Bring in the Translators and Decoders: The Language of Credentialing Needs Help – Part Three

• Melissa Goldberg, Director—Competencies & Credentials, Corporation for a Skilled Workforce
• Naomi Boyer, Education Design Lab, Executive Director of Digital Transformation
• Sarah DeMark, Vice Provost, Workforce Intelligence & Credential Integrity, Western Governors University
• Amber Garrison Duncan, Executive Vice President, C-BEN (Competency-Based Education Network)
•  Nan Travers, Director, Center for Leadership in Credentialing Learning, SUNY Empire State College; PI and co-lead, Credential As You Go

Credential As You Go (CAYG) sponsored the virtual Summit on Language Used in the Credentialing Space: Big Concepts, Many Terms, Multiple Perspectives, Different Voices on March 16, 2022. The Summit focused on three troublesome areas of language use: credentials and pathways; equity, inclusion, fairness; and competencies, skills, learning Outcomes. The first three parts of this four-part series focus on these three areas, part four on key takeaways. 

The Competencies, Skills, and Learning Outcomes discussion was moderated by Melissa Goldberg (Corporation for a Skilled Workforce) with a panel comprised of Naomi Boyer (Education Design Lab), Sarah DeMark (Western Governors University), Amber Garrison Duncan (Competency-Based Education Network and Nan Travers (SUNY Empire State College). The panel addressed the following question:

What do these terms mean, and how do we use them? Some are increasingly used interchangeably. That causes confusion across different stakeholders, especially students, employers, credential providers, accreditors, policymakers and educational researchers. We will explore the nuances behind these terms and contextual implications.

Naomi Boyer noted that there are tons of definitions, and the meanings are not always the same. In our organizations, we see competencies described differently than skills described differently than sub-competencies. This complicated network we have woven together makes it difficult for us to agree on definitions. It is ok to have our own, but at some point, we must agree. So, when we are having this dialogue, everyone knows what everyone means. Work competencies traditionally incorporate knowledge, skills, dispositions and abilities (and more), but why do we only hear about skills in mainstream conversation referencing the skills economy or skills ecosystem? Conceptually, we mean ways of knowing and doing that are more comprehensive than tactical skills. Often, when we use mainstream terms like skills, we are talking about something a bit bigger, which would be encompassed under competencies.

The nomenclature that frames skills vs. competencies is foundational; however, the vocabulary becomes even more complex when we add related terms like micro-credentialing and badging. Assembling the various terms together into a holistic meaning can be difficult, as many terms are used synonymously. But competency, skills and learning are distinct. When we unpack them, they are inherently different. We need to make sure we contextualize our conversations with colleagues when describing and sharing this important work. An example is the word frameworks. Many of us think about competency frameworks when we hear frameworks, but everyone likely has their own idea of what that means—and they are not all the same. Indicating “in this particular conversation” to an audience contextualizes my comments and helps everyone engage from the same vantage point. We need more clarity in our conversations. And we need multiple stakeholder groups to engage in a dialogue on transparency and intentionality when it comes to defining these terms.

There is also growing need for data to establish outcomes and understand whether we are truly meeting our goals. This is not easy work, particularly because many of these credentials are alternatives to traditional delivery models, and that means we usually do not have the learner data to guide them toward impact and outcomes. Also, we need to start thinking differently about how to measure those outcomes, whether they are offered on the non-credit or the credit side of valuable learning experiences.

Sarah DeMark described Western Governors University’s work to ensure every credential offered is aligned to the skills employers demand to meet workforce needs. WGU has done a lot of work with labor market data groups like EMSI and Burning Glass to come up with a list of skills. Then we identified the high-level skills, for example, communication skills. Are we talking about communicating technical concepts to technical peers and/or talking about taking technical concepts and explaining them to non-technical peers? We recognized that to make skills meaningful and impactful, they needed to dive deeper and contextualize them. So, WGU started this work with the idea that getting everybody to speak the same language when talking about skills meant we could start to connect the dots between all of these skills-based education and hiring systems. The work of the Open Skills Network is to create that open standard to communicate skills—contextualized skills statements that can then be tagged to all the different frameworks, licensure and accreditation requirements, whatever’s out there. Then we can start to tag these components together.

We’re starting to use these rich skills descriptors, which are part of that Open Skill Standard, to specify meanings and build competencies on top. We view those rich skills descriptors as atomic units of value on competencies that can be matched. This is powerful: We’re creating linkages from employers through the language of skills and back up to competencies, and then showing how those align with credentials or achievements of value and so forth.

