D. Moritz Marutschke

Education

Ph.D. in Culture and Globalization (Information and Communication Science), Kobe University

M.Eng. in Human Information Science, Ritsumeikan University

Message to Students

We live in times where we hear the words "Artificial Intelligence" or "Data Science" almost daily. These might evoke excitement, annoyance, or even dread and a deeper understanding of scientific concepts seem reserved for technical colleges.
At GLA, you will have the opportunity to get exposed, both practically and conceptually, to AI tools and data science practices. We will peek behind the curtain to appreciate both the technological advancements and shortcomings.
I am looking forward to welcoming you at GLA to exploring these cutting-edge technologies within liberal arts contexts!

Courses Taught

• Introduction to Algorithms and Programming
• Applied Data Curation
• Special Lecture (Social Change with AI)
• Special Lecture (Prototyping of Wearable Technology)
• Research Seminar
• Thesis

In the course Introduction to Algorithms and Programming, students will be exposed to the concept of informal algorithms and computer algorithms and will learn essential skills to write their own small computer programs.

The course Applied Data Curation teaches students about the data lifecycle. Students will learn crucial concepts in data collection, processing, maintenance, and preservation.

The Special Lecture on social change with AI, students will learn how artificial intelligence has shaped and continues to shape different aspects in society. Case studies from business, finance, security and surveillance, entertainment, and research are investigated.

Technology is part of our daily lives and concepts like ubiquitous computing seem to belong to yesterday. In the Special Lecture on prototyping wearable technology, students explore the process of planning, implementing, testing, and presenting an Internet of Things (IoT) device.

Research Interests

Data Science, Artificial Intelligence, E-Learning, Educational Technology, Software Engineering Education

My research interests are in E-Learning, Data Science education, and the use of Artificial Intelligence in multidisciplinary projects. Recent projects include the use of Large Language Models in understanding basic color terms in multiple languages, technology enhanced learning, and UML usage in distributed software engineering courses.

Supervision Information

I am happy to supervise research projects and theses related to the following topics: Artificial Intelligence (practical and conceptual), Natural Language Processing, Trend Analysis (Fashion, News, Society), Colors and Culture, Technology Enhanced Learning

Representative
Publications

• Daniel Moritz Marutschke, Patricia Brockmann, Tri Astoto Kurniawan, Mate Kovacs, Victor V. Kryssanov, "Multicultural Observations in a Three-University Global Distributed Software Development Course: A UML Case Study", The 6th World Symposium on Software Engineering (WSSE 2024), ACM, pp. 115–120, 2024
• Daniel Moritz Marutschke, Muhammad Riza Nurdin, Miwa Hirono, "Quantifying Social Capital in Post-disaster Indonesia: Methodological Innovation by an AI-Based Language Model", Disasters, e12631, 2024
• Editors: D. Moritz Marutschke, Atsuo Hazeyama, and Hironori Washizaki, "35th IEEE International Conference on Software Engineering Education and Training (CSEE&T 2023)", IEEE Proceedings, 2023
• Daniel Moritz Marutschke and Yugo Hayashi, "AI-Supported Evaluation of Kano Model Features for Online Courses", ICIC Express Letters - An International Journal of Research and Surveys, Vol. 16, No. 5, pp. 505–512, 2022
• Daniel Moritz Marutschke, Victor V. Kryssanov, and Patricia Brockmann, "Balanced, Unbalances, and One-Sided Distributed Teams - An Empirical View on Global Software Engineering Education", IEICE Transactions on Information and Systems Journal, Special Section: Empirical Software Engineering, Vol. E105-D, No. 1, pp. 2–10, 2022