CTDL Benchmark Models

CTDL Benchmark Models

Last Updated on 11/9/2020
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Introduction: Comprehensive information for understanding and making decisions about credentials is important for students and workers, employers, educators, government agencies, policymakers, and other stakeholders. In order to ensure we are gathering and enabling the use of relevant, clear, and quality data, Credential Engine has a Minimum Data Policy for the Credential Registry. The minimum data policy is based on the Credential Transparency Description Language (CTDL) and is the necessary baseline to establish credential transparency. However, the policy also identifies Recommended Benchmarks as models to include more comprehensive data that includes information valuable to different consumers, providers, employers, and agencies. Organizations offering credentials, education and career pathways, quality assurance, transfer value recommendations, and other information described by the CTDL are encouraged to include as much of this information as possible when publishing to the Registry. The recommended benchmarks allow for the creation and permanence of a more robust data network that offers valuable and trusted credential information to fuel the creation of services, tools, and opportunity.

Additional Information: These benchmark models are organized by credential type to accommodate the differences in both structure and data points for each credential type. Though not all credentials will fit perfectly into these boxes, these benchmark models serve as a guideline for the amount of information that can help describe your Certificates and Licenses.

Based on the definitions for Certification and occupational License, the following terms to describe credential renewal and revocation include: renewal, renewal frequency, renewed by, revocation, revocation process, and revocated by.

Credential Engine has also expanded the Credential Transparency Description Language (CTDL) to include data points for Pathways, Transfer Value, and Education and Training to Jobs Skills. We encourage you to publish and connect these data to information about your credentials, as well, to widen the impact and benefit of your contributions.

Additional Information: These benchmark models are organized by credential type to accommodate the differences in both structure and data points for each credential type. Though not all credentials will fit perfectly into these boxes, these benchmark models serve as a guideline for the amount of information that can help describe your Degrees and Certificates. Credential Engine has also expanded the Credential Transparency Description Language (CTDL) to include data points for Pathways, Transfer Value, and Education and Training to Jobs Skills. We encourage you to publish and connect these data to information about your credentials, as well, to widen the impact and benefit of your contributions.

Additional Information: These benchmark models are organized by credential type to accommodate the differences in both structure and data points for each credential type. Though not all credentials will fit perfectly into these boxes, these benchmark models serve as a guideline for the amount of information that can help describe your Apprenticeships. Credential Engine has also expanded the Credential Transparency Description Language (CTDL) to include data points for Pathways, Transfer Value, and Education and Training to Jobs Skills. We encourage you to publish and connect these data to information about your credentials, as well, to widen the impact and benefit of your contributions.

Additional Information: Only use the following benchmark model if you are publishing a digital badge that is a standalone credential. If you are publishing a credential that also has a digital badge associated with it, then please use the benchmark for that specific credential type.

These benchmark models are organized by credential type to accommodate the differences in both structure and data points for each credential type. Though not all credentials will fit perfectly into these boxes, these benchmark models serve as a guideline for the amount of information that can help describe your Badges. Credential Engine has also expanded the Credential Transparency Description Language (CTDL) to include data points for Pathways, Transfer Value, and Education and Training to Jobs Skills. We encourage you to publish and connect these data to information about your credentials, as well, to widen the impact and benefit of your contributions.

Additional Information: Education and Career Pathways are the starting points, available routes, and reachable destinations available to students and workers. People seek quality credentials as a means to achieve their education and career goals, but they often lack the necessary information to make use of their opportunities. This benchmark model helps individuals understand the routes, components and destinations such as credentials and training requirements for different jobs, how various credentials and skills translate to access and advancement in the workforce, and how different work and reskilling experiences can help with lifelong employability. Credential Engine recommends publishing these Pathways benchmark data (as applicable) into the Registry using the Credential Transparency Description Language (CTDL) to create a valuable linked open data network that reliably maps the credential landscape.

Pathway Components should be selected and used based on each pathways unique characteristics. This benchmark model is a draft and open for feedback via info@credentialengine.org.

Pathway Set

Benchmark

There are no Benchmark properties for this class. Please use the Required properties.

