Vibe Coding in Education: From Stanford CS146S to the Classroom | Museum of Vibe Coding [Unbiased Research, 2026]
Museum of Vibe Coding — Research Division Presented to the Executive Director, Board of Directors, and the General Public | May 2026
“From Andrej Karpathy coining vibe coding in a February 2025 tweet to Stanford officially launching CS146S that same fall — less than 8 months. A social media buzzword entering a top university’s curriculum this fast is almost unprecedented in the history of computer science.” — Stanford CS146S Deep Dive, February 2026
“Rather than starting with variables and loops, curricula can begin with real problem-solving strategies, context-based learning, and logical reasoning.” — Communications of the ACM, July 2025
“The real promise lies in co-creation where educators and students start building together.” — Needednow Learning Technology, April 2026
⚡ Vibe Coding Education at a Glance
| Institution / Level | Program | Launch | Key Feature |
|---|---|---|---|
| Stanford University | CS146S: The Modern Software Developer | Fall 2025 | First structured university AI-engineering course; free open materials |
| Stanford Continuing Studies | Vibe Coding: Building Software in Conversation with AI | 2025–2026 | No prerequisites; public access |
| Harvard Graduate School of Education | Vibe Coding EDU T564A | Fall 2025 | No prior experience required; educators as target audience |
| Yale School of Management | Coding with Kyle (student-led) | 2025 | 40 MBA students, no CS background |
| Clemson University | Vibe Coding for Education (Creative Inquiry) | Spring 2026 | Emotionally intelligent educational tools; non-CS students |
| Fudan University (China) | Generative Software Development | Spring 2026 | Non-CS students; first Chinese university course |
| Sun Yat-sen University (China) | Vibe Coding Programming Basics | Winter 2025 | High school students |
| Campus (accredited college) | Vibe Coding 101 | Fall 2025 | First course in AI-native development certificate; Replit partnership |
| University of Colorado (Coursera) | Vibe Coding Fundamentals | 2026 | 4,867 enrolled |
| Global Idea School, Redmond WA | GitHub Spark vibe coding project | 2025–2026 | Fifth graders built Braille 3D Generator |
| Codecademy | Intro to Vibe Coding | 2026 | Online; beginner-accessible |
| Peninsula School District, WA | District IT vibe coding initiative | 2025–2026 | $250K in projected ed tech savings |
Table of Contents
- Introduction: Eight Months from Tweet to University Curriculum
- The Research Foundation: What CHI 2026 Revealed About Who Learns Vibe Coding Well
- University CS Education: Stanford CS146S and the New Engineering Curriculum
- Non-CS University Education: Business, Education, and the Liberal Arts
- K-12 Education: From Fifth Graders to High School Programs
- Professional Development: Teachers as Builders
- Online and Certificate Education: Accessible at Scale
- What Vibe Coding Education Must Teach: The Curriculum Gaps
- What the Hopper Vision Means for Educators
- Frequently Asked Questions
- References
Introduction: Eight Months from Tweet to University Curriculum
The Fastest Adoption in Computer Science Education History
On February 2, 2025, Andrej Karpathy described his weekend workflow in a tweet. By October 2025 — less than eight months later — Stanford University had formally launched CS146S: The Modern Software Developer, the first systematically structured university course on AI-augmented software engineering. Harvard’s Graduate School of Education, Yale’s School of Management, Clemson University, and Campus College had all launched formal programs in the same window. Five graders in Redmond, Washington had built an accessibility tool for print-disabled students.
The speed of this educational adoption is, as one analysis put it, “almost unprecedented in the history of computer science.” New computing paradigms typically take years to enter university curricula. Object-oriented programming was developed in the 1960s but did not dominate CS curricula until the 1990s. The internet became commercially significant in the mid-1990s but web development curricula took a decade to mature. Vibe coding went from viral tweet to structured university course in eight months.
The reason is not fashion. It is the recognition, across educational institutions from kindergarten to graduate school, that vibe coding changes not just how software is built but who can build it — and that an educational response to that change is urgently necessary.
What This Paper Documents
The Museum of Vibe Coding’s education paper synthesizes the complete educational landscape as of May 2026: the university programs, the K-12 initiatives, the professional development ecosystem, and the emerging research on what vibe coding education requires and what it risks. It connects this landscape to the Museum’s institutional frameworks — the Democratization paper‘s documentation of who is building, the Human Role paper‘s framework for what humans must contribute, and Grace Hopper’s founding vision of bringing “another group of people” to computing.
