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Supporting Indicator Personalization and Platform Extensibility in Open Learning Analytics

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Abstract

The demand for Open learning analytics (OLA) has grown in recent years due to the increasing interest in the usage of self-organized, networked, and lifelong learning environments. However, platforms that can deliver an effective and efficient OLA are still lacking. Most OLA platforms currently available do not continuously involve end-users in the indicator definition process and follow design patterns which make it difficult to extend the platform to meet new user requirements. These limitations restrict the scope of such platforms where users regulate their own learning process according to their needs. In this paper, we discuss the Open learning analytics platform (OpenLAP) as a step toward an ecosystem that addresses the indicator personalization and platform extensibility challenges of OLA. OpenLAP follows a user-centered learning analytics approach that involves end-users in the process of defining custom indicators that meet their needs. Moreover, it provides a modular and extensible architecture that allows the easy integration of new analytics methods and visualization techniques.

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Notes

  1. http://www.learning-context.de/

  2. https://github.com/OpenLearningAnalyticsPlatform/OpenLAP-Architecture/wiki/1.-System-Overview

  3. https://github.com/OpenLearningAnalyticsPlatform/OpenLAP-AnalyticsMethodsFramework

  4. https://github.com/OpenLearningAnalyticsPlatform/OpenLAP-Visualizer-Framework

Abbreviations

Apereo LAI:

Apereo Learning Analytics Initiative

ATAM:

Architecture Tradeoff Analysis Method

GQI:

Goal-Question-Indicator

LA:

Learning Analytics

LAP:

Learning Analytics Processor

LCDM:

Learning Context Data Model

MOOC:

Massive Open Online Course

OLA:

Open Learning Analytics

OLAA:

Open Learning Analytics Architecture

OpenLAP:

Open Learning Analytics Platform

RIDT:

Rule-based Indicator Definition Tool

SoLAR:

Society for Learning Analytics Research

SUS:

System Usability Scale

TEL:

Technology Enhanced Learning

UI:

User Interface

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Authors and Affiliations

  1. National University of Science and Technology (NUST), Islamabad, Pakistan

    Arham Muslim

  2. University of Duisburg-Essen, Duisburg, Germany

    Mohamed Amine Chatti

  3. RWTH Aachen University, Aachen, Germany

    Ulrik Schroeder

Authors
  1. Arham Muslim
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  2. Mohamed Amine Chatti
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  3. Ulrik Schroeder
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Contributions

The evaluation was designed and conducted by AM. The Literature review was performed and results were documented by AM together with MAC. Editorial reviews and formatting of the paper were done by AM and MAC. US is the head of the department where the evaluation was performed. All authors read and approved the final manuscript.

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Correspondence to Arham Muslim.

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Muslim, A., Chatti, M.A. & Schroeder, U. Supporting Indicator Personalization and Platform Extensibility in Open Learning Analytics. Tech Know Learn 27, 429–448 (2022). https://doi.org/10.1007/s10758-021-09543-0

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