Learning and Employment Record (LER) Guide

Introduction to Using Credential Engine’s Open Technologies to Support Learning and Employment Records

The Credential Transparency Description Language (CTDL) Schemas and the Credential Registry support linked open data (LOD) and Learning and Employment Records (LERs). An LER is a digital record of learning that can document learning wherever it occurs, including at the workplace, through an education program/experience, through community activities, and/or through military training. The design and format of the CTDL data complement related LER specifications, including W3C Verifiable Credentials (VC) and VC Wallets, 1EdTech Open Badges (OB) and Comprehensive Learner Records (CLR), and Velocity Network Foundation Credential Schemas, among others.

Whether you’re following government, ACE Blockchain Innovation Challenge, AACRAO, T3 Innovation Network, or other guidelines such as those included in federal grants recommending or requiring the use of LOD, the CTDL schemas and Credential Registry will support your LERs. CTDL and the Registry provide a consistent semantic interpretation of authoritatively-sourced data that can be used with LERs by providing open schemas and metadata that are understood by humans and actionable by machines.

Use this introduction guide to plan for and implement your LERs using Credential Engine’s open technologies. It is intended for people planning for or in the process of implementing LER solutions and includes both general information for non-technical understanding and technical information for implementers. It will be updated as additional examples are developed with other LER-related specifications. If you have any questions, please contact us. We’re happy to meet to go over this information, answer any questions, and provide services as needed.

What are Learning and Employment Records (LERs)?

"A Learning and Employment Record (LER) is a digital record of learning and work that can be grouped together with other individual LERs for use in describing their abilities when pursuing education and employment opportunities. An LER can document learning wherever it occurs, including at the workplace or through an education experience, credentialing, or military training. It can also include information about employment history and earnings." (T3 LER Hub)

• Digital records of learning from diverse sources
• Verifiable and secure
• Controlled and shareable by the individual
• Interoperable: transferable, meaningful, and machine-actionable across education and employment systems and processes

LER Action Guide

The Learning and Employment Record Action Guide (July 12, 2023) describes the phases and steps that stakeholders can take to develop and sustain trusted LER ecosystems. It is based on Credential Engine’s widely and successfully used State Roadmap and Action Guide for Transparency. Specific supporting resources are included in this Guide, as well as tools and resources on the Credential Engine state partnerships site. These resources guide why and how to connect LERs to their necessary data transparency infrastructure. Together we can achieve the goal of empowering people with LERs that unlock equitable opportunities.

We encourage you to use this Action Guide and provide feedback. We also encourage you to make a copy to remix and reuse for your LER purposes. If you’d like to provide feedback, please email info@credentialengine.org.

Global Open Standards

Standards support full transparency and interoperability of LERs:

• W3C Verifiable Credentials and Wallets - VCs for universal "envelope" data. VC wallets for collection and storage of LERs
• Open Badges 3.0 - For organized content packaging of single records
• Comprehensive Learner Records 2.0 - For organized content packaging of multiple records
• Credential Transparency Description Language (CTDL) - For meaningful linked open data so that LERs can be usefully understood and applied

Why CTDL is Important for LERs

In addition to the technical guidance below, you can learn more about why it’s important to use CTDL to make learning and employment records more meaningful, relevant, and actionable. These resources are available for you to reuse and remix as part of your own projects:

• Overview blog
• Slide deck (also available as a PDF)
• Webinar recording

For more context, see also:

• T3 Innovation Network: Semantic Mapping of Data Standard Schema Properties and Classes: Supporting Learning & Employment Records
• T3 Innovation Network LER Hub

How CTDL Supports LERs

The CTDL schemas are available for anyone to use under an open license and are designed to work together. The schemas currently include:

1. CTDL for rich descriptions of credentials and their requirements as well as related data.
2. The CTDL Profile of Achievement Standards Network (CTDL-ASN) for competency frameworks and competencies. Competencies are broadly defined in CTDL-ASN to include knowledge, skills, abilities, learning objectives, performance objectives, academic standards, and other similar types of data.
3. Quantitative Data (QData) for aggregate employment and earnings data.
4. The CTDL family of schemas also leverage select terms from Schema.org and SKOS.

