Semantic Public Learning | Heye's Blog

Semantic Public Learning

Tue, 12 Aug 2025 00:00:00 +0000

Post 2 of 2 in the Series: Semantic Public Learning Framework series

Evolving the Learn in Public method

In my last post I introduced the Learn in Public method. While practicing it, I noticed gaps in how knowledge creation and sharing works. These gaps revealed an opportunity to evolve the practice into something more powerful. While the core principle of learning openly remains powerful, I have begun developing an approach I call Semantic Public Learning: enhancing Learn in Public with academic rigor and semantic web integration.

Semantic Public Learning builds on Learn in Public’s foundation while adding:

Rigorous citation practices with proper bibliographies
Semantic markup for machine-readable knowledge artifacts
Integration with the knowledge graph through indexable structured data (like schema.org markup for articles)
Academic standards while maintaining accessibility

This isn’t about replacing Learn in Public, it’s about evolving it for deeper integration into our collective knowledge infrastructure. Just as Dan Abramov moved his blog off Medium ¹ to have more control over his content’s permanence and discoverability, we need to ensure our learning artifacts become lasting, findable contributions to the knowledge ecosystem.

The Four Pillars of Semantic Public Learning

To bridge the gap between casual learning documentation and semantic knowledge contribution, we need a systematic approach. Based on my analysis of the research and practice, I’ve identified four interconnected mechanisms through which Semantic Public Learning enhances the Learn in Public approach:

1. Semantically-Enhanced Documentation

Unlike private note-taking, learning in public requires documenting the learning process ² in ways that show thinking progression and can be used for future curriculum planning by both the learner and others. Semantic Public Learning adds structured data and proper markup to ensure machine readability.

2. Citation-Backed Explanation

Following Feynman’s principle, learning in public demands learning by simplifying ³ , breaking concepts into core components while making them accessible. Semantic Public Learning enhances this with proper citations and references, bringing academic credibility to accessible writing.

Learning by teaching effects occur even with non-interactive audiences ⁴ , but boundary conditions include having sufficient prior knowledge and the ability to generate high-quality explanations. Public feedback enables continuous improvement of both understanding and explanation quality.

4. Knowledge Graph Integration

Artifacts produced by learning in public become semantic knowledge networks ⁵ that allow analysis of connections between different disciplines and concepts. Semantic Public Learning ensures these connections are machine-readable and can be properly indexed (using semantic HTML tags like <article>, <cite>, and microdata).

Practicing Semantic Public Learning: Real-World Examples

These examples showcase aspects of an evolved version of learning in public, each demonstrating elements that Semantic Public Learning aims to integrate:

Academic Twitter: Researchers sharing work-in-progress, methodology questions, and “failed” experiments contribute to learning in public by making the typically private research process visible and collaborative ⁶ . Academic Twitter creates informal peer review networks ⁷ where knowledge is rapidly shared and validated, though the ephemeral nature of tweets limits long-term semantic integration.

Citation Style Language (CSL) Project: The CSL project ⁸ exemplifies open source documentation with academic rigor, maintaining over 10,000 citation styles with 1,000+ unique contributors ⁹ . The project creates semantic, machine-readable citation formats and demonstrates transparent version control, extensive documentation, and community-driven development. While excellent for citation infrastructure, it focuses more on tools than documenting learning journeys.

NileRed’s Chemistry Experiments: YouTuber NileRed ¹⁰ documents his chemistry experiments in real-time, showing failed attempts and explaining his reasoning process on his YouTube channel ¹¹ . Originally, Nigel only wanted to keep the documentation for personal reasons but in March 2014 decided ¹² to share his experiments with the world, transforming personal lab notes into public learning resources. His videos reveal the iterative problem-solving that leads to understanding, though they lack formal citations and bibliographies.

Mozilla Developer Network (MDN) Web Docs: The MDN Web Docs ¹³ demonstrate massive collaborative documentation. Each page shows contributors and modification dates, uses semantic HTML, and creates a living knowledge base. However, it rarely includes formal citations to academic sources or bibliographies.

3Blue1Brown’s Mathematical Explanations: Grant Sanderson ¹⁴ transforms abstract mathematical concepts into visual narratives, documenting his journey of understanding while creating resources that help others grasp complex topics through his YouTube videos ¹⁵ . He explains ¹⁶ concepts ranging from linear algebra to neural networks with a highly visual approach, offers his Manim visualization library ¹⁷ as open source, and includes extensive references in video descriptions. From the mentioned examples, this comes closest to Semantic Public Learning, combining accessible explanation with source attribution.