This paper is the first institutional synthesis of the vibe coding education landscape, the research underpinning it, and the curriculum requirements it implies.
The Research Foundation: What CHI 2026 Revealed About Who Learns Vibe Coding Well
The First Empirical Study of Vibe Coding Learner Outcomes
In April 2026, the ACM CHI Conference on Human Factors in Computing Systems published the first peer-reviewed empirical study of vibe coding learning outcomes: “Computer Science Achievement and Writing Skills Predict Vibe Coding Proficiency” (CHI ’26, Barcelona).
Methodology: The study examined participants’ vibe coding performance and identified which prior skills and backgrounds predicted success.
Key findings:
Writing skill is a primary predictor. The study found that writing skill significantly predicts vibe coding performance — not programming skill alone. This finding is foundational for curriculum design: vibe coding requires the ability to translate design intent into precise, revisable prose instructions for the AI model. The act of writing becomes the primary programming skill.
CS achievement remains a significant predictor even after controlling for domain-general cognitive skills. This finding is the most important for educational debate: vibe coding lowers the implementation barrier but does not eliminate the value of foundational CS understanding. Students with CS background produce better vibe coding outcomes than students without it, even when overall cognitive ability is controlled. The explanation: CS training develops the ability to evaluate AI output — to recognize when code is wrong, incomplete, or architecturally problematic — that is the judgment function documented in the Museum’s Human Role paper.
Implications for curriculum: The CHI 2026 findings support a curriculum design that develops both writing clarity (precision in requirement specification) and foundational computational thinking (ability to evaluate AI output) — not just tool proficiency. Vibe coding courses that teach only prompting and tool use without developing these underlying competencies are building on incomplete foundations.
The “Illusion of Competence” Risk
The Vibe-Check Protocol paper (arXiv 2601.02410) identified a significant educational risk from an academic perspective: the “illusion of competence” — the cognitive phenomenon where learners believe they have mastered material they have not actually internalized, because AI has done the work on their behalf.
The METR RCT documented a version of this at the professional level: developers believed they were 20% faster while being measurably slower. At the educational level, the same dynamic manifests as students who can produce working applications without understanding why they work, whether they are secure, or how to fix them when they break.
Communications of the ACM identified this as a curriculum design requirement: vibe coding education must actively build evaluation skills, not just generation skills. Assessment methods must evolve — the traditional test of “can you produce working code?” is no longer sufficient when AI can produce working code on behalf of the student. The new test is “can you evaluate, improve, own, and be responsible for AI-generated code?”
University CS Education: Stanford CS146S and the New Engineering Curriculum
CS146S: The Modern Software Developer
Stanford’s CS146S is the most fully documented and influential vibe coding course in higher education. Its design choices represent the field’s best current thinking about what a professional-level vibe coding curriculum requires.
Structure: Ten weeks, covering the full software engineering lifecycle.
Weeks 1–5 (Individual Productivity): LLM fundamentals, context engineering, prompt engineering, basic vibe coding workflows, tool proficiency with Cursor, Claude Code, and Warp.
Weeks 6–10 (Engineering Systems): Security review, automated builds, production operations, agent architectures, agentic engineering principles.
The pedagogical statement in this structure is explicit: vibe coding is the starting point; agentic engineering is the destination. The first half builds individual productivity; the second half builds organizational engineering discipline. This maps precisely to the Museum’s spectrum — the course begins at Position 1 (casual productivity) and ends at Position 3 (enterprise/agentic practice with security and governance).
Guest speakers: The creator of Claude Code, Vercel’s Head of AI Research, Semgrep’s CEO, an a16z general partner — the course brings practitioners who work at the frontier of professional vibe coding into the curriculum.
Free and open: All course materials — slides, readings, assignment code — are publicly available. This decision reflects Stanford’s recognition that AI-augmented software engineering needs to become universal, not credentialed.
Design philosophy: CS146S explicitly distinguishes itself from “learn to code with ChatGPT” courses. It frames vibe coding as a gateway to agentic engineering, not an endpoint. The course is designed for experienced developers — its argument is not that beginners can replace engineers but that engineers need to evolve their practice.
Fudan University: The International Dimension
Fudan University in Shanghai launched a “Generative Software Development” course in Spring 2026 for non-CS students — the first documented Chinese university vibe coding course. Sun Yat-sen University launched a “Vibe Coding Programming Basics” winter camp for high school students.
