading information based on teacher-provided scenarios, with randomized difficulty levels. - Teacher dashboard: allows teachers to monitor students' conversations and responses during the activity. The goal wasn't to build a better chatbot. It was to create a learning environment where students could experience how easily AI-generated information might influence their understanding. What happened In the classroom experiment, the participating students failed to identify the misinformation, even while attending lessons, completing assignments, and discussing the material. This wasn't a large-scale scientific study, and I wouldn't generalize the results to all students. But seeing this happen in an actual classroom raised some interesting questions. Are students learning to understand information, or simply learning to obtain answers? And how do we teach critical thinking when AI can generate convincing explanations for things that aren't true? Open source I decided to make the classroom tools available as an open-source project through NomaDamas so other educators and developers can experiment with similar activities. GitHub: NomaDamas/EBS-Gurapingala-teacher The experiment is featured in an EBS documentary premiering on November 2, 2026. Official program page: docuprime.ebs.co.kr --- My question for this community: If you were designing this as a learning activity - scaffolding, debrief, assessment - how would you structure it so students learn to question AI-generated answers rather than automatically trust them?

We built a chatbot that lies to students on purpose - classroom experiment on AI misinformation, now open source (EBS documentary) Hi everyone! I'm an undergraduate student and independent developer from South Korea. I recently participated in an educational experiment featured in The Extinction of Thinking (생각의 멸종), a documentary by EBS, South Korea's public educational broadcaster. The question was simple: Can students recognize misinformation when it comes from a confident, convincing AI chatbot? What we did We conducted an experiment in real middle school history and ethics classes. Teachers prepared false claims and examples in advance. I helped design the experiment and developed two tools: - AI misinformation chatbot: intentionally delivers misleading information based on teacher-provided scenarios, with randomized difficulty levels. - Teacher dashboard: allows teachers to monitor students' conversations and responses during the activity. The goal wasn't to build a better chatbot. It was to create an environment where students could experience how easily AI-generated information might influence their understanding. What happened In the classroom experiment, the participating students failed to identify the misinformation, even while attending lessons, completing assignments, and discussing the material. This wasn't a large-scale scientific study, and I wouldn't generalize the results to all students. But seeing this happen in an actual classroom raised some interesting questions. Are students learning to understand information, or simply learning to obtain answers? And how do we teach critical thinking when AI can generate convincing explanations for things that aren't true? Open source I decided to make the classroom tools available as an open-source project through NomaDamas so other educators and developers can experiment with similar activities. GitHub: NomaDamas/EBS-Gurapingala-teacher The experiment is featured in an EBS documentary premiering on November 2, 2026. Official program page: docuprime.ebs.co.kr --- I'd really love to hear from teachers and education researchers here: How would you design a classroom activity that teaches students to question AI-generated answers rather than automatically trust them? And have you tried anything similar with your students?

Open source do GitHub: #15 a #11 | Vol. 13 #shorts Os projetos #15 a #11 do Top 15 open source do GitHub, Vol. 13, 10 segundos para cada um. #15 HQTUI: profullstack/hqtui #14 Amagine3D: amagine-ai/Amagine3D #13 slides-grab: NomaDamas/slides-grab #12 Snitch: aixisstudio/Snitch #11 Glide: michaelshimeles/glide Vídeo completo com os 15: youtu.be Oferecimento: Hallen Tech, hallentech.com #shorts #opensource #github

Mais 15 projetos open source do GitHub que valem o seu tempo | Vol. 13 Mais 15 projetos open source do GitHub que valem o seu tempo, em contagem regressiva e com 10 segundos para cada um: um conversor de 255 formatos que funciona arrastando, uma TV sem anúncios, o Figma offline, janelas do Mac no iPad e muito mais. 📺 Décimo terceiro volume da série Open source do GitHub. Escolhidos pela análise da lista inteira (estrelas, frequência de commits, último commit, README, documentação, capturas e site), conferida em 23/10/2026. Qual desses você vai testar primeiro? Conta nos comentários! ⏱️ CAPÍTULOS E LINKS 0:00 Abertura 0:10 #15 HQTUI: painéis de terminal no estilo btop em 10 linguagens, sem dependências profullstack/hqtui 0:20 #14 Amagine3D: descreva o aparelho e as medidas e ganhe a caixa em 3D editável, em STEP, STL ou 3MF (6,3 mil estrelas) amagine-ai/Amagine3D 0:30 #13 slides-grab: o agente cria slides em HTML e você seleciona uma área para pedir o ajuste; exporta em PDF (1,2 mil estrelas) NomaDamas/slides-grab 0:40 #12 Snitch: monitor de rede em tempo real com firewall de saída: veja e bloqueie cada conexão aixisstudio/Snitch 0:50 #11 Glide: gravador de tela open source para macOS no estilo Screen Studio, com zoom automático nos cliques michaelshimeles/glide 1:00 #10 House Control: a sua casa em 3D na barra do Mac e no iPhone, controlando luzes e ar-condicionado 0xProbabillity/house-control 1:10 #9 Talorys: agente pessoal de IA que roda na sua conta da Cloudflare, com memória, tarefas e lembretes (1,4 mil estrelas) rociiu/talorys 1:20 #8 Indra OCR: modelo de OCR minúsculo que roda na CPU, em mais de 80 idiomas e até letra de mão datalab-to/indra 1:30 #7 net-merge: usa Wi-Fi, cabo e celular ao mesmo tempo, somando a velocidade das conexões (1,8 mil estrelas) rohit267/net-merge 1:40 #6 opendesk: central de atendimento open source com e-mail, chat do site e base de ajuda numa caixa só useopendesk/opendesk 1:50 #5 editonny: skill para Claude Code e Codex que edita vídeo por conversa: corta pausas, legenda e arruma o áudio soumatheusgomes/editonny 2:00 #4 Desigma: alternativa gratuita e offline ao Figma, feita em Rust, que importa arquivos do Figma deepfounder-ai/desigma 2:10 #3 Sill: qualquer janela do Mac no iPhone ou iPad, com toque, teclado e Apple Pencil, sem conta nem servidor (3,9 mil estrelas) Saffsanity/sill 2:20 #2 cleanyourtv: tira anúncios e apps de fábrica da TV pelo Wi-Fi, de forma reversível (24,8 mil estrelas) Gathin23/cleanyourtv 2:30 Oferecimento Hallen Tech 2:44 #1 Filee: conversor de arquivos offline: segure uma tecla, arraste e converta entre 255 formatos (10,3 mil estrelas) KnifeLemon/Filee 2:54 Encerramento 🧡 Oferecimento: Hallen Tech, liderança de tecnologia sob demanda, software, cloud e segurança para a sua empresa. Site: hallentech.com E-mail: contato@hallentech.com Instagram: instagram.com LinkedIn da Hallen Tech: linkedin.com LinkedIn do Eddwan: linkedin.com Se curtiu, deixa o like, segue o canal e ativa as notificações para a próxima lista. #opensource #github #programacao #ferramentas