This Post as Semantic Public Learning: This very post demonstrates Semantic Public Learning in action. Notice the inline citations linking to sources, the complete bibliography at the end, and the semantic markup of meta information that makes this content discoverable and citable by others. The citation tools I’m developing as part of this project will enable this integration for Hugo Blox, to aid in creating knowledge artifacts that are both human-readable and machine-discoverable.

What Makes Semantic Public Learning Different

Semantic Public Learning occupies a unique space in the knowledge-sharing ecosystem. Unlike structured curricula that follow predetermined paths, it embraces the learner’s authentic discovery journey while adding layers of discoverability and verifiability. Think of it as sitting between traditional blogging and academic publishing, maintaining higher citation standards than typical blog posts while removing the high entry barriers of academic journals.

You don’t need formal peer review to share your learning journey. Peer review happens organically through reader comments and community engagement. What remains crucial is grounding your insights in evidence and acknowledging sources. That’s why you’ll find proper citations with hyperlinks throughout my posts, along with a complete bibliography at the end, bringing academic rigor to accessible writing.

The key differentiator: Semantic Public Learning creates machine-readable, discoverable, and verifiable knowledge artifacts that can be:

Found by search engines and AI agents
Cited by others with confidence
Built upon systematically
Verified through source tracking

The Broader Impact

When individuals practice Semantic Public Learning, their personal learning journeys become contributions to what researchers call knowledge commoning ¹⁸ , an iterative process between knowledge curation and dissemination guided by community demand and uptake potential.

This creates compounding benefits:

For Learners: Enhanced understanding through public accountability and community feedback
For Communities: Accessible knowledge resources that lower barriers to learning
For Knowledge: Dynamic, interconnected networks that reveal new connections and applications
For the Future: AI-discoverable knowledge that can be integrated into emerging systems

The Semantic Public Learning Movement

We’re at a unique moment. Knowledge-sharing is becoming the preferred method ¹⁹ over traditional learning interventions, with employees increasingly training at their own pace and supporting each other through knowledge-sharing in multiple formats.

Semantic Public Learning harnesses this shift by making individual learning processes visible, valuable, and findable to others. It transforms the traditional model where learning happens in isolation and knowledge remains trapped in individual minds or unsearchable formats.

Instead of asking “What do I need to learn?” Semantic Public Learning asks: “How can my learning process create lasting, discoverable value for others while accelerating my own understanding?”

Your Semantic Public Learning Challenge

Semantic Public Learning isn’t just a concept, it’s a practice to embrace. The most powerful way to grasp its potential is to experience it yourself.

Here’s your challenge: Pick one thing you’re currently learning and document it with semantic rigor to create a lasting, citable resource. It could be:

A complex concept you’re struggling with at work
A skill you’re developing in your free time
A research question you’re investigating
A book or paper you’re working through

Start with these steps:

Choose a specific concept you’re actively learning (not something you already know)
Write a clear explanation as if teaching someone new to the topic
Add proper citations for every source that informed your understanding
Include semantic markup (proper headings, meta descriptions, structured data)
Share your questions and confusion points openly
Publish it publicly on your blog, GitHub, or any platform that supports proper formatting

Share your learning experiment: Use #SemanticPublicLearning or #LearnInPublic when you post about your learning journey so others can discover and learn from your process. Whether on social media, your blog, or any platform where you share knowledge, make your learning visible and findable.

The knowledge you’re about to discover will not just belong to you. It will belong to everyone who might benefit from watching you discover it, now and in the future.

Join the Semantic Public Learning Journey

Speaking of making knowledge tools accessible: I’m using Hugo Blox for managing my blog and have been developing enhanced citation and bibliography features along with semantic integration capabilities. These tools powering the citations you see throughout this post, enable the semantic integration that makes Semantic Public Learning possible. All of these tools together form a framework that I’ll be sharing over the coming weeks. Follow me on LinkedIn, Twitter/X, or Medium to be the first to know and see Semantic Public Learning in action. You can also have a look at the Semantic Public Learning project page, it serves as a living document that tracks the journey as it develops. For best integration, you can also add the RSS feed of my blog, to always stay up to date without the need for a social media account. Comment below, share your perspectives, and help make it the interactive process it’s meant to be. Your questions and insights often become the catalyst for my next learning breakthrough.

