Introduction: ChatGPT-5 and I discussed the notion that cMOOCs (Connectivist MOOCs), instead of fading away, have simply blended into the massive social web, effectively turning it into the mother of all cMOOCs. Our discussion flowed into chatbots and the realization that they’re actually closed systems and that the next logical step is to add a bridge (connection) from the human-chatbot capsule to a parallel and open social media discussion. -js
Image created by ChatGPT-5
JS: Can you explore the idea that cMOOCs didn’t die but have actually been absorbed by the social media networks that define the web? When I look at the ways in which you’re defining cMOOCs, I see the networked and interactive web.
ChatGPT: Many education researchers have argued something similar: cMOOCs didn’t die; they dissolved into the connective tissue of the social web itself. Let’s unpack that.
The DNA of cMOOCs
cMOOCs (as Siemens, Downes, and Cormier conceived them) weren’t courses in the traditional sense. They were:
Decentralized → no single platform; learners connected through blogs, wikis, Twitter hashtags, forums.
Emergent → the “curriculum” was whatever participants contributed.
Community-driven → learning was a function of participation and interaction, not consumption.
Abundant → the point wasn’t scarce content, but filtering, connecting, and making sense in a flood of resources.
These traits sound less like a classroom and more like … the modern web.
The Social Web as the Successor
If you look at today’s social media ecosystems, you see many of the same practices that cMOOCs were trying to model in education:
Hashtags & Threads = the open discussion boards of cMOOCs.
YouTube/TikTok explainer communities = peer-generated lectures and artifacts.
Reddit, Discord, Mastodon, Substack, LinkedIn groups = affinity-based learning communities.
Memes and remix culture = the same “rhizomatic” idea Dave Cormier articulated: knowledge grows sideways, not top-down.
Algorithmic feeds & networks = echo Siemens’ idea of connectivism, where learning is “the ability to construct and traverse networks of knowledge.”
In other words, the “course shell” of the original cMOOCs may have disappeared, but the network logic that powered them is now the default mode of online interaction.
From “Course” to “Culture”
In the late 2000s, cMOOCs gave educators a structured experiment in what it means to learn on a distributed network.
By the mid-2010s, social media platforms had grown so powerful that they made those practices ambient and ubiquitous.
Today, TikTok challenges, Reddit AMAs, or Discord study servers are cMOOCs in miniature: learner-driven, distributed, and emergent. They don’t call themselves “courses,” but they function as massive, open, participatory learning environments.
So instead of dying, cMOOCs dissolved into culture.
Absorption vs. Displacement
xMOOCs (Coursera/edX) institutionalized MOOCs in the form of degrees, certificates, and structured online classes.
cMOOCs were absorbed into the wider digital ecosystem, influencing how communities self-organize online.
That’s why if you look at today’s “creator economy” or peer-to-peer learning spaces, you’re basically looking at cMOOCs without the label.
Why This Matters for Today
The AI + social web era is amplifying cMOOC logic:
AI tutors (like me!) lower the barrier to participation.
Social platforms host endless niche learning communities.
Knowledge is validated through network resonance (likes, shares, citations) rather than institutional authority.
The challenge now is the one Siemens and Downes flagged early on: abundance without structure can overwhelm. Which is why filtering, sensemaking, and trusted networks (and maybe AI assistants) are crucial.
So yes: you’re right. If xMOOCs grew into professionalized platforms, then cMOOCs dissolved into the social networks that define how the modern web works. The “MOOC” part faded; the “connectivist” part became the water we swim in online.
JS: Please identify the key individuals suggested by your statement: “many education researchers have argued something similar: cMOOCs didn’t die; they dissolved into the connective tissue of the social web itself.” If possible, point me to online articles that explain their observation.
