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

Competency-based education gives students transparency and flexibility in their learning process. The usage can enhance motivation, especially in university settings where instructors address students with diverse backgrounds and prior knowledge together. Therefore, Artemis contains the adaptive learning system Atlas to support university teaching. To provide the best experience possible to students, it is essential to understand how students currently interact with the system integrated into Artemis and its impacts on their learning process.

The need for effective digital platforms that support pupils and educators in computer science education is rising. This thesis seeks to evaluate existing platforms, such as Code.org, CS Unplugged, and ScratchEd, based on criteria including accessibility, usability, and adaptability. It will also examine whether these platforms incorporate configurators that allow teachers to input parameters such as pupil age, class size, and lesson duration. Based on this analysis, the thesis will propose recommendations and develop a Minimum Viable Product (MVP) of a configurator tool. The tool will be tested and refined in collaboration with educators to support the creation of tailored lesson plans and improve engagement in diverse classroom settings.

TUM lacks a unified, user-friendly platform for managing doctoral applications. Fragmented systems lead to inconsistent information, limited transparency, and accessibility barriers. Unclear navigation and outdated interfaces hinder applicants, while manual tasks burden faculty and staff. A centralized, inclusive solution is needed.

The increasing importance of computational literacy drives efforts to introduce computer science concepts early in education. However, many primary school teachers lack formal technical training, making selecting engaging, pedagogically sound activities difficult. Existing tools often lack personalization, leading to ineffective choices, while disparities in technology access highlight the need to integrate unplugged, digital, and hybrid approaches.

This thesis proposes a recommendation system to help teachers select suitable computer science activities based on age group, format, resources, and educational objectives. The system will leverage a comprehensive tagging framework grounded in pedagogical principles and compare different recommendation approaches for accuracy and scalability. This research aims to empower teachers with a personalized tool that boosts confidence in teaching computer science while enhancing student motivation and creating more inclusive learning experiences.

This thesis designs, implements and evaluates a board game using Ozobots to address gender stereotypes in STEM education among elementary students. It reviews gender-sensitive strategies, assesses robotics tools for inclusivity, and develops an engaging board game to promote equal participation and interest in STEM fields for both boys and girls.

Pupils playtest two board games that are identical in structure but differ in theme. Each version addresses a distinct gender stereotype. The process records engagement, collaboration, and individual perceptions through structured surveys and classroom observations. The collected data will provide insights into pupils’ confidence and participation levels, guiding refinements to enhance inclusivity.