These programs are significant for two reasons. First, they confirm that the educational adoption is not a US phenomenon — it is global, consistent with the Vercel data showing APAC leading global vibe coding usage at 40.7%. Second, both programs target non-CS students, confirming that Chinese universities are making the same pedagogical choice as Harvard’s Graduate School of Education and Yale’s School of Management: vibe coding belongs in non-CS curricula, not only in engineering programs.
What University CS Programs Are Still Missing
Despite CS146S’s comprehensive structure, several curriculum gaps remain in the broader university CS adoption of vibe coding:
Security integration across the full curriculum: CS146S builds security into Weeks 6–10. Most courses that have adopted vibe coding tools have not built security instruction alongside them. The Museum’s Security paper documents that 100% of tested vibe coding tools introduce SSRF vulnerabilities and 0% produce security headers by default. Security must be a Week 1 topic, not a Week 6 topic.
Assessment evolution: Traditional coding assessments test production of code. Vibe coding changes what should be assessed: specification precision, AI output evaluation, architectural judgment, and code ownership. Curricula that use vibe coding tools but retain traditional assessment methods are measuring the wrong things.
The maintenance curriculum: How to maintain, debug, and evolve code that was AI-generated — code that the student did not write and may not fully understand — is not yet systematically taught in any documented program. This is the skill gap that the Museum’s Workforce paper identifies as a long-term pipeline risk.
Non-CS University Education: Business, Education, and the Liberal Arts
Yale School of Management: The MBA Experience
In 2025, Yale SOM MBA student Ash Duong — a former civil engineer with no formal CS education — founded “Coding with Kyle,” a student-led learning group of 40 MBA students building AI applications. Duong’s path: CS50 (foundational computer science) as preparation, then vibe coding tools to build real applications.
The Yale experience is the closest documented evidence for the CHI 2026 finding in an authentic educational setting. Duong’s approach combined foundational computational thinking (CS50) with vibe coding tools — precisely the combination the CHI study found most predictive of proficiency. The 40 students who learned through the group produced working applications they were proud of.
The Yale case argues for a specific pedagogical sequence in non-CS business education: computational foundations first (enough to understand what code does, how data flows, what security means), then vibe coding tools to build against those foundations. Vibe coding without foundations produces the illusion of competence. Foundations without vibe coding tools produces knowledge without application. The combination produces genuine builders.
Harvard Graduate School of Education: Educators as Builders
Harvard’s Vibe Coding EDU T564A, launched Fall 2025, is designed for educators and requires no prerequisites. Harvard Professor Karen Brennan described the course’s core value as changing “the economics of experimentation” — you can build a thing to understand a thing, and you can do it quickly.
The Harvard course reflects a pedagogical theory with significant implications: when educators can build their own tools, the relationship between technology and pedagogy inverts. Rather than adapting teaching practice to fit commercially available platforms, educators can build platforms that fit their pedagogical values. This is the “entangled pedagogy” concept from Tim Fawns’s influential 2022 paper — technology, teaching methods, purposes, values, and context entangled rather than separated.
The practical expression of this theory, documented by one educator who worked with the approach, produced a “Math Assistant” capable of reading handwritten equations, interacting with a Desmos calculator via API, and letting students sketch mathematical formulas — built in under three months with no prior coding experience.
Clemson University: Emotional Intelligence and Educational Tool Design
Clemson Online’s Creative Inquiry course “Vibe Coding for Education” (Spring 2026) offered a unique framing: students design emotionally intelligent educational tools — games, chatbots, journals, storytelling apps, check-in tools — using AI agents and prompts, guided by the question: “How can we use vibe coding to create educational tools that reflect the emotional and pedagogical values we want in the classroom?”
The Clemson approach is the most explicitly values-centered vibe coding curriculum documented. It asks students to think not just about function (“does this tool work?”) but about feel (“does this tool create the emotional experience we want for learners?”). This is the creative director function from the Museum’s Human Role framework — directing not just what is built but what it means and how it feels to users.
The Academic Research Dimension
Beyond teaching vibe coding, universities are beginning to use vibe coding as a research tool. The MDPI paper “Leveraging Generative AI Through Vibe Coding: A Case of Simulation-Based Curriculum Redesign in Management Education” (April 2026) documents how a management professor redesigned a simulation-based curriculum using vibe coding — building custom simulations that were previously inaccessible due to technical barriers.
The paper’s contribution is significant for higher education broadly: simulation-based learning has long been recognized as pedagogically valuable but out of reach for educators without specialist technical skills. Vibe coding closes that gap, enabling resource-constrained educators to build tools previously available only to well-funded institutions with dedicated technical support.