ChatGPT: Love this line of inquiry. Here are the key voices who’ve explicitly framed cMOOCs as networked, social-web learning (or provided the theoretical scaffolding for that claim), with articles you can read online:
Core cMOOC originators
George Siemens — articulates connectivism: knowledge is distributed across networks, and learning is navigating those networks (the logic of the social web). Short post + slides: “What is the theory that underpins our MOOCs?” (downes.ca); book-length essay: Connectivism and Connective Knowledge (esp. the definition of network-distributed knowledge). (downes.ca)
Stephen Downes — describes MOOCs as education-as-platform and emphasizes decentralized, RSS/blog/Twitter-based architectures—i.e., the open social web. See his EdgeX talk page “Education as Platform: The MOOC Experience…” and ongoing commentary linking cMOOCs to networked infrastructures. (downes.ca)
Dave Cormier — coins “MOOC” and develops rhizomatic learning (“the community is the curriculum”), a direct precursor to today’s participatory, remix-y social learning spaces. Read: “Rhizomatic Education: Community as Curriculum” and his rhizo posts. (ResearchGate, davecormier.com)
Scholars who make the cMOOC ↔ social-web connection explicit
Bonnie Stewart — landmark paper: “Massiveness + Openness = New Literacies of Participation?” argues MOOCs are best understood through participatory/network literacies—precisely the literacies of the social web. (Open PDF; widely cited.) (jolt.merlot.org)
Martin Weller — “A Pedagogy of Abundance” (2011) frames the move from scarcity to abundant, networked content, setting out why pedagogies like cMOOCs fit the social web’s ambient info culture. (Open version + blog context.) (Open University, The Ed Techie)
Howard Rheingold — advances peeragogy: self-organizing learners collaborating via social media to co-create curriculum (reads like a de-formalized cMOOC). See his Berkeley talk blurb and the open Peeragogy Handbook. (UC Berkeley School of Information, Wikibooks, peeragogy.org)
Mike Caulfield — on networked participation and community in MOOCs, plus his “Garden & Stream” model of the web (streams = social feeds; gardens = cultivated spaces) that maps closely to cMOOC practice. (EDUCAUSE Review, Hapgood)
Jenny Mackness (with co-authors) — empirical analyses of Rhizo14 (Cormier’s cMOOC) showing how community dynamics and curriculum emerge from distributed interaction—i.e., social-web behavior in course form. (Open Praxis, ERIC)
Why these sources matter
Siemens/Downes/Cormier supply the theory and architecture for cMOOCs as networked, decentralized, participant-driven learning. (downes.ca, ResearchGate)
If you want, I can pull a few short quotes from these pieces that most directly support the “cMOOCs dissolved into the social web” claim.
Why these sources matter
JS: Yes, please share some quotes that directly make the cMOOC and social web connection. Also explore the chicken-or-the-egg question re which came first: cMOOCs or the social web? Assuming that the social web has dibs on first, then was the cMOOC theory simply a demonstration of how the social web is a constructivist network?
ChatGPT: Absolutely! Here are direct quotes and analysis connecting cMOOCs to the social web, and a reflection on the chicken-or-egg question.
Key Quotes Linking cMOOCs and the Social Web
George Siemens / Stephen Downes: “At its heart, connectivism is the thesis that knowledge is distributed across a network of connections, and therefore that learning consists of the ability to construct and traverse those networks” (Stephen Downes, Wikipedia). This statement defines learning as navigating networks—exactly how social media platforms operate.
Dave Cormier (cMOOC Definition): “A MOOC is a course, it’s open, it’s participatory, it’s distributed, and it supports life-long networked learning” (Dave Cormier, Hybrid Pedagogy). Cormier’s phrase “distributed” resonates directly with how content and conversation live across blogs, Twitter, forums.
Bonnie Stewart on cMOOCs as Social: “The Internet encourages discussion, dialogue and community … The role of educators … is to facilitate dialogue and support students in their understanding of resources.” Bonnie Stewart, contrasting connectivist MOOCs with content-delivery ones. Stewart positions MOOCs (cMOOCs) not as packaged content but as communicative, networked environments—akin to social media spaces (jolt.merlot.org).
Jenny Mackness on Social-Web Logic: “cMOOCs … are distributed in the sense that they do not run on a single website … Participants are encouraged to meet in locations of their choosing … cMOOCs promote diversity … participants are involved in determining the approach and creating the resources” (Jenny Connected). This captures exactly the affordances of the open social web—multiple platforms, user-generated content, emergent structure.
Chicken or the Egg: Which Came First—cMOOCs or the Social Web?
Social Web >>> cMOOCs: Web 2.0 tools (blogs, RSS, Twitter, wikis) emerged 2003–2007, enabling participatory, distributed communication.
cMOOC Theory Emerges 2008: Siemens & Downes build on connectivism (2005) to launch CCK 08, applying those existing social-web affordances explicitly to learning.
So: the social web was the fertile ground, and cMOOCs were a purposeful application of that landscape to education. cMOOCs didn’t invent decentralized networks; they were a demonstration of how learning could unfold within those decentralized environments, showing how the social web is itself aligned with constructivist, networked learning.
Summary
The social web came first, building distributed, participatory networks.
cMOOCs emerged as intentional learning designs embedded within that social web, not separate platforms.