Pathway

Pathway Component

Additional Information: Transfer Value benchmarks help individuals, employers, providers, and other stakeholders better understand how different credentials and competencies relate to other opportunities. People seek quality credentials and specific competencies as a means to achieve their education and career goals, but they often lack the necessary information to understand the value of these opportunities in relation to their larger education and employment goals. The information recommended by this benchmark model can also help employers understand how to expand their talent pool. Credential Engine recommends publishing these Transfer Value benchmark data into the Registry using the Credential Transparency Description Language (CTDL) to create a valuable linked open data network that reliably maps the credential landscape.

This benchmark model is a draft and open for feedback via info@credentialengine.org.

Transfer Value Profile

Transfer Value Profile describes the nature of the transfer value along with references to the source(s) and/or recipient(s) of that value.

Value Profile

Value Profile describes the specifics (such as type and amount) of the credit associated with the transfer value.

Required

There are no Required properties for this class. Please use the Benchmark properties.

Benchmark

Pending Policy
Pending Policy
Pending Policy
Pending Policy

National Quality Credential Frameworks

Better data is essential to making better decisions about the quality of credentials. National organizations including the Educational Quality Outcome Standards Board (EQOS), Educational Strategy Group, and National Skills Coalition are providing important guidance to state governments and other organizations responsible for identifying credentials that meet quality standards. Credentialing organizations - credential providers, quality assurance bodies, assessment organizations, state labor market information agencies, and others - can publish credential, competency, pathway, outcome, and other essential information relevant to quality determination so that it is publicly available.

To help government and credentialing organizations make quality information about credentials publicly available, use the Benchmark Models. Select any of these national frameworks to see the relevant CTDL terms to be included when publishing credential data. This will ensure greater transparency to help everyone better understand their quality and value.

The overlapping themes between these frameworks as they relate to the CTDL include:

  • Identify the jobs credentials prepare for those jobs that are in demand and new jobs forecasted to be on the horizon.
  • Provide outcome data to show employment, earning, and completion to show the credential led to a good job in the related field.
  • Identify the processes and quality standards followed in developing the credential. This includes how input was considered from employers.
  • Show the skills and competencies that people will demonstrate because of completing the credential.
  • Define how credentials prepare for or are prerequisites for other credentials.
  • Create education and career pathways to help people achieve their goals.
  • Issue credits for non-degree credentials.
  • Incentivize programs to provide quality credentials and to help students afford them.
Select a Quality Assurance framework to view its contents.

Select a Quality Assurance Framework.

Introduction to Educational Quality Outcome Standards

The Educational Quality Outcome Standards (EQOS) standards are intended to be applied broadly to higher education providers, including accredited and unaccredited institutions. As they are meant to measure and validate only the outcomes that a program claims, these standards are intentionally agnostic to institutional mission, structure, and other elements that might vary in a review of traditional institutions of higher learning. These standards accordingly do not restrict participation to education or training providers based on any type of qualifications related to facilities, faculty, or other structural elements. The goal of an agnostic approach to a provider’s model or structure is for these standards to provide assurance about the value of enterprises with regards to their student outcomes.

While no system can perfectly capture every dimension of an education provider's or training program's quality, these standards will allow institutions to report outcomes relevant to the customers—the learners who pay to attend and the employers who hire them. To that end, the EQOS Quality Assurance Standards and related assessments capture near and medium-term outcomes according to the following metrics:

  1. Learning - Skills and competencies gained
  2. Completion - Number of enrolled students who finish the program while meeting learning standards
  3. Placement - Labor market position post program
  4. Earnings - Delta between pre- and post-program income
  5. Satisfaction - Student evaluation of the program

To learn more about this framework visit the EQOS website.

EQOS Framework: Learning

Acquiring knowledge and skills is perhaps the most important feature of any consideration of quality. Learning quantifies and categorizes the skills and competencies within a program and assesses whether graduates have met industry and/or self-identified benchmarks by the end of instruction.

The following CTDL terms identify the competencies/skills a credential or learning opportunity program teaches students.

Competency Framework
Competency Statement
Assessment Profile
EQOS Framework: Completion

Rates of completion provide a useful measure of how individual learners fare within a given program. This metric logs the rate at which enrolled students successfully finish their program.

The following CTDL terms identify credential and learning opportunity completion rates for programs.

General Term Recommendations

In addition to the classes listed in the sections below, the following terms are recommended for use in the various contexts in which they appear:

Quantitative Value

Required

There are no Required properties for this class. Please use the Benchmark properties.

