Leuphana Semester at College

In the interdisciplinary methods module, you will work with the students in your year on the basics of scientific theory and scientific methods. You will also be able to apply the knowledge you acquire in other modules of the first semester and in your further studies up to your final thesis. 

Against this background, the LECTURE pursues three objectives: Firstly, a sensitivity to the contingent nature of methods is conveyed. Methods and their social, disciplinary and epistemological references are presented in terms of the sociology, history and philosophy of science. The methods module links cultural studies, education, economics and sustainability with the topics of data and responsibility. Secondly, the basics of qualitative and quantitative research methods are taught. The main features of the respective approaches, the (partly implicit) theoretical premises and the consequences of the respective choice of method are explained. Thirdly, the methods module teaches the skills needed to reduce complex teaching content as a basis for the following years of study.

In the module, you will learn the basics of applied data and AI literacy. Starting with an introduction to programming with Python, you will learn how to analyse data with Python and immerse yourself in the world of machine learning. In doing so, you will not only deal with the technical dimension of data and AI. You will also learn about examples of the diverse application contexts of data and AI and develop a basic understanding of the complex social and cultural changes that go hand in hand with them.

The AI Literacy module consists of a LECTURE and an EXERCISE. Both formats follow a blended learning approach that combines joint attendance phases and individual online learning formats. In a typical event week, you will prepare individually for our joint attendance sessions in the lecture and the exercise. For this purpose, we provide you with coordinated learning content in the form of texts, videos and Jupyter Notebooks via online tools such as Moodle and our AI hub.

While you will be introduced to the central concepts of data and AI literacy in the lecture, we encourage you to apply your new knowledge directly in the exercises. This way, you will not only improve your technical skills, but also engage with important social issues related to the responsible use of data in the 21st century.

In the Transformation module, you will deal with fundamental questions of responsible action in the 21st cent. and concretize this in the context of sustainable development, also against the background of the role of science in shaping change processes. Through a critical examination of both historical developments and current social conditions, you will discuss topics related to the conditions of social coexistence and their relevance for shaping present and future societies.

The LECTURE covers the broad arc and sets the topics to which the individual seminars and exercises are assigned. The examination of individual topics is carried out both from a historical and a more future-oriented perspective in order to make connections visible to students. The aim is to provide an overview of social transformations, with the seminars and exercises providing more in-depth coverage.

The EXERCISE asks about the cultural, social and historical conditionality of current conditions and peculiarities of social coexistence and thus tends to look back. It is less about developing new ideas and solutions than about classifying existing theories, models and attempts to explain contemporary phenomena. The focus is thus on critical thinking and reflection skills in order to be able to assess one's own thinking and the thinking of others. This focus is accompanied by an intensive introduction to essential elements of scientific work, such as developing research questions, researching literature, understanding arguments, etc., with a focus on writing didactics.

In the more action-oriented SEMINAR, which focuses on problem-solving skills, current conditions are considered with a view to the future and possible solutions to current social challenges. The seminar is conducted in a research-based learning mode, i.e. you will work in groups on your first research projects, from developing a research question and writing an exposé to conducting the project and then presenting the results at the conference week.

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In the Introduction to Fundamentals module, you will receive a substantive introduction to your area of specialization. Over the course of the first semester, you will gain insight into your specific field of study and develop an overview of the related subject areas. At the same time, you will learn to apply the knowledge acquired in the interdisciplinary modules to your specific field.

In the Methods (Subject-Specific) module, you will learn which methods you must master in your major or teaching subjects. This way, you will gain an overview of the methods as early as the first semester while simultaneously practicing their application.