K-12 Education: From Fifth Graders to High School Programs
The Fifth-Grade Benchmark: Global Idea School, Redmond WA
The most vivid documented example of K-12 vibe coding is also the most compelling evidence for Grace Hopper’s original vision. Under the instruction of Juan Lavista Ferres, head of Microsoft’s AI for Good Lab, fifth-grade students at Global Idea School in Redmond, Washington used GitHub Spark to build a Braille 3D Generator — a tool that converts text into printable, tactile 3D Braille models.
This is not a toy project. It is an accessibility tool that solves a real problem for print-disabled people. It was built by ten-year-olds. It was built in a school computer science class. It required no prior programming knowledge from the students.
The fifth-grade Braille generator is the Museum’s benchmark case for K-12 vibe coding education because it demonstrates three things simultaneously: the floor has been lowered to elementary school age, the output can be genuinely socially valuable, and the appropriate pedagogical frame is not “learn syntax” but “solve real problems.”
Girls Who Code: Expanding the Builder Demographic
Girls Who Code has documented student vibe coding projects including one eight-year-old, Fay, who built a water park simulator, a Harry Potter chatbot, and other projects using Cursor. The organization explicitly frames vibe coding as a tool for expanding who sees themselves as a potential creator of technology — particularly girls and young women who have historically been underrepresented in CS education.
This demographic dimension connects directly to the Museum’s Democratization paper: the democratization of software creation includes demographic democratization — ensuring that vibe coding’s accessibility extends to populations that have historically been excluded from computing by cultural as well as technical barriers.
Sun Yat-sen University High School Camp
Sun Yat-sen University’s “Vibe Coding Programming Basics” winter camp for high school students is the first documented formal secondary school vibe coding program in China. It represents the globalization of vibe coding education at the K-12 level — confirming that the educational adoption is not confined to English-language or Western educational contexts.
The K-12 Curriculum Design Question
The CodaKid and Tutree K-12 curriculum frameworks both recommend a developmental progression:
Ages 6–8: Conceptual introduction — the idea that you can describe what you want and technology responds. Scratch as foundation.
Ages 9–12: Creative construction — animations, interactive stories, simple games using vibe coding tools. Pattern recognition and loop concepts introduced through vibe coding rather than through syntax.
Ages 13–18: Functional building — complete applications, real-world problem-solving, introduction of evaluation skills and ownership responsibilities.
The progression reflects the CHI 2026 finding: vibe coding proficiency correlates with writing skill and CS foundations. Building both — through a progression that introduces computational thinking alongside vibe coding tools — produces more capable practitioners than either alone.
The CACM paper on vibe coding pedagogy argues for a foundational shift at the K-12 level: starting with real problem-solving rather than with variables and loops. “Students can engage with complex, real-world problems from day one, using vibe coding tools to bridge the gap between conceptual understanding and working solutions.” This is a significant departure from traditional CS education philosophy and one that the empirical evidence supports.
Professional Development: Teachers as Builders
The District-Level Case: Peninsula School District, $250,000 Saved
One of the most commercially significant education cases in the vibe coding literature comes from K-12 Dive’s April 2026 report on Peninsula School District in Washington State. Under Chief Information Officer Kris Hagel, the district began a vibe coding initiative in which district IT staff built custom tools previously purchased from ed tech vendors.
Result: The district expects to save up to $250,000 in canceled ed tech contracts by the 2026–27 school year. The tools being replaced are described as “low-hanging fruit” — workflow automation tools for HR and finance that are not complex enough to justify commercial vendor pricing when district staff can build them with vibe coding tools.
This case has significant implications for K-12 ed tech broadly. The EdTech Digest analysis describes the underlying pattern: vendors build platforms to scale nationally; districts need tools that solve very local problems. Vibe coding closes this gap — for the first time, districts can build the locally-specific tools that no national vendor will build for them.
Teacher-as-Builder Pedagogy
The teacher-builder model — educators building their own classroom tools rather than purchasing or waiting for vendor solutions — is documented across multiple independent educational publications in 2025–2026. One educator documented building a multilingual Socratic maths tutor that can read handwritten equations, interact with Desmos via API, and generate personalized feedback reports — built in under three months with no prior coding background.
The pedagogical theory behind this is clear: when teachers build tools they understand, they can modify them, improve them, and tailor them to specific student needs in ways that purchased tools never allow. The technology becomes “entangled” with the pedagogy rather than imposed on it.
