The UOL does not keep attendance records. However, active participation is only given if you are present in the course. This applies in particular to practical courses and seminars. Therefore, the following regulation applies to the course:

• We expect attendance for the duration of the course. In the case of minor absences (<20% of the attendance time), a message is sufficient (or subsequent notification in the case of illness) and active participation can be confirmed.
• In the case of planned absences > 20%, we ask you to attend the course at another time or to take another course.
• In the case of unplanned absences (e.g., due to illness) >20%, please contact the course management to discuss options.

In principle, the use of generative AI is permitted in teaching. However, the creation of an independent report or presentation is proof of active participation or even a graded examination. Therefore, the following regulation applies to the course:

• The use of AI to generate text components must be presented transparently in accordance with scientific criteria.
• The verbatim adoption of text from generative AI must be marked as a citation.
• An independent work cannot consist mainly of quotations.
• Failure to comply with the above points is considered scientific misconduct. It will result in active participation not being recognised or an examination being assessed as failed.

Failure to comply with the above points is considered scientific misconduct. It will result in active participation not being recognized or an examination being assessed as failed.

University information on the use of artificial intelligence in teaching

To successfully pass the course, each participant must submit a term paper, which will be graded. The topic of the seminar paper is "`A model ... "'. The seminar paper should document the model in detail. This includes a working programme, a model description, a sensitivity study and a description and discussion of the results.

The seminar paper should be in the form of a publication. This means, that at least an introduction with a description of the objective, the model description, the model results including sensitivity analysis and a discussion should be included. Criticism of the course is also welcome (of course this does not affect the grade ;).

As is usual for publications, no programme text should appear in the text. The programme should not be printed out! Please send the source code by e-mail or hand it in on a USB stick. The model description should contain a short section on the technical implementation, i.e. integration method, time step etc..

It should be cited properly if necessary. Images must be properly labelled. This includes the axis labelling including units and, if necessary, a legend and the detailed caption. The caption should describe the image in such a way that the image content can be understood without the text.

The work should be written in such a way that an outsider can understand what was done, how it was done and what results were achieved. This also includes the specification of parameter values (create tables, don't forget the units!).

The programme code should also be documented in such a way that an outsider can understand the programme. The specification of units in the comments is particularly helpful here.

The term paper including the programme must be submitted by ... at the latest. Please send the report (pdf) and the programme (tidy complete programme folder as archive) by email. Please send the programme from your university account, otherwise it may get stuck in the spam filter.

The grading takes into account the term paper, the model and the implementation.
The following points are particularly important:

Model

• Runnability
• Freedom from errors
• Comments (explanatory, units)
• Structure
• Completeness

Report

• Model description
• Reference run (description of results, comparison with data)
• Sensitivity analysis
• Interpretation of results and discussion
• Images/captions
• Style and form