The U.S. Department of Education says these integrated, next-generation strategies should feature a credential registry, learning and employment records (LERs), and a skills-based job description generator.
FIPSE grants required these. LER is part of what's required.
Yet most credentials fail to adequately capture the skills and knowledge of students who earn them, keeping employers in the dark and closing doors for jobseekers without four-year degrees
What's inside? What is the credential credentialing?
Digital badges can be stacked together to replace or supplement formal and informal learning experiences and be understood by learners, higher education, and the workforce
"understood" => I like this framing of centering that a purpose of all of this is to make sure that the learning can be understood (and thereby valued) by the audiences who need to understand it. In order for credentials to have currency, the brokers of currency need to know what the assets are and how to value them.
Micro-Credentials and Digital Badges: An Exploration of Definitions and Implications in Higher Education and Workforce
fundamentally change how we connect talent to opportunities
This is a narrative few are hearing and fewer are promoting: a huge benefit of the ecosystem vision is about connecting people and opportunities
And more importantly, what could it do for workers, education providers, employers, and our communities?
LER Ecosystem
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
Given STRADA's Talent Disrupted findings, "might not be the best indicator" might be a generous way of putting it.
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.
The WHY
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
More effective, efficient, and equitable admissions
employer verification
In addition, this hints at employMENT verification: this could be a light lift sort of Tier 1 entry point for organizations to be both issuing and consuming credentials. Large employers spend a lot of resources responding to requests to verify former workers' employment histories. If part of off-boarding departing workers includes VCs for official employment verification, that could lead to big savings of time and resources (as long as other employers accept the credentials), as well as accelerate hiring processes that sometimes lead to failed hires bc people find another position that starts sooner. For key HR leaders to start with badging from a place of effortlessly improving their efficiency and costs might be a better place to launch than more involved strategies that offer less immediate value propositions.
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.
Recognition can change the world. Signals need to be valid and trustworthy, but we're so close to making a huge difference in the world through recognition of things that are already there, just hidden in plain sight.
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
Employers want to know what credentials are credentialing, and they want to hear it in their own language. The temptation will be to convince faculty and others to revise descriptions, however the opportunity is in leaving that and instead seeking their consensus and comfort with interpreting their descriptions into the languages of employers.
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.
Example of how this gets operationalized: There will be platforms (think Naviance on big data and personalized data steroids) that will help Learners discover right fit opportunities based in part on the credentials they already have. There will be savvy institutions connecting to others' credentials so as to increase the likelihood that Learners discover those institutions' program offerings. This will be akin to a sort of skill-based SEO approach as a recruitment/admissions strategy.
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.
Simple, elegant explanation: it moves from clumsy proxies that screen out qualified people like Jake, to powerful and sophisticated matching that connect opportunities to people like Jake who have the verified skills to deserve those opportunities.
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
The value proposition, as presented here, is all about the wheel being more efficient, more effective, and less expensive in identifying, hiring, and retaining cogs. What might be magical is the rare nexus of what being best for the wheel also being good for the cogs, us humans who this work is hopefully really about.
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
Might some see this as a call to pay close attention, get involved, and push for public/public good solutions? Or will we default to leaning on FAANG to provide our "free" wallets and control or even own more of our data?
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
Opportunity to go deep here. Bread crumb is to check out the issuer directory with Credential Engine, where they are inviting institutions to publish details about their credentials in a standardized format (CTDL) that will hopefully one day be consumed by connections like those hinted at here.
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.
This might catch the attention of HE people paying attention. It also hopefully connects to the participants who shared that they are not getting the information about the programs that they desire. If the data being consumed (by this vendor or others) is still rooted in describing the content of the learning and not the measurable, assessed outcomes, then it's utility is limited and, crucially, it could create trust issues that make consumer wary of all the data. On the other hand, if they can trust the high quality data, there will be a window of competitive advantage for HE institutions that choose to share the data that the consumers (largely employers) want to see.