Bringing in the employer voice as we seek transparency in our use of language is important as well. If we talk about skills in a way that really facilitates translation between education providers and employers, it helps learners. Learners do not always understand the skills they have, their value and how to talk about them. So, as we are trying to create some sort of standardization in this chaos, transparency is key, but it must enable us to connect the dots to enable an individual to make good decisions about their education and communicate its value clearly.

Amber Garrison Duncan underscored an important coming-together around the theme of skills-to-competencies. The Competency-based Education Network (C-BEN) is helping institutions understand how to take the kind of market signals WGU is identifying to impact credentialing — taking what employers say they need from workers and turning into a flexible curriculum designed to serve today’s learners, providing a more equitable outcome and ensuring every learner attains mastery and succeeds after completing their credential program.

She described working with a group of institutions who had taken a National Restaurant Association Foundation competency framework to externally reference their programs with employer work, noting that you could see confusion emerge between the skill statement and competency statement. In practice, we are starting to see all this merging, which is an important, distinguishing moment. We have to help institutions understand what a skills signal is and how to translate it into a competency and design the appropriate curriculum to deliver it. And then, how to assess that in a contextual way, pushing on all our institutions to think about applied assessment that incorporates that context because that is what employers are looking for at the end of the day. These changes require a deep connection with employers.

Institutions are faced with determining whether learning is a skill or a competency. That is the work we are seeing when institutions try to meet employers and provide more equitable academic models. It is challenging and confusing. We also have learning outcomes linked to accreditation adding to the confusion for faculty especially.

We are all calling for more transparency and explicitness in our use of language. In that explicitness, we need to think critically about who we are including to help us make these definitions and how we are including communities that have traditionally been excluded to help us land in the right place.

Nan Travers noted that it has been more than 20 years since we started this big push around transparency, the kinds of knowledge we are calling for in credentials, and the competency and skills movements. But somehow the terms are equated as being different or of different values. For example, what if a skill was worth a penny and it takes 25 pennies to get a competency? Then it takes 24 competencies to get a learning outcome? Some people will ask whether we are saying that a penny is worth so much less than a quarter, but aren’t 100 pennies equal to a dollar? We get to this language of less/better than, and language itself can create a power differential. 

The power dynamic here—and something to be careful about—is that language can become elitist as soon as you start breaking a learning outcome into work-related competencies or skills (careerism) because that does not belong with academics in some faculty member’s views. When we talk about what people know and can do, we should also be talking about integrating the learning, regardless of the environment in which the learning is gained. The only things that matter are what people know and can do. We must work on this because we are creating inequities, just in the way we are talking about learning. We do not build language around source and people. As we work with faculty to evaluate workplace learning and determine how to integrate it into academic programming, we need to have these conversations about what a college-level education means. We must stop thinking about it in terms of this big differential, rather getting at the core what it is about and starting to equalize to recognize more of what people know and making sure they have the credentials to get the employment they want.

Key Takeaways

• There is no one right answer but establishing common vocabulary will help us move forward in organizing the emerging skills ecosystem. Key terms, data schema and skills details become important in furthering this work.
• Because many of these credentials are alternatives to traditional delivery models, we usually do not have the learner data to record impacts and outcomes. And it is difficult to measure outcomes for credentials offered on the non-credit side for valuable learning experiences.
• Key work is needed to create deep connections between employers and credential providers: using the language of skills identified by employers, then linking to competencies provided in the credential provider’s curricula and showing how those align to credentials or achievements of value.
• Institutions must understand how to take what employers are saying they need someone to know and be able to do and turn it into a flexible curriculum designed to serve today’s learners to provide a more equitable outcome and ensure every learner reaches mastery and succeeds after completing their credential program.
• Higher education institutions will need to think about applied assessment of learning because that is what employers are looking for.   
• It has been more than 20 years since we started the push around transparency, the kinds of knowledge being called for in credentials, and the competency and skills movement. Some terms are now being equated as different and/or of different value. The result is the inference less/better than language—and language itself can create a power differential.    
• Learning outcomes language can become elitist when we break a learning outcome into work-related competencies or skills because some faculty view that as careerism and do not believe that belongs with academics. We must work toward integrating learning. 

The discussion on the challenges of language use in credentialing will continue in Part four’s focus on final takeaways.