EQOS Framework: Placement

Students often cite obtaining jobs, career advancement, or continuing higher education as key reasons for pursuing postsecondary education. Placement measures whether a program graduate has obtained a new job, advanced in title and/or salary with an existing employer, or generated a new or increased income through self-employment.

The following CTDL terms identify aggregate employment outcome data for a credential or learning opportunity program.

General Term Recommendations

In addition to the classes listed in the sections below, the following terms are recommended for use in the various contexts in which they appear:

Quantitative Value

Required

There are no Required properties for this class. Please use the Benchmark properties.

EQOS Framework: Earnings

Financial rewards and economic mobility provide key measures of value for students in postsecondary education. Earnings measure the average wage or salary of participants before and after their program.

The following CTDL terms identify aggregate earnings data for a credential or learning opportunity program.

General Term Recommendations

In addition to the classes listed in the sections below, the following terms are recommended for use in the various contexts in which they appear:

Quantitative Value

Required

There are no Required properties for this class. Please use the Benchmark properties.

EQOS Framework: Satisfaction

While harder to quantify, student satisfaction is an essential component of quality evaluation. Satisfaction assesses the program's success from the student's perspective through survey questions focused on instructor quality, program content, and level of support.

Currently the CTDL does not have terms for student satisfaction. During 2021, Credential Engine will explore including terms for aggregate student satisfaction. CTDL does not include personally identifiable information, only aggregate outcome related information.

Introduction to Educational Strategy Group

Across the country, the pathway to economic security and self-sufficiency looks far different than it once did. Significant economic shifts—spurred both by rapid technological advancement and the downturn of the Great Recession— have fundamentally altered the reality of education and work. Postsecondary education is now a requirement to access good jobs, and there are many more pathways learners can take to get there, including those that culminate in non-degree credentials.

The choices states make about which non-degree credentials “count” will either encourage learners down a meaningful career path or unwittingly steer them to pursue lower-value credentials that do not lead to good jobs. The Education Strategy Group (ESG) toolkit lays out an evidence-based methodology that K-12, postsecondary, and workforce development leaders in any state can use to approach this work with greater confidence. States and communities can use this step-by-step guide within the toolkit to help ensure that students earn high value credentials:

  1. Identify in-demand, high-skill, and high-wage occupations
  2. Create a list of priority non-degree credentials that correspond to the in-demand, high-skill, high wage occupations
  3. Validate the findings with employers and finalizing a statewide list of “priority” non-degree credentials
  4. Incentivize priority non-degree credential attainment through offering postsecondary credit, funding strategies for schools and colleges, articulated postsecondary credit for high school earners, and rigorous accountability systems
  5. Report and monitor priority non-degree credential attainment with reliable, verified data

To learn more about this toolkit, visit ESG Building Credential Currency.

ESG Building Credential Currency: Non-degree credentials that prepare for in-demand, high-skill, and high-wage occupations

Before classifying the value of non-degree credentials themselves, it is necessary to first identify your state’s high-wage, high-skill, in demand occupations in which these credentials exist and hold value.

The following CTDL terms identify the occupations a credential and learning opportunity prepare for along with aggregate labor market information such as employment and earnings. Include the competencies that are learned.

General Term Recommendations

In addition to the classes listed in the sections below, the following terms are recommended for use in the various contexts in which they appear:

Competency Framework
Competency Statement
Occupation
Quantitative Value

Required

There are no Required properties for this class. Please use the Benchmark properties.

ESG Building Credential Currency: Validate with employer input

Use qualitative methods like representative sampling and sector-based industry focus groups to validate the value of non-degree credentials with employers.

The following CTDL terms, in the context of Credentials and Learning Opportunities, can include information about the processes used to align to the competencies and skills required by employers.

General Term Recommendations

In addition to the classes listed in the sections below, the following terms are recommended for use in the various contexts in which they appear:

Process Profile

Required

There are no Required properties for this class. Please use the Benchmark properties.

Benchmark

There are no Benchmark properties for this class. Please use the Required properties.

ESG Building Credential Currency: Incentivize non-degree credential programs

Provide incentives and outreach to education and training providers and to students to help more learners earn non-degree credentials with labor market currency.

