The Learning Analytics Processor project is aimed at accelerating the future of predictive learning analytics through the development of a flexible and highly scalable tool that will facilitate everything from academic early alert systems to data visualizations. Along with this powerful “big data” tool will come a library of open predictive models which can be shared across higher education free of licensing costs and, most importantly,allow institutions to collaborate on enhancing and improving these models over time. View our PDF brochure.
The project entered incubation in June 2015.

At a high level the Apereo Learning Analytics Processor application can be considered the manager of an analytics workflow. Typically, this type of workflow is referred to as a pipeline and consists of three distinct phases: input, model execution, and output. The Apereo Learning Analytics Processor supports this type of pipeline construct. Additionally, the Apereo Learning Analytics Processor exposes output from the pipeline via a collection of web service APIs.

The Apereo Learning Analytics Processor was developed using:

  • Java / Spring-Boot
  • MongoDB / H2

Currently, the Apereo Learning Analytics Processor supports the Marist OAAI Early Alert and Risk Assessment model but development of additional models as well as feature and scalability enhancements are underway.

The code for the Apereo Learning Analytics Processor is located at GitHub.

Contributors include:

  • Marist College
  • Unicon

Mailing lists:

  • lap-user[at]apereo[dot]org
  • lap-dev[at]apereo[dot]org



Apereo Analytics Flyer 2016

Introduction to the Apereo Open Learning Analytics Platform (April 2016)

     Apereo Analytics PDF - 26 April 2016