Of these schemas, the CTDL and CTDL-ASN are most relevant to LERs. You can learn more about these schemas:

• CTDL handbook and Terms
• CTDL-ASN handbook and Terms

Modeled using the W3C’s Semantic Web principles and recommendation, the CTDL family of specifications has been developed to support rich descriptions of credentials, their requirements, and other related data. The Credential Registry provides machine-actionable LOD via web-resolvable URIs based on Credential Transparency Identifiers (CTIDs) with all key CTDL and CTDL-ASN classes, such as Credentials, Organizations, Assessments, Learning Opportunities, Pathways, Competency Frameworks, and Competencies. These URIs are generated by concatenating the resource's CTID to the Credential Registry namespace:

While the Credential Registry does not include descriptions of an individual earning a credential or competency, the LER record for an individual can reference CTDL data in the Registry via these URIs to enhance the LER record with rich descriptions of the credentials and competencies earned by the individual. This allows for records from multiple learners to reference the same credentials and competencies, which not only reduces data duplication and maintenance, but opens the door to powerful search queries and data analytics.

Example of CTDL Enhancing LER Interface Information

1. From left to right, the first mockup of an LER, digital credential, interface, showing some of the credentials, skills and competencies earned by a person.
2. In the middle, the information showing for a credential selected by, or shared by, the person is supported by the CTDL and the Credential Registry. Each credential has a URI.
3. To the far right, along with all of the credential information, each competency can be shown by using the CTDL-ASN and the Credential Registry. Each competency framework and competency within a framework has a URI.

Example of CTDL/CTDL-ASN Data in the Registry

The LER mockups above are based on data in the Registry for an Ivy Tech Community College Certificate in Pharmacy Technician. See this example in the Credential Finder. At the bottom right corner of the detail page about this credential, you can click on the JSON-LD icons to see the data in the Registry that was used to display the page.

Credential Example

Competency Framework Example

How the Credential Registry Supports LERs

Credential Engine provides a suite of publishing tools, a LOD repository, and supports consuming the metadata directly at the record level, via a graph search, or via an import option. No API key or special access is needed when retrieving a record directly via its URI, making the data open and easily accessible.

The credential and competency publishing tools for the Registry utilize the Registry Assistant Publishing API. This API is used to map structured data and output it as CTDL and CTDL-ASN encoded JSON-LD. Data publishers can use the JSON-LD output in their own environment, publish it to the Web and to the Registry, and use it with LERs. The credential data in the Registry is from authoritative sources and all data is required to follow the Minimum Data and Currency Policy.

Publishing Credentials and Competencies to Reference with LERs

Any organization that wants to go from credential, competency, or pathway information in documents or web pages to Linked Open Data can create a Credential Engine account and select the most appropriate publishing tool(s) to manage their information and publish to the Credential Registry. Using the existing publishing tools and publishing to the Registry is free.

Learn more and sign up for an account here.

Available publishing tools include:

1. Registry Assistant Publishing API - This is recommended in all cases where the source of structured data for credentials, competencies, or pathways can be mapped to the API to publish data as it is updated to the Registry.
2. Bulk upload of credentials, competencies, or pathways - This uses CSV files to upload small to large quantities of information.
3. Manual entry of credentials and competencies - This is recommended for small quantities of credentials or competency frameworks.

The Credential Engine publishing technology stack also integrates an open source project funded by the Department of Defense called the Competency and Skills System (CaSS). Credential Engine integrated CaSS to utilize its competency publishing interface, competency alignment capabilities, and has included publishing competencies to the Registry in CTDL-ASN or optionally import from CaSS in 1EdTech CASE format. CaSS is available for any organization to set up their own instance for local competency management and publishing. If you’re looking into local interoperable competency framework management solutions, you can check out the CaSS repository on GitHub or contact Eduworks.