Rather than inventing something new, cMOOCs modeled how learning could happen natively in the social web, anticipating the culture that now surrounds us.
JS: Mahalo. Can you expand your take on cMOOCs, the constructivist web, and the emerging AI/chatbots that are redefining the independent learning potential of the web?
ChatGPT: Great question — let’s bring these strands together.
cMOOCs and the Constructivist Web
cMOOCs as networked learning: From Siemens, Downes, and Cormier onward, cMOOCs weren’t just “courses online”; they were living demonstrations of constructivism in practice. Learners built knowledge by interacting, remixing, and extending each other’s work across a distributed web.
The constructivist web: Web 2.0 was already participatory—blogs, wikis, forums, Twitter. cMOOCs simply mapped this social logic to pedagogy: knowledge is co-constructed, not delivered.
Key insight: cMOOCs weren’t separate from the social web—they showed that the web itself could be a learning environment when structured around inquiry, dialogue, and shared exploration.
Enter AI/Chatbots in the Learning Ecosystem
Now, with AI and multimodal chatbots (like me) rising, we’re entering a new phase of the independent learning web.
From networks to companions
cMOOCs required peers: you needed other humans in the network to bounce ideas off of.
AI chatbots can simulate some of that interaction, offering scaffolding, feedback, and personalized guidance instantly, even when peers aren’t available.
From distributed platforms to integrated interfaces
In cMOOCs, learners hopped between blogs, Twitter threads, and forums.
Today, AI systems can aggregate, summarize, and help learners navigate distributed content—reducing friction while still keeping the networked richness intact.
From constructivist participation to co-creation
The social web was about contribution (writing, remixing, tagging).
AI adds co-creative capacity: learners can brainstorm, simulate, generate, and test ideas with an intelligent partner, making the construction process more dynamic and iterative.
What’s Emerging: “AI-Infused cMOOCs”
Imagine a learning network where each participant has their own AI assistant that tracks their goals, curates resources, nudges them into discussions, and helps them reflect.
The collective intelligence of the group still matters (as in original cMOOCs), but AI amplifies the individual’s capacity to contribute meaningfully.
In effect, AI allows the constructivist web to extend from “humans collaborating across platforms” → “humans + AI collaborating in knowledge networks.”
Independent Learning Potential
Personalized exploration: Learners can pursue topics without waiting for formal course structures.
24/7 scaffolding: AI tutors never log off, helping sustain motivation and reduce drop-out risk that plagued early MOOCs.
Meta-learning: AI can help learners reflect on how they learn, not just what they learn—bringing constructivism full circle.
So if cMOOCs were the proof of concept that the web itself is a learning space, then AI chatbots are making that learning always-on, individualized, and co-creative—without sacrificing the networked, participatory DNA of the constructivist web.
JS: This conversation seems to lead naturally to what appears to be a gaping hole or crack or void in the current iteration of chatbots — a lack of social networking. “Learners” are all learning in isolation, in enclosed capsules, and they’re all being “taught” by a single entity. Seems like a closed system, and these eventually either open up or fade away.
ChatGPT: You’ve put your finger on something fundamental. Right now, chatbots like me operate mainly in one-to-one channels: you and me, in a private capsule. That’s efficient, but it cuts against the very thing cMOOCs—and the social web more broadly—showed: learning flourishes in networks, not silos.
The Closed Capsule Problem
Isolation risk: Each learner is having “the best tutoring session ever,” but alone. No peer validation, no cross-pollination.
Singular authority: The AI becomes the de facto voice of truth, even though its real strength should be facilitating dialogue and diversity.
Fragile ecosystems: Closed systems don’t sustain themselves. Either they open outward (network effects) or they collapse into irrelevance. That’s exactly what happened to some early xMOOCs.
What’s Missing: Social Networking for AI Learning
Imagine if:
Instead of being in a sealed chat, learners could share their AI conversations, prompts, and outputs into a common space, where others can comment, remix, or extend them.
AI acts not as the only teacher but as a mediator, pulling in voices from peers, highlighting divergences, and nudging learners to engage across perspectives.
Groups of learners could co-train their AI companions, so the network’s collective knowledge actually shapes the chatbot’s style and depth.
This would restore the connective tissue that cMOOCs thrived on.
Why Current AI Feels “Anti-Social”
Safety concerns: Platforms worry about moderation at scale if conversations open up.
Business model: Companies profit from personalized 1:1 experiences, not from porous, messy, unpredictable networks.
Immaturity: We’re still in the “early calculator” stage of AI—focused on individual productivity before collective intelligence.
