Current models of academic credentials are based on the outmoded requirements of the Industrial Age. Back in those factory-like work environments, we needed to ensure that people with the same level of education received the same credential as a way of indicating to future employers that they could do a certain job.
Those credentialing bodies were often Universities. And, they used two systems to measure academic qualification: instruction time (that translated into credit hours) and exam performance (that translated into grades).
However, as we have now come to realise, there is little or no correlation between credit hours, grades and actual skill. Exam grades indicate only one thing: that the student is good at taking tests.
Moving forward in an age of exponential technologies, increased automation, and ubiquitous A.I. we will start to see a shift in what we measure when we credential. We will see a transition from credentialing what is taught to, instead, credentialing what has been learnt and can be exhibited. We are already seeing this happen in a limited way and it is an appropriate and long-needed transformation in education.
At the 2016 Parchment Conference on Innovating Academic Credentials, Arthur Levine, President of the Woodrow Wilson National Fellowship Foundation, delivered the Education Keynote Address, in which he stated, “What we really need to do is achieve common definitions of competencies. What we really have to do is create the equivalent of the DSM in psychiatry: The Diagnostic and Statistical Manual of Mental Disorders. It offers a common language and standard criteria for classifying mental illnesses. We need that for competencies. When we talk about competencies, we have to be talking about the same thing, or it’s just another buzzword. We have to develop assessments that measure student progress and attainment of the standards or the outcomes and help us prescribe to students what it is they need to do in order to achieve those competencies.”
If we can codify, classify, and categorise mental disabilities, surely we ought to make some attempt to do the same with abilities and competencies?
In her book, Academic Credentials in an Era of Digital Decentralization, Natalie Smolenski makes the point that a standardised credentialing system would give employers, granting agencies, professionals, researchers, and creative workers a heuristic to more effectively distribute of all kinds of labour across the landscape of generative human possibilities.
Skills are dependent on social and cultural contexts. Howard Gardner is the professor of cognition at Harvard University. He defines intelligence as the ability to find and solve problems and create products of value in one’s own culture. Something similar may also be said about skills. Thus, if we agree that skills are only useful in a socio-cultural context then any attempt to classify skills is only a temporary appraisal of what is useful in that particular cultural milieu or socio-economic context. Also, it is useful to bear in mind that the kind of skills that can be credentialed are, at a fundamental level, a measure of value that has been conferred on a person by an organisation or by another individual. Therefore, this unit of value can be recorded in any ledger that records transactions of values.
Natalie Smolenski points out that this is precisely what the Bitcoin blockchain protocol does. “It records three things: the value itself, who conferred it, and to whom it was conferred. Because what the protocol records is transactions of value as such, the actual content of that value can be specified on the application layer. In the case of Bitcoin, this value is often thought of in terms of currency (“I’ll send you $35 in Bitcoin.”). Rather than serving a currency function, however, blockchain-based credentialing records which credentials have been issued to which learners by which institutions. These records are fixed and immutable, but the content of credentials can vary endlessly over time and across different professional and cultural contexts. This gives impetus to the call for standardised definitions of skills in order to streamline the evaluation of qualifications in what is already a global information economy.”
Once we start credentialing skills and competencies on the blockchain, we will be able to address more reliably the issue of what constitutes a skill. More important than that, it will allow us to stop depending on Universities and institutions of higher learning as the ultimate arbiters of skill. No longer will the university degree have the kind of importance that is has had until very recently.
Making this transition will address a range of problems we currently face, including unequal quality of education within and across institutions; academic programs that are too broad to focus on a narrow set of skills; and the issue of transferring credentials between countries or exam boards.
The current system sees time spent translated into credit hours, intelligence and skills translated into grades, and both these exchanged for currency (future employment). However, as employers are increasingly becoming aware this is a flawed system of exchange. Credit hours and grades are not a reliable indicator of skills. A student can have many hundreds of hours in credits and the best grades, but that is just not a reliable indication of how well they will be able to perform a particular job. This is also one of the reasons why in 2015 Ernst and Young dropped degree classification threshold for graduate recruitment saying there was ‘no evidence’ that success at university was linked to achievement in professional assessments.
It should definitely give us pause for thought if one of UK’s biggest graduate recruiters has decided to remove degree classification from the entry criteria for its hiring programmes.
Currently, potential employers don’t have the time or means to decide which prospective employee has the skills they are looking for. They depend on University degrees to give them a vague idea of this. So we have a situation where universities perpetuate a top-down credentialing system. They decide which skills a student has or doesn’t have and they base it only on two things: credit hours and grades.
However, the days of the University as the ultimate arbiter of skills and the absolute social authority for setting standards and credentialing are numbered. We are now beginning to see new communities of verification that will increasingly be able to credential skills and define standards of content. These communities comprise of the same individuals that depend on standards and engage with credentials. In other words, what we’re beginning to see is a bottom-up process of credentialing and standardisation that is more democratic and less dependent on the rigid and almost dictatorial system of the past.
We will increasingly see this process being played out using the blockchain to bypass traditional Universities and conventional credentialing bodies. Fundamentally, a credential is a verification that a person has the skill, smarts, intelligences, fluencies, competencies and experiences that they claim. This essential barter of trust is now being done in new ways that no longer depend on Universities. Students are using alternative certifications from platforms like Coursera, and edX; they are depending on badges and endorsements from professionals on LinkedIn; they use learning marketplaces like Quora, Stackoverflow, and Kaggle; and they are starting to use a range of online mentoring and educational platforms like Awecademy, Skillshare, Masterclass etc.
Many of these platforms are experimenting with offering open source credentialing using the blockchain. This distributed verification ensures transparency and serves to counter the rigidity bureaucracy and inability to adapt of traditional universities. The blockchain has many uses, but one of it is to encode and verify credentials. Natalie Smolenski points out that “This is where the blockchain makes its fundamental intervention as a social and technological infrastructure. As a cryptographically-administered, distributed ledger beyond the control of any individual or group of individuals, the blockchain creates a jurisdictional space that cannot be gamed by powerful actors — something which is continually happening with law. Moreover, its pseudonymous key structure ensures that individual privacy is maintained through discretionary gating while preserving quasi-traceability in cases of illegal activity. This sets the precedent for digital self-sovereignty in a context of the collective right to verify investment-based social claims.”
Bottom-up open source systems of verification and credentialing on the blockchain represents a powerful new way in which we measure integrity and repose trust. Figuratively speaking, what we are now witnessing is the digital equivalent of the French Revolution. The consequences of digital self-sovereignty will be far-reaching and profound.
12 April 2019 | Rohan Roberts | www.rohanroberts.com