Scope: Policy for the Foundation Modules of the Minor Digital Science (1-3a)
This policy applies to the modules (1) Introduction to Programming, (2) Introduction to Data Management, (3a) Data Analysis I.
Definition: Generative Artificial Intelligence (GenAI) tools are frameworks that create new content based on user input (prompts) and pre-trained neural networks. These tools can be accessed directly or through other frameworks, such as integrated development environments or web pages. Prominent examples are ChatGPT, GitHub copilot, etc.
Motivation: To successfully learn the basics of programming as well as the application of programs for data management and data analysis (and beyond), personal effort and practical experience are indispensable. Working hard and struggling is actually an important way of learning. Thus, to understand computational methods and their applications it is vital to personally carry out the key steps. This helps to consolidate theoretical concepts and prepares for the application to new and complex problems. This learning effect from personal experience (and sometimes struggle) cannot be replaced by letting GenAI generate code without understanding. Even if GenAI will become a valuable supporting tool in workflows later on, it is essential to first understand the underlying programming principles and computational methods. Only with this understanding the code generated by GenAI can be properly evaluated, debugged, and maintained.
Use: In the Foundation Modules (1, 2, 3a), GenAI tools are allowed to support active learning, but they are strictly prohibited in any assessments! All participants are encouraged to use GenAI in a balanced way that does not undermine their active learning and conceptual understanding. Guidelines for specific courses will provide further details. In case of doubt as to whether a particular tool is permitted in a certain context, the lecturer(s) should be consulted prior to using the tool.