fundamentally change how we connect talent to opportunities

And more importantly, what could it do for workers, education providers, employers, and our communities?

Certain types of learning (like degrees from well-known institutions) continue to be valued over others, even when they might not be the best indicator of job readiness

legacy systems move too slowly, lack the intelligence needed for smart decision-making, and fail to capture the full range of skills and experiences people bring to the table.

iQ4willgenerateandpostadigitalcredentialinthehighschoolstudents'WalletforcompletedCareerandTechnicalEducation(CTE)programsusingtheDigitalCredentialConsortium (DCC)trusted,distributed,andsharedinfrastructureandthe1EdTechOB3wrapperthatprovidescredentialverification,makingiteasierforemployers,educators,andprofessionalstoverifycredential

Institutions increasingly turn to digital credentials to reshape their recruitment and admissions processes. Universities like Georgia Tech, the University of California, Berkeley, and Syracuse already use digital credentials to assess applicants holistically. By incorporating digital badges, microcredentials, and LERs, institutions can create richer, more accurate student profiles that go beyond traditional metrics like standardized test scores and GPA

employer verification

For nearly half of the lower-wage employment analyzed, we identify at least one higher-paying occupation requiring similar skills in the same metro area. We also find that transitions to similar higher-paying occupations would represent an average annual increase in wages of nearly $15,000, or 49 percent.

Better understanding of what learning described by credentials prepares earners to do in theworkforce, at the skill level. This may be a reframing of competencies toward position descriptionlanguage

Increasingly, our partners are interested in building collections - or connecting to - credentials that they don’t own, issue, or offer to show learners the full pathways of learning opportunities that they can pursue.

One participant noted that local credentials,that is, from local colleges, were more highly valued because they almost certainly had examples ofhires with the same credentials

Resume parsers will now have better and slightly more detailed credential information to pass onto client systems—confirmation of a credential with a standardized name and associated skills

while there was certainly discussion with workshopparticipants about more specific changes to their hiring tools, thefundamental issue at the root of each major challenge was inadequateinformation about candidates

wants more consistent/trustworthy data

major HRIS system providers, from offering a full stack of proprietarysolutions to adopting a platform model that supports integrations with a range of third-party services

On the otherhand, there are legitimate concerns about how well resumes may be translated into structureddata via parsing.

This is consistent with what their peers report generally: one study suggests that almosthalf of companies do not know how to gauge a candidate’s skills based on a non-degree credential.12

The top four HR platforms according to Forbes13 all have marketplaces showcasing 300+ partnerintegrations. These platforms’ integration capabilities mean that established providers of traditionalbackground check services have a path to incorporate non-degree verification into their offerings

In addition to service providers, a new class of information consolidator, the Learning andEmployment Record (LER) wallet providers, may find benefit in joining the partner marketplaces. AnLER wallet is envisioned to be an application where credential holders can store their credentials ina safe, private way, giving the holder an ability to curate and share more comprehensive informationabout formal and informal education activity, along with other achievements. A key value of LERwallets is that credential information can only be stored in them if they have been verified by theissuer

At a minimum, we hope this discussion willencourage HR leaders to work with their HR technology providers to broaden access to the fieldsoffered by the parsing companies in system integrations

Parsing algorithms that translate unstructured resume data into a set of variables thatcorrespond to fields in an ATS or HRIS implementation are sometimes maintained in-house bythe HR technology companies. In a large number of cases, however, resume parsing is a serviceprovided by a handful of companies. These companies have all been in business for decadesand process incredible volumes of data on a daily basis. We estimate that, collectively, thesecompanies process ten million resumes a day or three billion resumes per year.

This kind of data could potentially enhance his understanding of what sources generateapplicants who work out best and what experiences correlate most highly with more successfulhiring outcomes

having better information can help Malik address the common queryfrom unsuccessful applicants about why they weren’t selected and allow him to proactively offerguidance on what they might seek to earn

helps him turn a pool of rejected applicantsinto a pipeline of potential future candidates that will let him achieve even better, more cost-effective efficiency

data does exist, but doesn’t yet flow through theecosystem in a consistent and high-quality way

stored data that he can analyze

more connected data,

Just as skills information can begin to flow from the curricular skills data source to the resumeparsers, a similar connection can be created between the curriculum data source and non-degreecredential data sources

For Jake, the high school graduate applying for jobs, the application process shifts away from being agame of how to pick the perfect keywords for his resume. Instead, he is matched by the actual skillsacquired in his recent community college coursework and EdX certificate. Both Jake and the hiringmanager he will soon meet have a more equitable and accurate path through the noise of today’sonline hiring process.

This interconnected ecosystem allows for improvements that HR leaderswould most like to see: better whole-person evaluation, better leverage of candidate skills, bettercredential verification, and more reliable information on what makes a good candidate

integrationswith the mission-focused LER wallet companies or the entrance of a few general-purpose walletproviders, such as ApplePay or GooglePay, into the hiring ecosystem. Both Apple and Google arealready experimenting with housing digital driver’s license information for a number of U.S. states, andexpansion into storing digital credential information may be a viable, incremental step for them

Examples of these sources would include an established digital walletprovider, or an exhaustive catalogue of digital credentials that are available, such as the repositoryhosted by Credential Engine. Having the curricular data source, which has a connection to the parsingcompanies, also create a connection to credential information opens up a connection, albeit anindirect one, between the non-degree credential information and the parsing activity. Instead ofreceiving just a course name from the resume parser, the intermediary can also receive a non-degreecredential identifier that is sent to the credential data source to look up and return skills information

One example of a curriculum data source is OpenSyllabus.org, a non-profit that hosts acomprehensive repository of higher ed course information. OpenSyllabus.org can serve as a value-added provider that sends skill information about specific college coursework to the parsers. This willexpand the potential skill information parsers can associate with a resume, going beyond what mightbe gleaned only from reading a course or degree title. They would now have access to informationderived from more detailed course catalog descriptions or even course syllabi information. Parserswill be able to send more extensive lists of skills over to companies’ HR platforms in a structuredformat they can immediately utilize. This integration also captures the skills from a particular type ofnon-degree credential - the coursework completed by the 40 million people in the U.S. who have somecollege, but no degree.