Remember: every expert was once a beginner who learned in public. By adding semantic layers to our learning, we ensure that knowledge remains discoverable for future learners. See you in the comments!

References

1. Abramov, D. (2019, 23). Why My New Blog Isn’t on Medium Medium. Retrieved 1, 2025, from https://medium.com/@dan_abramov/why-my-new-blog-isnt-on-medium-3b280282fbae
2. Martirena, C. C. (n.d.). How Teachers Can Use Pedagogical Documentation for Reflection and Planning Edutopia. Retrieved 29, 2025, from https://www.edutopia.org/article/how-teachers-can-use-pedagogical-documentation-reflection-and-planning/
3. Founder, T. H. & TeachThought, D. (2019, 9). What Is The Feynman Technique? TeachThought. Retrieved 29, 2025, from https://www.teachthought.com/learning-posts/how-to-use-the-feynman-technique-learning-by-simplifying/
4. Lachner, A., Hoogerheide, V., Gog, T. & Renkl, A. (2022). Learning-by-Teaching Without Audience Presence or Interaction: When and Why Does it Work? Educational Psychology Review 34 (2), 575-607 https://doi.org/10.1007/s10648-021-09643-4
5. Kiv, A., Soloviev, V., Tarasova, E., Koycheva, T. & Kolesnykova, K. (n.d.). Semantic knowledge networks in education ResearchGate. https://doi.org/10.1051/e3sconf/202016610022
6. Mojarad, S. (2020, 20). A Beginners Guide to Academic Twitter Medium. Retrieved 29, 2025, from https://medium.com/@smojarad/a-beginners-guide-to-academic-twitter-f483dae86597
7. Stewart, B. (2016). Twitter as method: Using twitter as a tool to conduct research ISBN: 978-1-4739-1632-6
8. (n.d.). Citation Style Language Citation Style Language. Retrieved 1, 2025, from https://citationstyles.org/
9. (n.d.). citation-style-language/styles: Official repository for Citation Style Language (CSL) citation styles. Retrieved 1, 2025, from https://github.com/citation-style-language/styles
10. (n.d.). NileRed - Official Website NileRed. Retrieved 29, 2025, from https://nile.red
11. Brawn, N. (n.d.). NileRed YouTube. Retrieved 1, 2025, from https://www.youtube.com/channel/UCFhXFikryT4aFcLkLw2LBLA
12. Rajapaksha, M. (2023, 24). Who Is Behind NileRed? | The Untold Story of the TikTok Chemist Taking the Internet by Storm. Starsbiopedia.com. Retrieved 1, 2025, from https://starsbiopedia.com/nilered-nigel-braun-age-biography/
13. (n.d.). MDN Web Docs GitHub. Retrieved 1, 2025, from https://github.com/mdn
14. (n.d.). 3Blue1Brown Retrieved 29, 2025, from https://www.3blue1brown.com/3blue1brown.com
15. (n.d.). 3Blue1Brown YouTube. Retrieved 1, 2025, from https://www.youtube.com/channel/UCYO_jab_esuFRV4b17AJtAw
16. Wei, P. (2020, 24). 3Blue1Brown creator Grant Sanderson ’15 talks engaging with math using stories and visuals Retrieved 1, 2025, from https://stanforddaily.com/2020/01/24/3blue1brown-creator-grant-sanderson-15-talks-engaging-with-math-using-stories-and-visuals/
17. Sanderson, G. (2025). 3b1b/manim https://github.com/3b1b/manim
18. Qureshi, I., Bhatt, B., Parthiban, R., Sun, R., Shukla, D. M., Hota, P. K. & Xu, Z. (2022). Knowledge Commoning: Scaffolding and Technoficing to Overcome Challenges of Knowledge Curation Information and Organization 32 (2), 100410 https://doi.org/10.1016/j.infoandorg.2022.100410
19. Spiro, K. & Bhamidi, V. (2021, 16). Open learning and knowledge sharing in a remote working world Chief Learning Officer. Retrieved 29, 2025, from https://www.chieflearningofficer.com/2021/08/16/open-learning-and-knowledge-sharing-in-a-remote-working-world/

Learn in Public

Tue, 05 Aug 2025 00:00:00 +0000

From Individual Discovery to Collective Intelligence

Post 1 of 2 in the Series: Semantic Public Learning Framework series

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Picture this: You’re struggling to understand how human memory works. Mid-explanation to a friend, you say: “… kind of like when we tried to piece together that party from last year: you remembered the music, I remembered the cake, Sarah remembered who was there. None of us had the full memory, but together it all came back…” Then it hits you. That might just be how the brain remembers, not stored in a single location, but distributed across a vast neural network. You just understood in 30 seconds what hours of reading couldn’t clarify.

