Email: rahim.seyidov@stud.uni-due.de

Related project: OpenLAP

Supervisor(s): M.Sc. Shoeb Joarder

Thesis topic:  Enhancing the Modularity and Scalability of the Analysis and Visualization Modules in OpenLAP

Description: OpenLAP is a learning analytics platform designed to serve a range of stakeholders, including teachers, students, researchers, designers, and developers. It enables users to generate custom indicators by selecting specific data, applying filters, and choosing from various analysis and visualization methods to present data graphically. The objective of this thesis is to augment OpenLAP's functionality by improving its modularity and scalability. This enhancement will be achieved by integrating a broader array of analysis methods and incorporating additional visualization libraries in a user-friendly manner.

Thesis duration: 01/2024 – 04/2024