Conveying information in a tour traditionally either requires a real human or an audio recording. However, the human guide might not always be available and the quality in the tours varies. With audio recordings, extra care has to be taken to convey to the user which element is currently being talked about since there are ...
Learning content by heart can be facilitated by the method of Loci. In this mnemonic technique, the learner converts pieces of information into mental imagery. The imagined representations are then anchored in a location. If the learner then traverses a path through this location, the information can be remembered by recalling the mental imagery. However, ...
The emergence of large language models (LLMs), along with recent advances in mixed reality (MR) and virtual reality (VR), enable new opportunities for applying virtual agents in education. These simulated humans can imitate real-life situations and interactions with native speakers, which leads to an immersive and engaging learning experience. Especially in VR, interactions can be ...
Mixed reality agents are simulated humans who are displayed in a mixed reality environment, e.g., in augmented reality or virtual reality. They provide the opportunity to support teaching activities with automation. Possible use cases include general presentations in one place, e.g., of lecture content and station-based routes as seen in museums or with tourist guides. ...
Mixed reality agents are simulated humans which can be viewed and interacted with on mixed reality technologies. For conveying content in educational settings, mixed reality agents have a series of advantages. They are part of a mixture of virtual elements with the real world, which provides opportunities where the agent can refer to points and ...
This bachelor thesis aims to delve into the critical intersection of trust, transparency, and bias mitigation in machine learning (ML) systems through the lens of explainable data. The proliferation of ML algorithms across various domains has underscored the importance of understanding how these systems make decisions, especially when they impact individuals or societal outcomes.
The bachelor thesis aims to contribute to the ongoing research project MILKI-PSY, which is centered around advancing Self-Regulated Learning (SRL) in psychomotor training through multimodal immersive mentoring. In the context of the project, we explore how various calculation mechanisms and hardware decision impact the latency of feedback in psychomotor learning.
