What is a Learning Record Store?

A Learning Record Store, or LRS, is an application that stores records about learning. From a data perspective, an LRS sits at the center of your learning ecosystem and brings data together from all your learning systems, applications, and content. It also will often connect to operational systems to gather data about job performance.

Not every database of learning records is an LRS, though. The term “LRS” refers to a specific type of application defined by the Experience API (xAPI) specification. And because xAPI sets strict rules around the core functionality of LRSs, it’s important to use an LRS that strictly conforms to those parameters. A non-conformant LRS will cause problems when you try to connect other applications via xAPI or use the data later.

If an LRS was part of a house, for example, it would be the plumbing—not the window. In other words, learners don't typically interact with or see an LRS as it collects data about their interactions and influences their learning experiences behind the scenes.

What can I expect from my LRS?

All LRSs must support certain core functionality required by xAPI. This includes:

There are applications that may implement some of this functionality, but not all of it. For example, an app might receive learning records to trigger an action, but it won't store the records or return them. Another app might not be able to receive records from external applications, limiting it to only providing availability to records it created. And, while an LMS might store learning records generated internally, it won't support the ability to receive or send records to other systems.

While these applications might fulfill important use cases, they can’t be considered LRSs. If you’re in the market for an LRS, ask:

"Can your product receive learning records from external xAPI applications, and can it return learning records to external applications when requested via xAPI?"

Quality Control: LRS Conformance Testing

LRSs are required to respond to clients in the way defined by the xAPI specification and validate the data Learning Record Providers send. This helps protect your LRS from bad data, which can cause problems both when processing the data and then displaying it in reports later.

The conformance test suite confirms these requirements when testing an LRS. This is a vital step, but doesn’t guarantee that the version of your LRS is still conformant. The LRS code may have changed, or the LRS may have been configured differently than the settings used during the test. Ask your LRS vendor if they have regularly updated processes to ensure their LRS remains conformant, and if they’ve configured their LRS to behave in a non-conformant way.

At Watershed, we’ve built the conformance test suite into our testing and release process to ensure we only deploy versions that pass the test suite.

When comparing LRSs, you should choose an LRS that has the core functionality above, plus any of the additional features you require.

Consider the extras.

Many LRSs offer additional functionality. When comparing LRSs, choose an LRS that has all the core functionality, plus additional features you need. These might include:

  • Tools for developers, such as debug logs and data search
  • Additional data export functionality beyond core xAPI requirements (e.g., options to query via API, data downloads, or pushing learning records to other LRSs)
  • Data import options, including CSV to xAPI translation
  • Static visual reports and dashboards
  • Configurable visual reports and dashboards
  • The ability to merge data about individuals collected under different identifiers for that person
  • Organizational hierarchies for comparative reporting and permissions
  • Single Sign On (SSO)
  • Deployment options (e.g., cloud-hosted vs. self-hosted)

Most of the additional features discussed above aren’t simply checking a box with yes or no. The quality, robustness, and usefulness of these features can vary significantly between LRSs. Overall performance and speed, services offered, and support are other factors that vary between LRSs.

If your goal of implementing an LRS is to use learning analytics, there are a few things to keep in mind when getting started. To learn more, follow our insights blog or check out the resource center.

Want to see how an LRS fits into the data ecosystem?

Complete the form below to explore the nine areas of a data ecosystem and Watershed's LRS fits into the mix.

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