Human Computer Interaction

Personalized learning experiences are pivotal in enhancing student engagement and academic success. This thesis investigates the development of dynamic learner profiles within Artemis, an open-source Learning Management System (LMS). By leveraging data analytics and machine learning techniques, we aim to generate comprehensive learner profiles that capture individual learning behaviors, preferences, and progress. These profiles will enable tailored educational experiences, providing insights for both educators and learners. The study covers the methodology for data collection and analysis, the design and implementation of the profiling system, and the impact of personalized learning on student outcomes. This research offers valuable contributions to the field of adaptive learning technologies and the advancement of personalized education.

In the rapidly evolving landscape of educational technology, scalable and maintainable software architectures are crucial for the success of learning management systems (LMS). This thesis explores the transformation of Artemis, an open-source LMS, from a monolithic architecture into a modular system using Java Modules. By modularizing Artemis, we aim to enhance the system’s scalability, maintainability, and development efficiency. The thesis delves into the challenges of decomposing a large monolithic codebase, the strategies employed for effective module separation, and the benefits realized post-modularization. This research provides a comprehensive guide for developers and engineers aiming to modernize legacy monolithic applications in the educational technology domain.

This Master’s thesis aims to enhance the educational platform Artemis by implementing automatic formative feedback for students and improving semi-automatic assessment for tutors. Building on the foundational work of Athena and CoFee, which use NLP and LLMs for text-based feedback, this project focuses on refining these techniques for greater accuracy, reliability, and consistency.

The initial phase will prioritize developing immediate feedback mechanisms to support students before deadlines. Following this, we will explore advanced LLM techniques like RAG, CoT prompting, self-consistency, and fine-tuning models like Llama 3 and GPT-4 with historical feedback data. Each iteration will be evaluated for accuracy, efficiency, and educational impact to ensure continuous improvement. By adopting an agile approach, we aim to deliver automated, personalized feedback that enhances student learning and reduces tutors’ workload, creating a more efficient and supportive educational environment.

In this thesis, we develop a gamification-based system to enhance the code review process by increasing participation and improving code quality. By integrating gamification elements such as points, levels, badges, and leaderboards into existing code review platforms, we aim to create a more engaging and motivating environment for developers. Our system provides real-time feedback through a user-friendly web interface, and seamlessly integrates with popular development tools to support continuous workflows. The primary contribution is a versatile framework adaptable to various code review systems, fostering a culture of continuous improvement and collaboration among developers. To evaluate the system’s effectiveness, we will conduct a comprehensive user study involving multiple development teams. This study will use both quantitative metrics, such as participation rates and review quality scores, as well as qualitative feedback from user surveys and interviews. The results will provide detailed insights into the impact of gamification on code review practices, demonstrating its potential to enhance software development processes and other collaborative environments.

In modern development workflows, the seamless integration of UML diagrams into documentation, issues, and pull requests on Git hosting services is crucial for clarity and collaboration. We can significantly enhance Apollon, a web-based UML editor, to meet these needs. This project aims to implement efficient embedding capabilities, allowing developers to embed their UML diagrams with live updates in issues, pull requests, and more. When users make changes to diagrams in Apollon, the system will automatically reflect these changes in their embedded versions, eliminating the need for manual updates. Additionally, we will introduce version management, which will enable users to capture new versions, preview changes, and revert to previous versions. Furthermore, a new structured and readable textual format for diagrams, integrated with VSCode, will facilitate developers in versioning their UML diagrams with Git for seamless documentation integration. These enhancements will improve Apollon’s usability, encouraging its adoption in development workflows.

To enhance Artemis as a more dynamic and approachable platform for TUM students and external users, it’s important to ensure compatibility with and integration into other learning platforms. One way to accomplish this is by using the Learning Tool Interoperability standard, which allows for the seamless integration of different Artemis features into platforms like Moodle or edX. The primary objective of this thesis is to further improve the functionality and scope of the Learning Tool Interoperability integration. A major focus is to ensure that all Artemis features are easily accessible from Moodle, facilitating a smoother and more integrated experience for users unfamiliar with Artemis. These features encompass various aspects of the Artemis platform including competencies, lecture and exercise selection, learning paths, and the Iris dashboard.

Abstract TBA

Computer science education in schools often fails to engage school students with diverse prior knowledge. Many existing educational tools also lack gender-sensitive design, particularly at the foundational level when girls are making critical future career decisions. This thesis will evaluate digital and unplugged games in computer science education to enhance computational thinking and address adaptive learning needs. The study will identify the strengths and limitations of these tools, focusing on their adaptability and ability to engage young girls. Based on these findings, the research will provide evidence-based recommendations and best practices for integrating gender-sensitive and adaptive strategies into computing education. In addition, the study will include the development and testing of an interactive game with multiple levels of difficulty designed to engage all genders. The results will provide valuable insights for improving computer science education, fostering inclusive learning environments and promoting greater gender balance.