Muhammad Faizan Riaz

Master Thesis Student

Email: muhammad.riaz.faizan@stud.uni-due.de

Thesis topic: A Generic Infrastructure to Support Different Database Technologies in OpenLAP

Related project: OpenLAP

Supervisor: Dr. Arham Muslim

Thesis duration: 05/2019 - 11/2019

 

Description

Open Learning Analytics (OLA) is an emerging field, which deals with learning data collected from various environments and contexts, analyzed with a wide range of analytics methods to address the requirements of different stakeholders. The diversity in different dimensions of OLA introduces a set of challenges for the LA developers and researchers while designing solutions for OLA. The Open Learning Analytics Platform (OpenLAP) is a framework which addresses these issues and lays the foundation for an ecosystem of OLA that aims at supporting learning and teaching in fragmented, diverse, and networked learning environments. It follows a user-centric approach to engage end users in flexible definition and dynamic generation of personalized indicators. OpenLAP adopts a data model called the Experience API (xAPI) to address the data aggregation and integration as well as the interoperability requirements.

The aim of this thesis is to increase the interoperability of OpenLAP using a generic framework to seamlessly support different underlying database technologies. Therefore, an appropriate data access framework should be investigated based on different dimensions and incorporated into the OpenLAP.