Our LMS has an in-built Learning Record Store (LRS) providing a single record location for all forms of training, whether via an online platform, face to face, seminars or appraisals.

 

What is a Learning Record Store?

The heart of any xAPI ecosystem is the learning record store. The LRS receives, stores and returns xAPI information statements. You will need an LRS to work in conjunction with the xAPI. The tool sends and receives activity information data, usually the learners, which interacts with learning record store as the central hub.

The definition of LRS: is a server system that is capable of processing received web requests and responsible for storing, receiving and providing access into the LRS.

The LRS is designed for storing and receiving xAPI statements as well as storing xAPI statements. The xAPI is for storing metadata from another system. Factoring in that in essence the “S” in the store means what is says, which at its core is to store information and make available information xAPI stats. 

A learning record store receives and stores data regarding learning experiences, achievements, performances and everything else is relevant to your training. They are usually standalone systems, but at Bolt we provide an efficient learning record store as an integral part of our LMS.

Our Learning Record Store (LRS) enables modern tracking of a wide variety of learning experiences, data from these experiences can be viewed through our powerful reporting suite or shared with other systems for reporting analytics and to support adaptive learning experiences.

The data collected allows you to define and record attendance and participation in different forms of training and can be collated to evaluate the effectiveness of training programmes and learning solutions. A learning record store is an essential tool for big companies with the need to store data about a big number of employees.

Our learning record store can capture data on learning experiences outside of the current company or organisation, so even records pertaining to courses trainees have done in their own time, or in a previous role, can be recorded giving you as full a picture on a trainee as possible.

 

Learning Record Store

 

What does LRS enable?

So, we know that the main function of LRS is to store and collect data. The learning record store enables superior tracking from a large selection of learning experiences and can include various actions completed from performance of jobs to mobile apps.

All the data that is collected in the LRS and can be shared with other systems, which enables very sophisticated reporting, which other learning systems support. This helps adaptive learning and the trend for growing businesses to help learning and development.

 

Developing Learning Record Store into an Analytics Platform

The trend towards LRS being used more than their initial intended functionality is clear. New LRS functionality combines xAPi data storage with dashboards, insightful analytics and allows for recommendations based on user interaction.

Here at Bolt we have developed an LMS that captures the essence of LRS but developed the most advanced data analytics tools to enable the learning record store to offer user engagements insights at such a granular level that we can tell exactly what questions are causing problems, which gives actionable data to make critical decisions.

 

How to Know if You need an LRS?

In order to know if you need a learning record store there are some key questions to consider and ask yourself. Firstly, do you need dashboard functionality with reports that are built into the system? Do you want the LRS to give you deep insights into your learners? We know analytics are important for understanding the effectiveness of training, so this might be worth considering when deciding to choose an LRS. How deep into analytics do you want to go? Traditionally learning systems provided information on users learning experiences in simple form, such as “completed” or “in-progress”, but with modern systems like LMS they offer insights into granular aspects of big data analysis. For example, companies with 10,000 learners might want to understand why users are failing in one section of a module. In order to assess this, we would need to see the page interactions of users and get in-depth data that can help resolve learning journey’s and as a result be more effective in training.