The lack of reliable and consistent information about non-degree credentials presented by candidatesin the hiring process also meant that workshop participants had no information to classify candidatespost-hire. This gap made it impossible to know who among the employee base had earned whichcredentials. Without this basic profile data, HR leaders are unable to gather much-needed insight intowhat types of credentials appear to prepare candidates best for a given role or which credentialsappear to be more effective at training than others

Due to the relative novelty of LER wallets, both applicant adoption and employer awareness remainlimited. This lack of familiarity has resulted in minimal client demand to integrate LER wallets intohiring workflow tools. Consequently, major HRIS platforms do not currently support APIs for data flowdirectly from LER wallets.

In contrast to the badge information screens in Figure 10, HR leaders expressed strong preferencefor the concise summaries on the mocked-up HRIS screen. They also appreciated keeping theinformation in the flow of work, thereby minimizing the need to consider yet another tool or interface

information about trainingcontent and skills was important, but only one aspect of how they determined if credentials wereof interest. They also wanted some understanding of the quality of the training. Some of the parsingcompanies have created scores that might help HR leaders understand credential quality, but theworkshop participants told us quite clearly that they didn’t like these kinds of scores. To them, scoringsystems felt very black box in nature and were generally not trusted.

Ideas for More Actionable InformationIn discussion with HR leaders helping imagine process improvement, we learned that the informationcurrently curated for digital badges was helpful, but perhaps not quite hitting the mark. Workshopparticipants told us two things about the kind of information found in Figure 9: it was overwhelming,and it missed key facts they wanted to know.In their view, the sum of information presented on badge websites is a bit dense and very focused onthe nature and content of the training

Briana aims to enhance efficiency by leveraging technology to better manage andverify credentials, potentially exploring solutions that simplify the integration of professional socialmedia profiles that have been linked to government-recognized credentials. Briana’s main concern,however, is that she is unclear whether the company developing the platform she uses to store HRinformation is committed to supporting these kinds of integrations

Stage Three: Expandingthe EcosystemLeverage new demand from end-usercompanies that have access to additionalinformation to justify more integrationsbetween data sources and HR tools

Once these connections are established,expand data flow to include the additionalinformation about non-degree credentialsdesired by HR leaders

Creating Internal Value.

Measuring What Matters

The question of how testing is currently being done, does not state a clear hypothesis, butis set to look at the collected data without being certain what that data will conceal.According to Saaranen-Kauppinen and Puusniekka (2009, 6-7) the lack of a clearhypothesis and data-driven research are factors to categorize this research as qualitative.Typical methods for gathering information in qualitative research are observations andinterviews, or at present the use of existing material and documents as well (Saaranen-Kauppinen & Puusniekka 2009, 47). An observative approach could yield deep insights inthe existing testing practices in an organization, but would restrict the data collection toone or two development processes due to the small scope of this research. Due to thelack of existing material of the organizations in question I chose to conduct interviewsinstead, as I expect to gather a good understanding of existing testing processes indifferent types of relevant organizations.

As employers continue to face hurdles in identifying and hiring qualified talent, the potential for skill- and competency-based digital credentials is likely to grow

Makes the case for why trusted skills assertions can be the future of better connecting talented humans with opportunities they deserve

Interoperable LERs support learners’mobility by functioning in local, regional,state, national, and global talentmarketplaces

Interoperability: The ability of systems to worktogether, exchange, and make use of informationfrom other systems. In education, interoperability isthe ability of a system to exchange education andworkforce information with and use information fromother systems without special effort on the part of theuser. This means all individuals, including learners andemployers, have appropriate access to educationand workforce information, allowing them to makeinformed decisions in the workplace

“Our relationship with Community College of Aurora exemplifies the best in finding workforce solutions. Together we dug into the details to develop curriculum and training experiences that prepare students to meet the requirements for specific job responsibilities in behavioral health.”

only about a third of the need for mental health professionals in Colorado is currently met, driving demand for additional qualified behavioral health workers. By offering microcredential pathways in patient navigation, peer support specialist, behavioral health associate, and behavioral health+, these new credentials are designed to address Colorado’s mental health workforce shortage by preparing people for these roles in less than one year

whether built as credit-bearing or non-credit pathways, microcredentials are by no means a substitute for the intensiveness or comprehensiveness of traditional higher education pathways.

Credential Engine Learning and Employment RecordsAction Guide

They also need to communicate their potential, i.e., what they are able to learn, as well as toreceive guidance on how to realize their potential

employers see potential value in using digital credentials for a number of differentreasons. These include using digital credentials to better match candidates to jobs by analyzingtheir skills, broadening the talent funnel by data-mining credential databases, ensuring theauthenticity of credentials, and using credentials to manage the talent pathways in theirorganizations

OER-enabled pedagogy

The Day of Happiness