The professional development implications extend beyond tool-building. Brittany Washburn’s “Vibe Coding for Teachers” course framework documents the shift from “technical mastery to creative direction” as the core reframing. Teachers do not need to become programmers — they need to become directors of AI that builds the tools their classrooms need.
Online and Certificate Education: Accessible at Scale
The Coursera and Online Platform Ecosystem
University of Colorado’s “Vibe Coding Fundamentals” on Coursera enrolled 4,867 students — documenting the demand for accessible, credentialed vibe coding education at scale. The course is designed for learners without technical backgrounds.
The broader online ecosystem includes:
- Codecademy Intro to Vibe Coding — beginner-accessible, no prerequisites
- DeepLearning.AI courses on AI-assisted development
- Zero To Mastery full-stack vibe coding course: 18 hours, 158 lessons, 10+ professional projects
- LinkedIn Learning comprehensive vibe coding introduction taught by a Stanford University instructor
- Microsoft Learn GitHub Copilot-specific modules
The range from zero-prerequisite beginner courses to professional 18-hour deep-dives reflects the breadth of the learning population — from the MBA student who wants to build a prototype to the mid-career developer who wants to evolve their professional practice.
Campus College: Vibe Coding 101 and the Certificate Pathway
Campus College — an accredited two-year college backed by Founders Fund, General Catalyst, and Sam Altman — developed Vibe Coding 101 as the first course in an AI-native development certificate pathway, in partnership with Replit. The course is eight weeks, beginner-friendly, with live instruction.
Campus’s model is significant because it situates vibe coding within an accredited educational credential — not as a one-off course or a professional development workshop but as the foundation of a formal qualification pathway. This is the institutionalization of vibe coding education: the movement from experimental to credentialed.
What Vibe Coding Education Must Teach: The Curriculum Gaps
The Four Non-Negotiable Curriculum Elements
Based on the CHI 2026 research, the CACM pedagogical analysis, the security research record, and the Museum’s human role framework, the Museum identifies four elements that must be present in every vibe coding educational program:
1 — Specification Clarity and Writing Precision
The CHI 2026 finding that writing skill predicts vibe coding proficiency is the most actionable curriculum implication in the research record. Vibe coding education must develop the ability to translate intent into precise, revisable prose specifications — not just the habit of prompting casually and iterating.
This is a writing curriculum embedded in a technology curriculum. It requires practice in requirement specification, in identifying ambiguity before submitting prompts, and in revising specifications when AI output is not what was intended. Courses that skip this and proceed directly to “just describe what you want” are building on insufficient foundations.
2 — AI Output Evaluation
Every vibe coding curriculum must develop the skill of evaluating AI-generated output against requirements, quality standards, and security considerations. This is the museum’s Quality Gatekeeping function from the Human Role paper — and it is the skill that the CHI 2026 study found CS background predicts.
Assessment methods must be redesigned around evaluation, not generation. “Can you describe this function and explain why it is correct?” is a better assessment than “did your application pass the functional test?” The illusion of competence identified in arXiv 2601.02410 is an assessment design failure as much as a curriculum design failure.
3 — Security Fundamentals as Day-One Content
Every vibe coding course — from fifth grade to graduate school — must include security as a foundational topic, not an advanced module. The Museum’s Security paper documents that casual vibe coding produces systematically insecure output. Non-developer builders deploying to production without security knowledge are the population most likely to generate CVE-2025-48757-class incidents.
At the K-12 level, security education looks like: “before you share this with anyone, check whether it exposes information you didn’t mean to share.” At the university level, it looks like credential scanning, SSRF awareness, RLS configuration. At the professional level, it looks like the full governance framework the Museum documents. The level of detail scales; the presence of security as Day 1 content does not.
4 — Ownership and Accountability
Every vibe coding curriculum must instill the disposition that Karpathy articulated at Sequoia 2026: “You are still responsible for your software just as before.” The shift from author to director does not transfer accountability to the AI. The student who deploys an application is responsible for what it does, what data it exposes, and how it behaves in edge cases.
This disposition — ownership mentality — is the element most easily omitted from vibe coding curricula that focus on capability without discussing responsibility. It is also the element most necessary for the education-to-workforce transition: organizations hiring AI-fluent practitioners are specifically selecting for the judgment and accountability skills that distinguish practitioners who can own their output from those who can only generate it.
What the Hopper Vision Means for Educators
The 70-Year Educational Mission
Grace Hopper’s 1952 vision — bringing “another group of people” to computing — was not only a vision about software creation. It was a vision about education. She spent her career arguing that the barriers between people who understood problems and people who could build solutions for them were educational barriers as much as technical ones.