Enhancing Learning Records with CTDL Schemas

The CTDL schemas are all available under open licenses for anyone to use. Existing projects looking to minimize data design updates or leverage the Credential Registry can include CTIDs and URIs in existing data and models in order to reference rich descriptions.

If you're designing a new project or updating a data model and/or schema for an existing project, the CTDL schemas can all be used per their Creative Common Attribution 4.0 International License. Use as much of the schemas, all designed to work together, as needed.

Our technical team actively works to evolve the schemas. If in the process of reviewing the schema for your data design you identify potential updates that would be helpful, we will review such requests. We use GitHub issues regularly and recommend you post any issues or requests to our Schema Issues GitHub Repository. Using CTDL in your data design means you’ll have a jump start with Linked Open Data as it is already modeled on RDF and it is aligned to Schema.org and other specifications such as Open Badges.

To get started:

1. Review the CTDL Explorer.
2. Dig deeper with the CTDL Handbooks, which each include domain diagrams and JSON-LD encoded examples.
• CTDL handbook
• CTDL-ASN handbook
3. Review the Schemas
• CTDL Terms
• CTDL-ASN Terms
• The general references at the top of the page show external vocabulary alignments (e.g., Schema.org).
• Use the filters on the bottom of the page to jump to classes, properties, concept schemes, and concepts.
4. Download complete serializations of the schemas.

Using CTID-based URIs and Registry Search

Utilize CTID-based URIs in these ways:

• Store URIs with the LER. As described in the above section, include CTIDs with data design.
• Provide an LER interface to display LOD from the Registry. The data in the Registry is a source for consistently formatted LOD following the CTDL and CTDL-ASN schemas.

There are a number of ways to use the Registry data. To use the Registry data, set up a Credential Engine Account to receive your key to pull data from the Registry. Use the CTID-based URIs:

• For an organization to reference the record for that organization in the Registry.
• To pull in the most current credential and competency data with or without related graphs.
• To pull in a specific previous version of the credential or competency data.

Use the Registry search API to get an up-to-date snapshot of the credential and competency data. Import and store point-in-time information to your system or check for updates to keep the imported data current.

Including URIs to Raw Data in the Registry or to a Detail Page in the Credential Finder with an LER Interface

There’s two options to include URIs to Credential Registry data with an LER user interface:

1. Use URI(s) to the durable machine readable data in the Registry. This is recommended and anticipates there is a user interface for viewing this data.
• Use the following format: https://credentialengineregistry.org/resources/[CTID]. Paste the actual CTID to replace [CTID].
• Example: https://credentialengineregistry.org/resources/ce-9d99809e-07cb-4520-8d09-abb6f251f2d9
• Note: Some resources will have additional information not contained in the main record, such as the organization and competencies that belong to a competency framework or basic data about entities that do not have official records in the registry, such as a reference to an organization that accredits a credential. To retrieve this additional information, use /graph/ instead of /resources/ in the URI structure provided above. It is recommended to always reference the /resources/ URI in issued LERs and only use /graph/ when necessary, such as an implementation or interface that needs to retrieve the additional data.
• Example: https://credentialengineregistry.org/graph/ce-9d99809e-07cb-4520-8d09-abb6f251f2d9
2. Use URIs for people to view a resource such as a Credential in the Credential Finder. This provides an end-user interface linked to the Credential Finder website, which pulls information from the Credential Registry.
• Use the following format: https://credentialfinder.org/resources/[CTID]. Paste the actual CTID to replace [CTID].
• Do not copy/paste the urls directly from the Credential Finder. Those urls could change.
• Example: https://credentialfinder.org/resources/ce-9d99809e-07cb-4520-8d09-abb6f251f2d9

