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Technology Developments
& Opportunities

Technology has reshaped many areas of education, but some of the most profound changes are still to come. What role will leading-edge technology play in a CBE system?

The price of computing, storage, and devices has plummeted in recent years, leading to a dramatic improvement in access in most American schools and the development of early personalized learning models. New school development grant programs like XQ and NGLC have accelerated this development.

Two recent and significant technology advances that have not yet been incorporated into new school models — machine learning and blockchain — are discussed in this section. Also discussed are how these advances could help to advance a new form of credentialing. It is important to note that such developments will take time to take hold and these present a long-term vision rather than a short-term forecast.

Machine Learning

Code that learns may prove to be the most important invention ever. Machine learning (a subset of artificial intelligence), when combined with big data and enabling technologies like robotics, will produce extraordinary benefits and wealth (which is likely to be concentrated) but will lead to significant job dislocation and waves of challenging issues.

 

The most important implication of machine learning is the need for updated graduate profiles and transcripts that include broader measures of success.

 

In the next three to five years, machine learning will:

Looking further ahead, 10 to 15 years down the road, machine learning will support inexpensive, safe, on-demand transportation (through ride-sharing and autonomous vans), opening up secondary learning locations and opportunities. Combined with well-developed and widely available out-of-school credentialing systems (e.g., LRNG, MOOCs, dual enrollment programs, and career and technical learning), it would create a much more diverse and personalized secondary landscape. LRNG, for example, is a national network of youth-serving organizations that leverages technology and machine learning to provide experiences and issue badges that reward demonstrated progress on prioritized skillsets. This dynamic, personalized, and distributed learning future depends on a foundation of competency-based policies, practices, and tools.

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Blockchain

As a secure distributed ledger, blockchain technology provides a way for information to be recorded and shared by a community. Each member maintains an updated digital copy of the information, eliminating the need for an information intermediary. The cryptocurrency Bitcoin was the first widespread use of blockchain.   Blockchain will end paper-based certificates, automate the award, provide recognition and enable the transfer of credits, increase learner ownership and control over their own data, and reduce institutional data costs and risk — but only if open standards are adopted. Those are the findings of a new report by the Joint Research Centre (JRC), the European Commission’s science and knowledge service.   Often called “the new Internet” or the “Internet of Value,” blockchain (and Bitcoin) has been heavily trending in the technology press. While it is still a young technology, it is also becoming a topic of discussion in edtech and education policy circles.   Rob Abel, CEO of IMS Global Learning Consortium, said, “Blockchain is a very interesting technology that is already in limited use as a way to store traditional credentials, but the application of blockchain to reliably expand the use of micro-credentials is still in the realm of R&D.”51   Teacher micro-credentialing may be the first application for blockchain in education. It would allow teachers to earn credentials (some machine-scored, some human judgment, some combinations) and keep their own portable record without relying on a third party.   While blockchain will make it easier to share credentials, it leaves wide open the question of who creates and grants certifications. Employers and educational institutions will need to decide what knowledge and skills are important and how those are developed and assessed. In some cases, machine scoring will be able to verify certain skill claims, but in many cases with important and multidimensional skills, human judgment observation will remain important.   Blockchain will support lifelong learning by making it possible for everyone to assemble a record of learning and expanding capabilities represented by diplomas, certificates, credentials, and artifacts. But again, the value of these distributed records will be based on the quality of the credentials.   Pioneers in issuing blockchain-based credentials include:

Since 2015, the MIT Media Lab has been using the Blockcerts open standard (developed with Learning Machine) for issuing digital certificates.

Holberton School, a project-based coding bootcamp that takes a percentage of future earnings, delivers certificates in paper and with a blockchain digital certificate number that can be included on a resume and verified by an employer.

Sony has developed an in-house certificate-issuing system that uses blockchain to record educational achievements and activity records in an open and safe way.

Indorse is using blockchain to verify e-portfolios. Users upload claims with a link to verification and other users verify that claim.

In Europe, the Open University and the University of Nicosia have been experimenting with blockchain certificates. About two percent of Nicosia students pay tuition in Bitcoin.

BitDegree is a blockchain powered online education platform that will offer students online courses with a clear and transparent blockchain- based reward system and achievement tracking.

Smart contracts — automated transactions — can be set up in blockchain and executed when specific conditions are met. In some cases, learners will be able to take a test and earn a certificate immediately upon passing. Like Degreed Skill Certificates, an automated process could also incorporate human judgments. The benefit of smart contracts in credentialing will be that the learner can gain portable certification immediately without interacting with an intermediary for verification or record keeping.

 

A fully equitable personalized learning system would have weighted funding which could be supported by blockchain technology. Weighted funding (i.e., more funding based on more risk factors) could be provided immediately to schools (or to a learner education account) based on verified factors (e.g., family income, learning conditions) and provided to a bank account accessible by certified learning providers based on a provision of a learning experience and associated certificate. For example, if a learner chooses private piano lessons over school choir, a certified teacher could receive automated payment based on demonstrated progress.