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
This could play into Credential Quality Assurance work in Higher Ed.
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.
KEY FINDING. This is one of the most important takeaways of the report, especially in regard to LERs. It's also important to note the lack of familiarity when considering other survey data about innovative credentials: if participants have limited understanding of the stuff they are being asked about, how much should we read into the data about their (possibly inaccurate) perceptions?
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
TWO THINGS: 1. The shiny interface is for humans, not machines. Are the participants assuming that they are looking at the interface for all of the candidates or just the top candidates? 2. If participants know that they are only seeing an interface like Figure 10 for top candidates, would they still desire something more concise or would the narrative be right-sized?
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.
Consumers want quality. They also are wary of quality assessment. Trend currently appears to align with historical defaults of using proxies instead of precise, targeted measurements (eg Using length of seat time and GPA instead of competency-based assessments)
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
KEY FINDING: it's a problem if the context focuses on the nature of the content instead of the nature of what the credential is credentialing.
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
For these ecosystems to be healthy, the interconnected nodes. function in harmony. They are aware of the other nodes' desires and intentionally seek to meet those needs. A barrier to progress is technology solutions that can function to meet important needs yet do not. (Positive assumption here that the developers either don't properly understand their users' needs or don't properly understand how to capture ROI if they do design to meet those needs; not that they know the needs and choose not to address them)
Stage Three: Expandingthe EcosystemLeverage new demand from end-usercompanies that have access to additionalinformation to justify more integrationsbetween data sources and HR tools
Ecosystem expansion might rely on market incentives for additional parties to connect, synthesize, and operationalize data. Important to consider that this is not limited to HR vendors; it's also about their clients, as well as other vendors that may be better enabled to connect with (L)earners to market Navigation services, coaching, scholarship and lending programs, educational/training/upskilling opportunities, and more. In a future of direct admissions, there are multiple roles in this ecosystem. And, of course, there is much opportunity and value for the human (L)earners at the center of the ecosystem.
Once these connections are established,expand data flow to include the additionalinformation about non-degree credentialsdesired by HR leaders
KEY: data is what the Consumers desire, not necessarily what the learning providers want to describe.
O Direito de Ler em Voz Alta
Na minha opinião, ler em voz alta é muito importante, porque podemos “saborear” as palavras de uma forma diferente do que se estivéssemos a ler “para dentro”.
Creating Internal Value.
LERs will give employers internal heat maps of talent
Measuring What Matters
THIS! Been declaring for ten years how this is all about measuring the stuff that people actually care about.
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.
LER NOVAMENTE: Explicação de pq usar e( o que é pesquisa qualitativa), para responde a 3 sub-questão
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
This "WHY" for industry is well stated. Employers are highly motivated.
Makes the case for why trusted skills assertions can be the future of better connecting talented humans with opportunities they deserve
SHRM research
Interoperable LERs support learners’mobility by functioning in local, regional,state, national, and global talentmarketplaces
MOBILITY
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
Interoperability is rooted in access and equity
“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.”
co-design with the employers who will consume credentials
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
Market need + Short prep time for learners = meeting needs of job seekers and employers.
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.
Yes! It's a false dichotomy to pit MCs vs traditional credentials. They are different and can be complimentary.
Credential Engine Learning and Employment RecordsAction Guide
14 page playbook on LERs
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
Fascinating idea of systems not only serving to inform learners/earners about where they can go and how to get there, but to also be a reliable signal about their potential to advisors, councilors, social workers, navigators, parents, recruiters and others
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
reminder that stakeholders are not monolithic and neither is any given stakeholder's incentive structure. Yes, keep it simple when mapping out stakeholder ecosystem. And, include multiple incentives when relevant.
OER-enabled pedagogy
First use of "OER-enabled pedgogy" outside of David Wiley's blog?
The Day of Happiness
A masterful way to help shape the conversation.