More Than a Digital Transcript: Social and Organizational Implications of LERs

A recent publication in Issues in Science and Technology-co-authored by Workcred’s Isabel Cardenas-Navia and New America’s Shalin Jyotishi-explores Learning and Employment Records (LERs), digital records detailing a person’s education, training, and work experience that are verified through a distributed system similar to blockchain. The article, “Everything You’ve Ever Learned,” explores how LERs offer a promising solution to the challenge of capturing and communicating the skills of individual workers to a wide selection of potential employers. LERs may also equip employers with the tools necessary to maximize hiring, promotion, and upskilling.

The publication also explores the need for LERs to be carefully designed to achieve more equitable, socially desirable outcomes, rather than intensifying existing inequities or disproportionately benefitting one group over another.

Very simply, LERs are another new technology with the tremendous potential to benefit individuals and organizations, but whose ultimate impact will be shaped by the human-technology partnership that is developed. Below, you can read an example of how adoption of LERs could unintentionally exacerbate inequity, as well as three recommendations to mitigate this potential.

Example of LER Human-Technology Partnership Gone Wrong:

Differential Adoption of LERs by Post-secondary and Secondary Educational Providers

One example of how LERs could inadvertently exacerbate existing inequities is through differential adoption by different user groups, either at the individual level or organizational level.

Currently, several colleges and universities are participating in LER pilots. Participation in these pilots takes resources, typically paid for by the participating institution. Among other items, these resources include administration, faculty, and staff time; investments in technical infrastructure to support LERs; and investments to educate students, faculty, and employers about LERs. These requirements make it more likely that well-resourced higher education institutions will be early adopters of LERs.

Secondary institutions can also participate in LER pilots. They require many of the same resources as higher education institutions and may face some additional resource needs as they serve younger learners. Like higher education institutions, there is variability in access to funding for different secondary institutions. Thus far, fewer secondary institutions seem to be participating in LER pilot projects when compared to the number of higher education institutions.

There are already multiple benefits stemming to individuals who have earned college degrees: wage premiums, lower unemployment, and more job opportunities since many job postings require a degree to qualify for the position. If colleges and universities are early adopters of LERs, then their alumni may disproportionally benefit from this early adoption. Graduates from these institutions will have verified skills in addition to their degrees, whereas those without college degrees may not yet have access to the use of LERs to verify their skills.

As it currently stands, the use of LERs in employment decisions would create a larger perceived difference between those with a degree and those without because of greater access to LERs for some postsecondary credential holders. Even if individuals with no post-secondary credential created an LER, if their secondary institution or non-degree credential provider does not participate in LERs, they will need to find a way to capture their skills, likely at their own expense.

Recommendations

While these potential concerns should not stop the development and implementation of LERs, there is a strong need to proactively mitigate these concerns. Three recommendations are offered below, and additional recommendations are welcomed.

Recommendation 1: Develop a Metrics Framework to Support Equity

Alongside the development of the LER pilots, there is a need for a proactive approach to develop a framework to examine the impacts of LERs on users, both organizational and individual. This framework should include a process for regularly collecting metrics to examine inequities in access to and use of LERs.

Once developed, groups like the U.S. Chamber of Commerce Foundation’s T3 Innovation Network (T3) effort on LERs could encourage their communities to adopt the framework and publicly report on metrics. The T3 LER community would be an excellent forum where pilot projects could share their results and support each other to develop best practices to support equitable implementation of LERs.

Metrics would also provide employers the ability to make informed decisions about the role LERs should play in employment, promotion, or training decisions. Particularly as employers recommit to a diverse workforce, there is a need to understand how LERs can support those goals.

Recommendation 2: Additional Investment Focused on Supporting Equity in LERs

While there has been significant, much needed funding that has gone into the development of LER infrastructure and pilot projects, there is a need for additional investment focused on supporting the equitable development and use of LERs. Some of this funding should support LER pilot projects to collect and analyze metrics related to access and equity and to develop processes to mitigate inequities and improve access. This funding should require the data collected to be publicly shared, which will keep the equitable use of LERs central to the development of these pilot projects.

There should also be a dedicated effort to understand how LERs will alter the education and workforce system. This research is inherently multi-disciplinary, involving psychology, sociology, anthropology, economics, technology, and systems. Like the adoption and use of any new technology, LERs will have impacts on the organizations and individuals who use them. They are likely to change actions and behaviors of workers, credentialing organizations, employers, and other stakeholders. Additionally, while no financial model has yet been determined for LERs, one (or more) models will certainly be developed and impact LER use and access. The results of this research can help inform policymakers how they can best support LER development to benefit society.

Recommendation 3: Expand the Types of Organizations Involved with LERs

There should also be investment in new LER pilot projects to bring in credential providers who are not currently participating. For example, many credentials are given by certification bodies, for-profit and non-profit training providers, and industry associations, all of which are underrepresented in current pilot programs. Many learners seek out credentials from these types of providers, and interest in non-degree credentials is growing.

Furthermore, there should be additional engagement in LERs from employers in sectors such as manufacturing, whose workforce is highly skilled but not highly credentialed. LER pilots in these sectors are more likely to directly address how to capture non-credentialed training and work experience.

More broadly, there should be an investment in the development of processes and tools for individuals and organizations to participate in LERs and LER pilots. This will ensure greater participation in pilots from community colleges, secondary institutions, small businesses, credential providers, and workers. These organizations and groups are critical to the equitable use and implementation of LERs and should be actively supported to get involved.

That these are not the only recommendations to guide the equitable access to LERs, but these would be an integral part of the solution. See more about this work in Workcred’s article in Issues in Science and Technology, “ Everything You’ve Ever Learned.”

Originally published at https://blog.ansi.org on August 18, 2021.