Learning Analytics Processor (LAEP Inventory)

Cloud created by:

Rebecca Ferguson
11 February 2016

Synopsis

The Learning Analytics Processor (LAP) is software to manage a learning 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 pipeline is build using an open architecture that exposes output from the pipeline via a collection of web service APIs. The LAP is a general-purpose tool designed to meet the need for scaling up learning analytics from manually driven processes to automation of the routine technical tasks. The essential purpose of the LAP is to streamline data pre-processing, predictive model use, and results post-processing to make this a more efficient and reliable process. It is configurable, not tied to particular data sources, and agnostic as to the way the results of the predictive model are used.

 

Currently, the LAP supports the Marist College Open Academic Analytics Initiative Early Alert and Risk Assessment model but development of additional models as well as feature and scalability enhancements are under way.

Classification

Inventory type:

general analytics tool

Role of analytics:

prediction

modelling

Data sources:

LAP can use data from different sources

Keywords:

workflow, pipeline, predictive analytics, open source

Tool in Context

Learning:

school/VET/post-compulsory/informal

Supply model:

desktop tool/self-hosted server software/privately-hosted software/shared service model

Origin:

OAAI Project (led by Marist College): collaborative project

Unicon: TEL vendor (open source)

Ethics and privacy:

The original OAAI project was undertaken with ethical research oversight. Since the LAP is a system to automate an analytics pipeline, rather than being a user-facing application, the main concern is system security.

Languages:

Not applicable

Maturity and Evidence of Utility

The LAP arose out of the Open Academic Analytics Initiative (OAAI), led by Marist College (USA), being conceived of to automate the processing pipeline that OAAI demonstrated.

It is currently work in progress, being an incubation project in the Apereo Foundation, and is under development by Unicon and Marist, having been selected in a competitive tendering process as a component for the Jisc Effective Learning Analytics pilots.

Further Information

Tool provider’s website, Apereo Foundation, open source custodian: http://bit.ly/LAP-Apereo

LAP and Open Learning Analytics, outline: http://bit.ly/LAP-OLA

LAP features and technical architecture: http://bit.ly/LAP-Details

 

Jayaprakash, S. M., Moody, E. W., Lauria, E. J. M., Regan, J. R., & Baron, J. D. (2014). Early alert of academically at-risk students: an open source analytics initiative. Journal of Learning Analytics, 1(1), 6–47. [describes the Open Academic Analytics Initiative project]

 

See also LAEP Inventory record:

  • Effective learning analytics pilots – Jisc

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