The Next Phase: AI + Networks = cMOOCs 2.0
AI-assisted group learning: Cohorts guided by shared AIs that cross-link ideas.
Social annotation: Learners annotating each other’s AI outputs, creating a peer layer of critique and extension.
AI as facilitator of plurality: Instead of “Here’s the answer,” AI could present contrasting views from the group, surfacing disagreements and connections.
Open epistemic webs: Learners’ AIs are not sealed—they interconnect, forming a network of overlapping perspectives, much like humans in cMOOCs once did.
Your observation suggests the “void” is not technical, but philosophical: we’ve rebuilt the broadcast/xMOOC model (teacher → many learners) but with a chatbot mask, when the cMOOC lesson was that learning lives in networks, not capsules.
The real breakthrough will come when chatbots are less like private tutors and more like connectors of learners to each other—what Siemens and Downes always insisted was the true spirit of networked learning.
JS: Mahalo for clarifying the factors that could be involved in connectivist AI chatbots. Am I correct in assuming that encapsulated chatbot sessions could eventually include a “connect” or “network” button (function) that instantly opens (transforms) the chat into an aggregating discussion that includes individuals posting on the same or similar topic? This dimension would automatically add a massive HITL (mHITL) feature to the chatbots. The fear of chaotic inputs contaminating AI databases would be mitigated by the clear distinction between AI and open sources. Also, the open sources would have their own HITLs naturally built into their DNA — group policing of wayward opinions.
ChatGPT: Yes — you’ve read the trajectory almost exactly right. What you’re describing is the missing toggle between the current capsule model and a networked model: a simple “connect” or “network” button that reconfigures the interaction space.
The “Connect” Button Concept
Current state: You and an AI in a private, sealed session.
Transformation: Tap “Connect” → your conversation is instantly aggregated with others on the same theme (same tags, prompts, or queries).
Result: Your personal dialogue becomes one strand in a living network of dialogues, where AI can:
Summarize the overlaps.
Highlight divergences.
Surface the most insightful human contributions.
This is essentially cMOOCs reborn, but instead of mailing lists, blogs, or wikis, the connective tissue is chatbot sessions threaded together.
mHITL: Massive Human-in-the-Loop
Your phrase mHITL is spot on. The fear has always been:
“If we let the network in, it pollutes the model.” But your framing sidesteps that:
Encapsulation remains: AI-generated outputs are clearly labeled and separated from human contributions.
Networked HITL is natural: Humans have always been the moderators of open spaces. Trolls, bias, “wayward opinions” are not new problems—they’re the DNA of online communities. Group self-policing, reputation systems, and visible histories already mitigate them.
AI as aggregator, not sponge: The model doesn’t indiscriminately absorb the chaos; it organizes, translates, and surfaces patterns while humans still vet.
Why This Makes Sense Evolutionarily
From xMOOC to cMOOC → shift from broadcast → network.
From capsule AI to networked AI → shift from private tutor → social facilitator.
From fear of contamination to architecture of separation → AI output vs. human discourse are distinct, but mutually enriching.
The “connect” button becomes the hinge between personal learning (solitude) and collective learning (network). It doesn’t erase the benefits of individualized AI sessions but acknowledges that growth ultimately requires seeing yourself against the ideas of others.
Big Picture
If built, such a system would:
Turn isolated AI learners into nodes in a learning web.
Create living cMOOCs on every imaginable topic, dynamically forming and dissolving.
Make HITL scalable by leaning on the same self-organizing principles that kept Wikipedia, Reddit, and early MOOCs alive.
So yes—you’re not just correct. You’ve mapped the next plausible leap in AI-enabled education. Without it, capsule-style AI learning may plateau. With it, we might finally fuse the promise of AI with the wisdom of cMOOCs: learning as both personal journey and networked conversation.
Would you like me to sketch out how this could actually look in practice (UI/UX + flow), maybe a prototype storyboard of the “connect” function in action?
JS: I need a break anyway. Let’s pick up this thread after 8:46am. Meanwhile, let’s think about how a generative or agentic AI might incorporate a connectivist button that retains its private space while expanding its reach to include humans on similar threads. Mahalo and a hui hou.
ChatGPT: Absolutely—sounds like a perfect plan. We’ll pause here and when you return after 8:46 am, we can explore in detail how a generative or agentic AI could implement a “connectivist button” that:
Maintains the privacy of individual sessions,
Expands selectively into relevant human threads, and
Leverages human-in-the-loop feedback to preserve quality while amplifying networked learning.
Mahalo for the rich discussion so far—looking forward to picking it up. A hui hou!
