Categories
Pages
-

DBIS

Collaborative Immersive Learning Analytics

December 16th, 2021

Our approach is a comprehensive and evolutionary sociotechnological learning analytics and design process leading to a flexible infrastructure where professional communities can co-create their wearable enhanced learning solution.

Thesis Type Master
Student Suchi Julidayani
Status Finished
Submitted in 2021
Proposal on 25/05/2021 12:35 am
Proposal room
Presentation on 21/12/2021 1:00 am
Supervisor(s) Ralf Klamma
Stefan Decker
Advisor(s) Benedikt Hensen

Nowadays, we can use immersive interaction and display technologies in collaborative analytical reasoning and decision making scenarios. In order to support heterogeneous professional communities of practice in their digital transformation, it is necessary not only to provide the technologies but to understand the work practices under transformations as well as the security, privacy and other concerns of the communities. Our approach is a comprehensive and evolutionary sociotechnological learning analytics and design process leading to a flexible infrastructure where professional communities can co-create their wearable enhanced learning solution. At the core, we have a multi-sensory fusion recorder and player that allows the recordings of multi-actor activity sequences by human activity recognition and the computational support of immersive learning analytics to support training scenarios. The approach shall enable cross-domain collaboration by fusing, aggregating and visualizing sensor data coming from wearables and modern production systems. The software shall be open source and shall be based on the outcomes of several national and international funded projects.


Prerequisites:

Strong knowledge of Javascript, Java/C#/C++
Knowledge in Unity, Augmented/Virtual Reality
Interest in Mixed Reality Hardware and Software, Wearables, Web Technology