The following CTDL terms provide information about credits, cost and Identify the financial assistance available to students who may enroll in non-degree credential programs.

Cost Profile
Financial Assistance Profile
Value Profile

Required

There are no Required properties for this class. Please use the Benchmark properties.

Benchmark

Pending Policy
Pending Policy
Pending Policy
Pending Policy
ESG Building Credential Currency: Report on credential attainment

Collect comprehensive, validated data on non-degree credential attainment to understand which credentials are being earned and by whom. Store that information in the appropriate data systems. And create processes in accountability and reporting to clearly prioritize the non-degree credentials that are aligned to in-demand, high-skill, high-wage occupations

The following CTDL terms identify aggregate outcomes with credential and learning opportunities.

General Term Recommendations

In addition to the classes listed in the sections below, the following terms are recommended for use in the various contexts in which they appear:

Introduction to National Skills Coalition

National Skills Coalition (NSC) developed this framework to help states define quality for non-degree credentials. Non-degree credentials (NDCs), such as certificates, industry certifications, apprenticeship certificates, and occupational licenses are a key component of state credential attainment goals. NSC considered four types of non-degree credentials in developing a definition of quality: certificates, industry certifications, occupational licenses, and apprenticeship certificates. A quality non-degree credential is defined as one that provides individuals with the means to equitably achieve their informed employment and educational goals. There must be valid, reliable, and transparent evidence that the credential satisfies the criteria that constitute quality. Following a set of general principles, NSC encourages states to establish quality guidelines for non-degree credentials based on four criteria identified below. Each criteria is followed by a listing of CTDL terms that make credential quality information transparent:

  • Substantial job opportunities
  • Transparent evidence of the competencies mastered by credential holders
  • Evidence of the employment and earnings outcomes of individuals after obtaining the credential
  • Stackability to additional education or training

To learn more about this framework, read the NSC publication, Expanding Opportunities: Defining Quality Non-Degree Credentials for States (Sept. 23, 2019).

NSC Quality Non-Degree Credentials Framework: Substantial job opportunities

There must be evidence of substantial job opportunities associated with the credential. And the evidence must include quantitative data and direct communication with employers.

The following CTDL terms identify the occupations the credential prepares for such as the O*Net Standard Occupation Codes and aggregate job demand and growth data.

General Term Recommendations

In addition to the classes listed in the sections below, the following terms are recommended for use in the various contexts in which they appear:

Occupation
Quantitative Value

Required

There are no Required properties for this class. Please use the Benchmark properties.

NSC Quality Non-Degree Credentials Framework: Transparent evidence of the competencies mastered by credential holders

There must be transparent evidence of the competencies mastered by credential holders; competencies that align with expected job opportunities.

The following CTDL terms identify the competencies/skills a credential prepares for.

Competency Framework
Competency Statement
NSC Quality Non-Degree Credentials Framework: Evidence of the employment and earnings outcomes of individuals after obtaining the credential

Unless there is evidence of the employment and earnings outcomes associated with a credential, individuals and others are not in position to know if a credential provides the means to achieve their goal.

The following CTDL terms identify aggregate employment and earnings outcome data.

General Term Recommendations

In addition to the classes listed in the sections below, the following terms are recommended for use in the various contexts in which they appear:

Quantitative Value

Required

There are no Required properties for this class. Please use the Benchmark properties.

NSC Quality Non-Degree Credentials Framework: Stackability to additional education or training

Credentials should stack toward another postsecondary credential.

The credentials can also be shown in education and career pathways. See the CTDL Pathways Benchmark Model for more information.

The following CTDL terms identify the relationships between credentials.

General Term Recommendations

In addition to the classes listed in the sections below, the following terms are recommended for use in the various contexts in which they appear:

Pathway Set

Benchmark

There are no Benchmark properties for this class. Please use the Required properties.

Pathway

Benchmark

There are no Benchmark properties for this class. Please use the Required properties.

Pathway Component

Condition Profile Benchmarks

A Condition Profile describes a set of requirements for a credential, assessment, or learning opportunity. If there is more than one way to earn a credential or to complete a learning opportunity or assessment, you will need more than one Condition Profile.

Process Profile Benchmarks

Requirements

There are no Required properties for this class. Please use the Benchmark properties.

Benchmarks

There are no Benchmark properties for this class. Please use the Required properties.