CozyClay: Make the scene first. Then make it a video. (896 stars) What it does All text below is quoted directly from the project README. >Open source previs in a browser tab: block the set, move the cast, cut the camera, hand the shot to an AI video model. What you can do: - Stage: Build the set from primitives. Add rigged characters, or capsule stand-ins when nobody needs to move a limb. Fly the view like a 3D editor. - Move: Describe the action. The agent writes a motion spec, and a deterministic compiler in the browser bakes every frame. QA checks collisions, foot slide, reach and hand contact before you see it. - Shoot: Put shots on a timeline, draw dolly rails, look through the lens. Each shot knows the limits of the video model you target. - Export: Keyframe pack (first and last frame, greybox clip, camera, prompt), mp4, depth and normal passes, contact sheet, OTIO cut list. - Storyboard: Prefer stills? A Storyboard project is a row of panels with captions, an animatic and a contact sheet. - Undo anything: Every edit, including each change the agent makes, is one undo step. >That is the whole install. You need Node.js 22.19 or newer and a Chromium browser. You do not need a GPU, Python or a model download. Repository NomaDamas/CozyClay Repository stats |Metric|Value| |:-|:-| |Stars|896| |Forks|101| |Last release|v3.0.3 (2026-10-19)| |Languages|JavaScript 92.8%, CSS 5.5%, HTML 1.4%| |Contributors|13| |AI contributor accounts (Claude / Codex / Cursor / Copilot)|claude: 48, cursoragent: 6, Copilot: 1| |AI co-authored commits|Claude: 49, Cursor: 6| Main contributor |Field|Value| |:-|:-| |Name|Yun| |GitHub|@HaD0Yun| |Commits to this repo|1,732 (top contributor)| |Bio|I love something people want| |Company / Location|seoul| |X / Twitter|@Yun_HDY| |Followers|203| ────────────────────────────── 📌 How many great GitHub repos have you discovered and completely forgotten about? Don't let another useful tool disappear into your Reddit feed. Get the community's best repos, organized by category, plus key takeaways from real developer discussions, delivered to your inbox twice a week. 📬 Never lose track of great repos again. Subscribe free.

I kept paying $17 a run for Seedance 2.5 because the camera was wrong, so I built a three.js previs tool. 3.0 is out and I did not pose a single keyframe for this scene Last time I posted here I was burning $17 every time Seedance 2.5 picked a different camera than the one in my head. So I built CozyClay, a browser graybox in three.js: block the scene, cut the camera, send the same shot to the model. That fixed the camera. Then I hit the next wall. For this truck scene I needed a driver smoking at a red light, a girl crossing on her phone, the hit, 11 shots. Posing a rig for 30 seconds of that took me a whole night and it still looked like a mannequin falling over. So for 3.0 I stopped posing. I type what happens. "lights a cigarette", "flicks the ash out the window", "she steps into the crosswalk looking at her phone". The agent writes a motion spec, the compiler bakes it in the browser. No keyframes, no GPU box, it is all three.js + r3f. Top is what I got in the tab, bottom is Seedance 2.5 reading that clip as reference. Same cuts, same camera. I paid for one run. Open source. NomaDamas/CozyClay npx cozyclay

blocked the whole truck scene in a browser tab, typed what the driver does, cut the camera, handed the exact same shots to seedance 2.5 top is clay, bottom is what came back. zero keyframes NomaDamas/CozyClay

blocked the whole truck scene in a browser tab, typed what the driver does, cut the camera, handed the exact same shots to seedance 2.5 top is clay, bottom is what came back. zero keyframes NomaDamas/CozyClay