Referencing Registry Data with 1EdTech Open Badge V2.0 and V3.0

In the 1Ed Tech Open Badges Implementation Guide (Document Version 1.7, December 15. 2023), Section 3 Recommended Practices includes information and examples for using the badge alignment to integrate with CTDL data. This integration enhances the effectiveness of badge implementation. In this context, we refer to the following subsections:See the following sections:

• 3.1.6 Alignment with a ceterms:Credential resource - Within CTDL, 'Credential' serves as a superclass encompassing various types of credentials, each with its own specific subclass. For optimal alignment, we recommend utilizing the more specific subclass that aligns with the badge's purpose. You can find a comprehensive list of CTDL credential subclasses to aid in this alignment.specific subclass. See a complete list of CTDL credential subclasses.
• 3.1.7 Alignment with a ceasn:Competency resource - Aligning badges with 'Competency Resources' in CTDL is a key practice for demonstrating skill acquisition. This alignment provides clarity and depth to the badge's meaning, making it valuable in showcasing specific competencies.
• 3.1.8 Alignment with a CTDL resource - CTDL offers a wide array of resources for aligning badges with various educational and professional contexts. This section explores aligning badges with CTDL resources, enhancing their relevance and utility.

By integrating these practices into your badge implementation strategy, you'll not only enhance the significance of your badges but also provide a more robust and informative experience for your audience.

The following example shows how an Open Badge following the 1EdTech Open Badge V2.0 specification references CTDL encoded JSON-LD records published to the Registry via an Alignment Objects. The targetUrl references the data for a ceterms:Certificate in the Registry. The Alignment Object also references a ceasn:Competency. Multiple competencies could be referenced as well.

Using CTDL with 1EdTech CLR Specification

References to CTDL and CTDL-ASN encoded data from records using the 1EdTech CLR Specification along with encoded examples are included below.

Each of the 1EdTech CLR Achievement Records below could reference CTDL-encoded data from the Registry. The table below shows which CTDL type would be referenced by which 1EdTech CLR Achievement Record. This is not a direct class-to-class mapping, but rather, an explanation of which type of CTDL data could be referenced via URI by which type of 1EdTech record.

* Could also be associated with any credential type as determined by the credentialing organization.

JSON Examples of 1EdTech CLR References to CTDL

Below are some examples of CTDL data being referenced by 1EdTech CLR Records, listed by use case.

Use Case: Reference Organization

Use Case: As a publisher, issuer, or endorser I want to link my Profile to my Credential Organization data in the Registry.

Any Profile in CLR can link to an external reference via its URI. With this example, the 1EdTech CLR "Profile" references the data for a ceterms:CredentialOrganization in the Registry.

To get the data for the organization, services should GET the full CTDL JSON-LD data using the id.

Use Case: Reference License

Use Case: As an issuer I want to include a reference to a License (published to the Registry and encoded in CTDL) with my assertion of achievement.

When the achievement description represents one or more records in the Registry, the achievement should contain one or more alignments. Each alignment should have a targetType of CTDL and targetUrl should be the URI of the Registry record. This CLR snippet shows an Achievement aligned to the "Advanced Practice Nurse" ceterms:License published in the Credential Engine Registry.

To get the data for the license, services should GET the full CTDL JSON-LD data using the targetUrl.

Use Case: Reference Learning Opportunity

Use Case: As an issuer I want to include a reference to a learning opportunity (published to the Registry and encoded in CTDL) with my assertion of achievement.

When the achievement description represents one or more records in the Registry, the achievement should contain one or more alignments. Each alignment should have a targetType of CTDL and targetUrl should be the URI of the Registry record. This CLR snippet shows an Achievement aligned to the "Salesforce Marketing Cloud Implementation Workshop" ceterms:LearningOpportunityProfile published in the Credential Engine Registry.

To get the data for the learning opportunity profile, services should GET the full CTDL JSON-LD data using the targetUrl.

An explanation of the code libraries used to operate on CaSS Assertions can be found at: CASS Developer Guide # Assertions.

CaSS Assertions support credential awards via the credential property, which may point at any CTDL credential or badge class.