Now, why does explaining in the open unlock insights that studying alone never could? The answer reveals something remarkable about how knowledge is built.

The Teaching Paradox

Nobel Prize-winning physicist Richard Feynman believed that true understanding meant being able to explain complex ideas simply. His colleague David Goodstein recounted how Feynman once said about explaining a complex physics concept: “I couldn’t reduce it to the freshman level. That means we really don’t understand it" ¹ . This philosophy, that if you can’t explain something simply, you don’t truly understand it, became the foundation for what we now call the “Feynman Technique.” However, the systematic four-step technique commonly attributed to him appears to be a modern construction based on his general approach ² rather than something he explicitly formulated.

The technique involves: choose a concept, explain it as if teaching a sixth-grader, identify knowledge gaps, and simplify further. While this method is sound, I propose adding one crucial step that amplifies its benefits for everyone: document your learning journey and share it publicly.

Traditional learning: You’re learning how LLMs choose the next token. You write an explanation on paper, pretending to teach it to an imaginary sixth-grader: “The AI looks at all possible words and picks the most likely one based on what it learned during training.” You realize you don’t understand the probability calculation, study more, and refine your explanation. The learning remains private.

Learning in public: You follow the same process but document and publish that explanation on your blog, explicitly noting your confusion about the probability calculation. Now the magic happens: a machine learning engineer comments with a clearer explanation, someone shares a helpful visualization, and a student asks a question that reveals another gap. Your learning becomes collaborative.

The difference? When you teach to an imaginary audience, learning stops with you. When you learn publicly, knowledge spreads and grows within learning communities ³ , transforming individual understanding into collective intelligence.

Discovering Learn in Public

As I developed this concept while writing this post, I initially called it “public learning.” But in the spirit of the practice itself (openly documenting my learning journey), I discovered I wasn’t the first to explore this territory. Shawn Wang (swyx) ⁴ had already articulated a framework called Learn in Public ⁵ that captured much of what I was describing. This discovery exemplifies the principle I’m exploring: by working through ideas openly, I found existing wisdom that sharpened my understanding. I’ve adopted the term Learn in Public, building on this foundation while adding my perspective and contributions. I’ll use the more natural phrase learning in public when it fits better in context, but both refer to the same core idea.

Learn in Public is the practice of deliberately documenting and sharing your learning process in real-time, creating openly accessible knowledge artifacts that benefit both your understanding and the broader learning community.

The Research Foundation

Learning in public’s effectiveness is backed by converging research findings that explain why this approach transforms individual learning into collective intelligence.

The foundation starts with the act of teaching itself. Research shows that both preparing for and actually teaching academic content significantly enhance learning outcomes ⁶ . When you prepare to teach material publicly, you engage in more sophisticated cognitive processing than private study requires. The more complex the teaching activity, the more opportunities to learn by teaching ⁷ , and public documentation is inherently complex, requiring you to anticipate questions, structure information clearly, and fill knowledge gaps you might otherwise ignore.

This enhanced processing leads directly to improved retention. Weinstein et al. showed ⁸ that bringing information to mind directly improves memory for that information, and public documentation forces continuous retrieval and reorganization of knowledge. Unlike traditional teaching in a classroom, learning in public makes this process transparently visible and persistently accessible, creating artifacts that serve as both personal reference and community resource.

But the real magic happens at the community level. Learning in public transforms individual study into systematic knowledge documentation where learners acquire life skills along with subject matter ⁹ while creating resources others can build upon. Knowledge sharing contributes to success ¹⁰ through positive impacts on creativity, learning, and performance. The public dimension creates what educational research terms learning communities ³ where participants experience higher retention rates, with belonging and support contributing to increased persistence and success.

