This thesis will focus on the integration of AL into Artemis. We will use theoretical research and a requirements analysis to create a software design based on the existing architecture of Artemis. The proposed design will be implemented in the LMS. Finally, the thesis will document the analysis of the current state, the requirements engineering process, and the development of the features proposed in this section. Artemis is open source and available on https://github.

Abstract TBA

In the evolving landscape of computer science education, the burgeoning student population necessitates a shift from traditional teaching paradigms. The Artemis teaching platform, with its interactive learning approach, offers a scalable solution for large courses. However, a notable challenge remains: the uniform distribution of programming exercises, regardless of individual student proficiency. Recognizing the diverse skill set and learning needs of students, this master thesis proposes a transformative solution — the utilization of Generative Pre-trained Transformer models, particularly Large Language Models (LLM), for adaptive programming exercise generation.

Online educational platforms, including Coursera, Udacity, edX, and Khan Academy, offer diverse courses and rely heavily on exercises to reinforce learning. Among these, the Artemis platform from the Technical University of Munich has introduced specialized programming exercises. However, a pressing challenge is the time and effort instructors invest in creating these exercises. This bachelor thesis, supervised by Prof. Dr. Stephan Krusche and advised by Patrick Bassner, M.Sc., proposes the integration of OpenAI’s GPT-4 into Artemis to assist instructors in generating programming exercises.