Web3, Crypto & Learning
The original post can be found on Mirror. This post is an extension of the tweetstorm I did in early October 2021
Web3, crypto & blockchain are making waves in art, music, and fintech today. How will web3, crypto, and blockchain affect edtech & learning? In this post I outline what I’m seeing so far.
Today I’m seeing early efforts in a couple of areas:
- Future of Learning: Learn to earn
- Future of Learning: DAOs as universities or Learning DAOs
- Future of Learning: Credentials, transcripts
- Future of Earning: Career funding: creator coins, securitized music
- Future of Earning: Freelancer networks
In this collectible post, I’ll dive into each of these and where there’s additional opportunity in web3 x learning.
Learn to Earn (L2E)
Taking a note from play to earn (P2E) successes like Axie Infinity, companies like Rabbithole are pioneering a L2E model that rewards people for performing tasks & learning skills. There’s L2E for language learning, reading newsletters, branding and social design, and new protocols, all rewarded with tokens.
People have paid students to study or given prizes for top results for years. But the benefits of L2E include on-chain ledger of skills, and potentially stronger motivation for learners. An early blockchain approach to L2E dates back to 2015 when Professor Gunnar Stefansson received funding from the University of Iceland. His site Tutorweb, has enabled students in Iceland & Kenya to earn the $SMLY coin he developed for learning. He says he has had over 1,000 students earn $SMLY tokens.
As someone with a Masters in Education, I am obliged to point out the research by Roland Fryer and others has shown paying people for behaviors associated with learning can improve achievement, but paying people solely for attaining higher scores doesn’t seem to work. Some critics worry about intrinsic motivation and this is a real concern. There is a lot to learn about the long-term effects of paying learners, especially children, for years on end, to pursue learning. But if designed correctly, L2E models could have a real basis in encouraging students to take the actions that lead toward better learning.
Elements of top designed L2E models will include:
- payment for online and offline behaviors that support learning
- ability to integrate with other services that track supporting behaviors (e.g. contributing to a community, habit formation)
- ability to assess depth of learning and weight credential appropriately — teaching someone else is a far stronger retention method than reading about something
Another innovation area is universities as DAOs or Learning DAOs. DAOs are decentralized autonomous organizations or decentralized communities where any token holder has voting rights & a shared “bank account.” These are a few great primers on DAOs for those new to the concept. DAOs can manage and deploy L2E courses, credentials & learning environments for their community. Colleges can be slower moving given the amount of time it takes to accredit a new degree or field of study, so DAOs could have an advantage in fast moving fields.
This piece by Kassen is an excellent breakdown of the value & function that today’s higher education institutions serve and how DAOs could serve many of these purposes. She highlights potential issues and opportunities like admissions & life-long learning.
Quite a few DAOs as learning communities already exist. One such is Crypto, Culture & Society — a course built on Mirror that used crowdfunded crypto to come to existence. Their backers received an NFT for membership & tokens for voting on syllabus, scholarships, guests, and more. In some ways this decentralized, crowd-funded form of education reminds me of Kritik, an innovative web2 peer assessment platform that allows peers to contribute to the syllabus, rubric, and evaluation of other students.
There is also the Ethernaut DAO, a learning organization geared at helping train the next generation of ETH developers. This could be the General Assembly or Lambda of the future. Soon traditional learning orgs for adult learners may need to learn to setup DAOs to be competitive long term
Here’s a few things the best learning DAOs will need to get right:
- scholarships & admissions — many DAOs today are pay-your-way-in and clearly that’s not equitable. many DAOs are also first-come-first-serve which means great potential members who arrive later may never get the chance to buy the initial set of limited tokens
- trusty & safety — so many things can go awry while running a social, living, breathing community. a robust set of standards with community escalation policies is crucial to ensure a thriving social community
- choose signal v. skill priority — the problem with many higher education institutions is that they have chosen to prioritize the signal of their credential versus specific skills as what brands them in the market. It is easy to fall into this trap if assessment, admissions, and brand aren’t thought through.
- proof-of-skill creep — many universities experience grade inflation, which makes differentiation difficult. For a learning DAO to maintain the value of it’s credentials, it will need to ensure decentralized management holds the same bar
Credentials are one of the most cited uses of web3 in edtech. Verified credentials about one’s education history could be shared in a blockchains immutable ledger. MIT has been using blockchains to release transcripts since 2015. Originally called Blockcerts Wallet, it’s an open standard for blockchain credentials created by the MIT Media Lab.
MIT isn’t the only one. Maryville also allows students to access blockchain-based transcripts. They use pistis.io. Traditional higher education news outlets such as Inside Higher Ed have been writing about this space for years. Despite being one of the longest discussed use cases, a singular platform for blockchain transcripts hasn’t broken through.
Professor Beau Brannan at Pepperdine experimented with minting NFTs for his college finance class on the OpenSea platform.
NFTs are likely not the right platform for credentials however given they can be freely transferred. This isn’t core (in fact really antithetical) to the use case of transcripts. A blockchain entry should be sufficient to demonstrate provenance, so we’ll have to wait and see if another platform reaches mass consumer scale for this use case in the future.
