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  1. Learning Analytics Initiative
  2. LAI-3

LAP 1.0 - Initial learning analytics processor (OAAI automation)



      This is the parent ticket for the work on the Learning Analytics Processor 1.0. All the work will happen in linked task and feature tickets.

      Tasks (in execution order):
      LAI-4 App setup
      LAI-2 Data format definitions
      LAI-9 Sample data
      LAI-6 Initial architecture
      LAI-1 Sakai data extraction
      LAI-5 OAAI processing pipeline

      Wiki page with more details:

      Code in GitHub: https://github.com/Apereo-Learning-Analytics-Initiative/LearningAnalyticsProcessor

      Project Goals
      Complete OAAI Automation and package it as a web service API.
      Make OAAI a sustainable open source predictive modeling framework.
      Establish a framework for automation and execution of learning analytics models (which is possible to extend with additional model pipelines)
      Establish input and output specifications for data used for model processing

      Key Requirements
      API should satisfy the following criteria:
      Accept 4 required OAAI data files from the input directory
      Validate the data inputs for compliance with OAAI data specifications
      Perform data processing and generate predictions using a PMML based model developed by Marist College
      Output the results in configurable formats (JSON / CSV / XML)
      Provide seamless integration with Sakai CLE

        Gliffy Diagrams


            Issue Links



                • Assignee:
                  kvalenti@unicon.net Kate Valenti (Inactive)
                  aaronz Aaron Zeckoski (Inactive)
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                  • Created:

                    Git Source Code