As universities strive to enhance the effectiveness of their lecture exercises, there arises a need for diverse and realistic test user scenarios to evaluate the understandability and usefulness of educational materials. However, in creating such scenarios a number of challenges arise: Real world students can rarely be used for testing, they are likely inexperienced or ...
Fine-tuning pre-trained large language models (LLMs) enhances biomedical text mining. This thesis introduces a tool capable of performing tasks such as Named Entity Recognition (NER), Normalization (NEN), and Knowledge Graph Construction (KGC). A key research question explores how LLMs can address the challenges of named entity recognition, normalization, and relation extraction in biomedical contexts.
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 thesis aims to explore the realm of Natural Language Processing (NLP) in the context of automated grading systems, focusing specifically on identifying and analyzing frequent learner mistakes. With the increasing integration of technology in education, automated grading systems have gained prominence, but they often lack nuanced understanding and feedback provision. This research endeavors to ...
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.
Open Source Software (OSS) revolutionised the computing world about three decades ago. One of the principles of OSS guarantees software developers, companies, researchers, and students the freedom to change and improve the software. Characterised by active community involvement (bazaar-style software development), OSS development has produced category-killer Operating Systems (e.g., Debian, Ubuntu) and applications (e.g., the ...
This thesis aims to develop a social bot designed to enhance self-regulated learning experiences by leveraging xAPI statements to track learning progress. The system will employ the “GRETA Kompetenzbilanz” model to visualize the learner’s progress comprehensively, recommend suitable learning materials, and facilitate reflective practices. The project also explores the potential integration of FAQ handling and ...
Psychometric inventories provide a means to analyze the expression of a variety of human traits. When applied on specific sets of people, they may show shared characteristics that could contribute to their behavior. Common traits can be significant for criminal individuals, as they could be used to discern early warning signs or identifiers. For example, ...
This master’s thesis aims to advance the field of psychomotor learning within the context of Project MILKI-PSY, a research initiative focusing on multimodal immersive mentoring to facilitate Self-Regulated Learning (SRL) for psychomotor training. Psychomotor learning involves the acquisition of skills through the integration of physical and cognitive processes. In this project, we are developing an ...
This bachelor thesis aims to explore the development of a peer-assisted exergame using Unity as the framework and YOLOv8 for movement tracking. Exergames, which combine exercise and gaming elements, have gained popularity in recent years as a means to promote physical activity. However, they often lack a social component, which could enhance motivation and engagement. ...
High data quality is becoming increasingly critical to today’s medical research. After identifying respective data quality rules, data quality checks can be implemented relatively easily on structured data. However, Pathology reports are predominantly narrative reports. Thus, these reports, comprising microscopy, histology and diagnosis provide very few structured elements. Hence, consistency checking of the sections of ...
Writing is an essential skill in both academic and professional contexts, that allows individuals to convey their thoughts, ideas, and information in a clear and concise manner. However, it can still be challenging to write effectively, efficiently, and accurately, especially for non-native speakers of the language.
The immense growth of scientific literature makes it nearly impossible for researchers to keep pace with all new developments in their domains. An automated scientific Question Answering (QA) system could substantially expedite the process of literature review, hypothesis generation, and knowledge extraction. With the emergence of Large Language Models (LLMs) like GPT, BERT, and their ...
In recent years, the advancements in natural language processing and machine learning have revolutionized various industries and domains.
This thesis aims to explore the potential of training a Large Language Model (LLM) on Git source code repositories to enable it to effectively respond to queries regarding the codebase, such as dependencies and functionality.
