assessment.md

Assessment:

During this course, you will work in teams on a project. The education is supported by python notebooks, which will help you with the fundamentals of the software environment we will use during the course. The idea, however, is that you work as a team on a project. The evaluation is assessed through a metric.

The minimum score to pass is 55 points, which will translate to a 6.0 as a final score (note that a score of 56 to 64 will also result in a final score of 6.0). The rest of the scores are determined by linear interpolation and rounding to integers and half points.

As deliverables for the course, we expect you to:

• Participate in weekly paper and topical discussions. The list of papers can be found here. These correspond to a pass/fail grade.
• Present with your team the results of your project (Each team member should get the opportunity to speak).
• Have a clear and clean git repository.
• Write a project report of less than 2001 words (including captions) with at most 7 figures.

Requirements for each of these ingredients:

• Presentation. On December 17th you and your team will present your results in a 10 min presentation + 5 minute for discussion. Note that the other teams will also present their work, and your participation (by asking questions and joining the discussion) during this session is important for your final score.
• A git that can be used to reproduce your results.
  • All scripts are required to run your simulations and make your plots. They should be .py format.
    • Make sure they run on any system, so there are no system-specific file paths! You can always use an option parser.
  • A README that instructs which scripts to run in which order.
  • If your runs are expensive, think about including a way to run a simple example (e.g., low resolution, a single point in parameter space).
• A more extensive written report (delivered in the form of a .pdf file) should be presented. The report should not contain the source code (which is in the python notebook and on the git repository) but should contain an:
  • Introduction with a motivation for the selected topic
  • Assumptions with a description and motivation for the various ingredients and their coupling (should include a flow-chart and doodle of the astrophysical setup)
  • Choice of model parameters and initial conditions (with a doodle of the initial parameter space)
  • Results (at least two figures showing results).
  • Discussion (should contain a discussion on the caveats and future prospects).
  • Conclusions (if any).

The minimum score for this course is 0 points, and the maximum score is 100 points. Your final score will be your score divided by 10. A score of 54 points will result in failing the course.

Passing grade is 6.0 or at least 55 points.

The score you receive is a team effort. In principle, each team member receives the same score. This is not always fair, as team members may put different efforts into the project. If you are a team member with a large range of expertise or dedication, please talk to the teacher, and we'll see what we can do.