Description

Problem: 

Data-driven Digital Twins are increasingly used in complex decision-making environments. Humans can significantly enhance Digital Twins operations through domain knowledge and cognitive and physical capabilities. To allow human integration in Digital Twins in a more systematic manner, efforts are being made to develop standardized frameworks and applied prototypes. However, evaluating such frameworks and corresponding prototypes remains a major challenge.
 

To enable systematic development and comparison of Human-in-the-Loop Digital Twins, a structured evaluation methodology is required that considers multiple dimensions such as user satisfaction, transparency, cognitive load, and operational efficiency.

Goal: 

The goal of this thesis is to design and validate an evaluation framework for Human-in-the-Loop Digital Twin systems, including both conceptual frameworks and technical implementations.
 
To achieve this, the student will review evaluation approaches from related domains such as Human-Computer Interaction, Human Factors, and simulation-based systems. Based on this, relevant evaluation dimensions and metrics will be identified and consolidated into a unified, multi-dimensional evaluation method, which is subsequently applied and validated.

Required Skills and Knowledge: 

• Interest in Digital Twins and Human-Computer Interaction.

• Basic understanding of empirical research methods.

• Analytical and structured working style.

• Basic programming skills (Python) are beneficial but not required.

• Interest in user studies and evaluation design.