Perhaps most importantly for our digital age, documenting learning creates knowledge graphs that significantly promote collaborative knowledge building, group performance, and social interaction ¹¹ . Each concept you explain becomes what researchers call a semantic node ¹² in a broader knowledge network. These artifacts must be machine-readable to maximize impact, just as search engines need to understand your content to rank it effectively, your learning artifacts need proper structure, clear terminology, and semantic markup (like a Wikipedia page the internet links to). This makes them discoverable by indexers so both humans and AI agents can find them. This is commonly known as search engine optimization (SEO), but it’s more than that: by properly linking and annotating your writing, you ensure your knowledge contributions integrate into the expanding web of human understanding.

When you learn in public, you’re improving your own understanding while participating in the collaborative construction of knowledge itself.

Semantic Public Learning

While Learn in Public provides the foundation, I’ll show you in my next post in this series how we can enhance it further with what I call Semantic Public Learning by adding academic rigor and machine-readability to maximize both personal learning and collective knowledge building.

Follow me on LinkedIn, Twitter/X, or Medium to be the first to know and see Semantic Public Learning in action. You can also have a look at the Semantic Public Learning project page, it serves as a living document that tracks the journey as it develops. For easy integration, you can also add the RSS feed of that page, or the RSS feed of my blog, to always stay up to date without the need for a social media account. Comment below, share your perspectives, and help make it the interactive process it’s meant to be. Your questions and insights often become the catalyst for my next learning breakthrough.

Remember: every expert was once a beginner who learned in public.

See you in the comments!

References

1. Goodstein, D. L. (1989). Richard P. Feynman, Teacher Physics Today 42 (2), 70-75 https://doi.org/10.1063/1.881195
2. Gleick, J. (1993). Genius: the life and science of Richard Feynman Vintage Books ISBN: 978-0-679-74704-8
3. Zamiri, M. & Esmaeili, A. (2024). Methods and Technologies for Supporting Knowledge Sharing within Learning Communities: A Systematic Literature Review Administrative Sciences 14 (1), 17 https://doi.org/10.3390/admsci14010017
4. (n.d.). swyx.io/about Retrieved 29, 2025, from https://www.swyx.io/about
5. (n.d.). Learn In Public Retrieved 29, 2025, from https://www.swyx.io/learn-in-public
6. Fiorella, L. & Mayer, R. E. (2013). The relative benefits of learning by teaching and teaching expectancy Contemporary Educational Psychology 38 (4), 281-288 https://doi.org/10.1016/j.cedpsych.2013.06.001
7. Duran, D. (2017). Learning-by-teaching. Evidence and implications as a pedagogical mechanism Innovations in Education and Teaching International 54 (5), 476-484 https://doi.org/10.1080/14703297.2016.1156011
8. Weinstein, Y., Madan, C. R. & Sumeracki, M. A. (2018). Teaching the science of learning Cognitive Research: Principles and Implications 3 (1), 2 https://doi.org/10.1186/s41235-017-0087-y
9. Burow, O. & Bornemann, S. (Eds.) (2018). Das große Handbuch Unterricht & Erziehung in der Schule Carl Link ISBN: 978-3-556-07336-0
10. Fan, Z. & Beh, L. (2024). Knowledge sharing among academics in higher education: A systematic literature review and future agenda Educational Research Review 42 , 100573 https://doi.org/10.1016/j.edurev.2023.100573
11. Zheng, L., Niu, J., Long, M. & Fan, Y. (2023). An automatic knowledge graph construction approach to promoting collaborative knowledge building, group performance, social interaction and socially shared regulation in CSCL British Journal of Educational Technology 54 (3), 686-711 https://doi.org/10.1111/bjet.13283
12. (n.d.). Semantic network Wikipedia. https://en.wikipedia.org/w/index.php?title=Semantic_network&oldid=1299856638 Retrieved 29, 2025, from https://en.wikipedia.org/w/index.php?title=Semantic_network&oldid=1299856638

Semantic Public Learning | Heye's Blog

Semantic Public Learning

Evolving the Learn in Public method

The Four Pillars of Semantic Public Learning

1. Semantically-Enhanced Documentation

2. Citation-Backed Explanation

3. Community-Validated Refinement

4. Knowledge Graph Integration

Practicing Semantic Public Learning: Real-World Examples

What Makes Semantic Public Learning Different

The Broader Impact

The Semantic Public Learning Movement

Your Semantic Public Learning Challenge

Join the Semantic Public Learning Journey

References

Learn in Public

From Individual Discovery to Collective Intelligence

The Teaching Paradox

Discovering Learn in Public

The Research Foundation

Semantic Public Learning

References