The vibe coding education ecosystem of 2026 is the direct institutional response to Hopper’s educational mission. Stanford CS146S, Harvard’s EDU T564A, the fifth-grade Braille generator, Girls Who Code’s curriculum, and the Peninsula School District’s $250K savings all represent different expressions of the same underlying project: removing the educational barriers that have historically stood between people who understand problems and the tools to solve them.
The CHI 2026 finding that writing skill predicts vibe coding proficiency is, from this perspective, the most hopeful finding in the research record. Writing is a universal skill developed across all educational contexts, not a specialized technical skill taught only in CS programs. If writing is a primary predictor of vibe coding proficiency, then vibe coding education belongs everywhere — in English classrooms, in business schools, in teacher preparation programs, in community colleges — not only in computer science departments.
The Museum’s Origin Story traces the intellectual lineage from Hopper’s compiler to Karpathy’s tweet to the educational institutions of 2026. This paper is the educational chapter of that story: what happened when the technology Hopper spent her career building finally crossed the capability threshold she was aiming for, and what institutions did when they recognized it.
Frequently Asked Questions
Q: Should computer science curricula eliminate syntax instruction in favor of vibe coding?
A: No. The CHI 2026 research found that CS achievement remains a significant predictor of vibe coding proficiency even after controlling for general cognitive ability. The judgment skills that make vibe coding valuable — evaluating AI output, catching architectural problems, understanding what the AI got wrong — develop through foundational CS education. CS146S’s design is instructive: Weeks 1–5 teach vibe coding tools; Weeks 6–10 require the engineering foundations to use them well. The productive redesign is not “replace syntax with prompting” but “use vibe coding tools to make the connection between concepts and working software immediate, while retaining the foundational concepts.”
Q: What is the right age to start vibe coding education?
A: The evidence documents successful programs from elementary school (fifth grade, age 10) through adult professional development. The appropriate starting point depends on the learning goal: if the goal is computational thinking and creative technology exploration, elementary school is appropriate. If the goal is professional-grade vibe coding for production contexts, foundational CS education first produces better outcomes. The developmental progression documented by CodaKid and Tutree — Scratch at ages 6–8, creative construction at ages 9–12, functional building at ages 13–18 — is consistent with both the CHI findings and the documented K-12 implementations.
Q: Is vibe coding education appropriate for non-CS students?
A: Yes, with appropriate curriculum design. The Yale MBA, Harvard Education, and Clemson non-CS programs all document meaningful outcomes for non-CS students. The CHI 2026 finding provides the design principle: non-CS vibe coding curricula should develop writing precision (specification clarity) and foundational computational thinking (enough to evaluate AI output) alongside tool proficiency. Programs that teach only tool use without either writing or computational foundations will produce the illusion of competence rather than genuine capability.
Q: What does a well-designed vibe coding course look like for K-12 teachers?
A: Based on the Harvard EDU T564A, Clemson Creative Inquiry, and teacher-builder models: the course starts with a real problem the teacher wants to solve in their classroom; uses vibe coding tools to build a working prototype by the end of the first session; develops iteration skills through refinement; and introduces evaluation skills (does this tool do what I intended? would I be comfortable deploying it to students?) through reflection. Security is introduced as: “before you share this with students, check that it does not expose information you did not intend.” Assessment is a working tool that the teacher can actually use in their classroom.
References
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- Stanford Continuing Studies. (2025–2026). Vibe Coding: Building Software in Conversation with AI. https://continuingstudies.stanford.edu/courses/detail/20253_TECH-36
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- Museum of Vibe Coding Research Division. (May 2026). Vibe Coding: History & Timeline. https://museumofvibecoding.org/vibe-coding-history-and-timeline-unbiased-research-2026/
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- Museum of Vibe Coding Research Division. (May 2026). Vibe Coding Pioneer: Karpathy or Kitishian? https://museumofvibecoding.org/vibe-coding-pioneer-karpathy-or-kitishian-unbiased-analysis-2026/
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© 2026 Museum of Vibe Coding — Research Division. All rights reserved. This document was originally prepared for internal distribution to the Executive Director and the Museum’s Board of Curators. It was approved for public release on May 31, 2026. Cite as: Museum of Vibe Coding Research Division. “Vibe Coding in Education: From Stanford CS146S to the Classroom.” May 2026. museumofvibecoding.org