 

There are a few startups in the payment space. EduDAO is a nonprofit Ethereum-based blockchain platform that wants to be a public utility that any school can use. They also plan to support crowdfunded causes and impact-focused startups.

 

It seems clear that blockchain will transform credentialing. More broadly, where political hurdles can be crossed, it should enable personal portable learning profiles that will inform a variety of machine learning applications powering much more sophisticated forms of personalized learning, especially when combined with expanded learning options, smart advising, portable payment mechanisms, and a series of smart contracts.

 

The combined potential of machine learning and blockchain technology warrants expanded research and development especially in the context of new learning models (i.e., designing new learning experiences, environments, and tools simultaneously). However, political and communication caution is warranted given the way other attempts to advance interoperability in the service of personalized learning ended abruptly amid privacy concerns. The politics of educational R&D are more challenging than technology.

Credentialing Systems

Based on trends in technology, credentialing, and school network development, next-generation credentialing — or diploma — systems are likely to develop using a common transcript interface, but this transition will take time.

 

For example, transcript alternatives, including but not limited to Mastery Transcript, could serve as a common user interface between high schools and post-secondary institutions. This could eventually serve as an interface between learners and a landscape of providers. Such a platform would likely eventually use blockchain technology to securely capture and transfer credentials and evidence in common formats, but it will still rely on local or network judgments of mastery. Initially, these judgments will be made by individual independent schools; but as public schools join the consortium, many are likely to participate in regions or networks.

 

The development of new credentialing systems will likely begin with states, regions, and networks developing common graduation requirements that combine credentials and, in some cases, required or recommended experiences. As illustrated below, such networks would need a transcript interface that is aligned with a competency-based diploma and that will provide proper signaling for post-secondary and employer needs. The IB Diploma Programme is an example of a curriculum and exam system used globally. The New York Performance Standards Consortium is a local group of high schools that use performance assessments as an alternative to state tests.

 

Summit Public Schools is investigating a common diploma system for its managed schools and the 330 schools using the Summit Learning platform. New Tech Network and League of Innovative Schools (and XQ) could do the same. A group of international schools is interested in an Innovation Diploma, that combines required experiences and micro-credentials.

 

Within a single-diploma system, groups of affiliated schools could share a common competency model and assessment systems and will affiliate with a diploma system. For example, while aiming at New Hampshire’s proficiency-based diploma, several different groups of schools could emerge from the PACE pilot program.

EXAMPLES OF POTENTIAL DIPLOMA NETWORKS

For the purpose of illustration, this table shows existing networks that would have the potential to evolve into a set of diploma networks. This is intended to project a potential concept, not to show what exists today.

New Hampshire Proficiency-Based Diploma

Existing regional network, diploma in practice

PACE Network 1

PACE Network 2

Summit Public Schools Diploma

Existing network, diploma in development

Summit Public Schools

Summit Learning Schools in RI

International Baccalaureate Diploma Programme

Existing international network, diploma in practice

Individual United States Schools

Individual International Schools

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Path Forward on Blockchain Transcripts

Neither of the national standards groups, IMS Global Learning Consortium (IMS) and Ed-Fi Alliance, has a plan for blockchain, but both are eager to incorporate it into their strategy roadmap. IMS has been an engaged leader in digital micro-credentials, having developed the Open Badges standard and the more recent digital transcript (IMS Extended Transcript) that was developed as part of the AACRAO comprehensive student record program with the National Association of Secondary School Principals in 2016.

 

IMS is pursuing demonstration projects that will create functioning examples of employer-educator-learner ecosystems where the learner has access to (and the ability to manage) their personal achievements (badges, transcripts, etc.) in a skills marketplace. An early example is a demonstration project with the University of Wisconsin Extension and employer recruiting platform Portfolium. More demonstration programs will require financial and technical support to build the sample infrastructure.

 

The JRC report urges the development of open standards for educational records and continued community conversations about the advantages of blockchain technology.

IMPACT OPPORTUNITIES

TECHNOLOGY DEVELOPMENTS:

Establish interoperability and blockchain standards.

Standards groups ought to continue to work together to form combined data standards (like IMS Global and Ed-Fi Alliance) and open blockchain standards.

Further interoperability design.

The current inability to combine formative assessment data is a technical, psychometric, political, and business model problem. The field would benefit from creative approaches to solving complex multi-dimensional problems). This includes encouraging districts and networks to exert pressure on vendors to release item-level data (requiring a business model change) to improve interoperability.

Continue to grow high-quality formative assessment practice.

Districts or networks that are strong in formative assessment practice ought to be leveraged. This could include improvement of content and assessment tagging to facilitate combined formative insights and mastery judgments.

Design and pilot learner profiles that emphasize CBE and include out-of-school learning experiences.

Every student ought to have access to his/her data through a competency-based transcript, personalized learning information (supplemental achievement data, record of services, extracurriculars, etc.), and a portfolio of verified work experiences, community service, and job shadowing.

Support development of updated transcripts.

Support transcript platform development that is accessible to all schools, leverage technology, and represent competencies.