Another exciting potential in credentials is real-time skill acquisition and display. Given crypto credentials can be earned for individual tasks, a student wouldn’t need to wait 4 years to get credit for their knowledge. Real-time progress of their degree could be visible for all anytime. If an employer decides xyz skills or 75% is enough, the learner may not need to go further.
People are calling this “proof of skill” and it overlaps with the world of “competency based education” = a movement in education that has tried to give learners credit for what they know, not just butt-in-seat or Carnegie hours which are based off of hours spent in class.
Here’s a few things crypto credentialing platforms will need to get right:
- partnerships with employers — new forms of credentials have long been hard to establish because adoption by employers is slow. it’s easy for them to rely on top college rankings
- review sites for DAOs and crypto credential issuer — as any new industry emerges, consumers and employers need to sift through the noise. There are already nearly 1M DAO members today
- public education and category creation — the hardest part of any new credential is acceptance by the public. new credentials will need to collaborate and share where they are finding pockets of acceptance so the whole industry can succeed.
Formal education and credentialing is an important avenue for many forms of work. But there are some categories of work, especially those in the creative fields, where education takes the form of experimentation and exploration. Music, Art, and indeed any form of content creation, whether it be on Tiktok or movie screens can all fall into this category. But this experimentation needs resources. That’s what makes creator coins and securitized music such an interesting area of web3. These new categories allow supporters to invest in their favorite creators and receive a stake of their future income as a result, an area that turns patronage into investment, and is directly adjacent to education. I especially like creator coins and securitized music because college isn’t always a great fit for creatives. Creator coins can be a better fit for high risk, high reward professions that help artists avoid the starving artist fate.
If you’ve been in the education world for some time, this might sound a bit like ISAs or income share agreements. With student debt in the USA at $1.57 trillion or $36k on average, we do need more options. But, although a few schools still have them, ISAs never took off.
Securitized music is a specific subset of creator coins that focus on sharing a % of royalties. Companies like Royal, Vezt & others are defining the category.
Here’s a few things creator coins and securitized music builders will need to get right:
- Clear design choice on fungible v NFT — tokens are fungible, NFTs are not. I’m seeing players build both right now. The NFTs definitely have supporter fan value, but may have different implications for liquidity and how creator coins are valued.
- Consumption v. hold focus? Platforms naturally want to provide an outlet for liquidity. Does this mean spending the currency on their platform for special 1v1 interactions with the artists? Does it mean creating a secondary exchange? What behavior do you want to drive with fans, speculation or real interest?
- First-come v gated access? Similar to learning DAOs, creator coin builders need to figure out if they want to reward loyal fans and give them access, thus seeding their initial users with more of a fan club audience, or open it up to the public, increasing the likelihood that prices rise quickly as crypto whales come in.
Freelancing on Blockchain
Freelancer networks are being built on the blockchain like Braintrust. In Freelancer-owned orgs, members earn a share of all the projects completed by other members and give input on governance. For example, when a client issue persists over time, disputes could go to a jury to determine new policies. These networks can also use tokens to reward new customers who refer business rather than a referral fee, potentially increasing the attractiveness of such an offer. The freelancing network could theoretically charge lower prices since platform take rates on places like Upwork or Fiverr are replaced with shared earnings.
Here’s a few things freelancing platforms will need to get right:
- ejection of members — if someone is no longer pulling weight or begins performing poor quality tasks, how do you address or remove them while keeping in mind decentralized governance and their ownership stake
- handling losses — members share in gains, but what about projects where clients ask for refunds or aren’t satisfied with the work done?
- management of DAO tools — this type of group, perhaps more than most, may resemble a more traditional company that needs lots of shared resourcing and tools. there are now so many tools supporting DAOs that they’ll need to get a handle on everything available in addition to traditional corporate saas tools
These are just 5 areas where Web3 x Edtech are intersecting. There is truly so much more to build and I can’t wait for the future.
When I think about where there are gaps in the market today between existing and future Web3 and Learning tools, I refer to a few market maps and frameworks I’ve used to think holistically about this sector in the past.
When I look at HolonIQs education blockchain market map from 2018, before this current wave of crypto, there were already tons of examples of learning DAOs, learn to earn models, and credential solutions.
HolonIQ’s market map from 2018 of Blockchain & Learning
I also think about the five areas I’m seeing gain steam today in relation to two of my learning sector frameworks (see below and here, here).
From my Lightspeed Edtech Portfolio post
From my 2019 Future of Workers post
So given these frameworks, where am I hoping to see solutions for Web3 x Learning? Here’s just a few:
- hiring platforms tied to DAOs
- job-integrated proof of skill (like degreed)
- assessment: proof of task does not equal mastery of concept
- early childhood and k12: most of innovation today is for adults
- corporate learning & internal mobility
- career discovery
- job search & hiring tools
- on-the-job performance enablement tools
Thanks so much for reading this post and perhaps the tweet that inspired it. If you are forming a learning DAO, want to crowdfund a course, or are building startups solving any of the solutions areas, hit me up! I would love to continue the conversation.