Warning! The directory is not yet complete and will be amended until the beginning of the term.
290131 UE Modelling in Physical Geography (2017W)
Continuous assessment of course work
Labels
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Sa 02.09.2017 07:00 to Mo 25.09.2017 07:00
- Deregistration possible until Mo 16.10.2017 07:00
Details
max. 30 participants
Language: English
Lecturers
Classes
2. October 2017: 8:00 - 10:30 AM
9. October 2017: 8:00 - 12:00 AM
16. October 2017: 8:00 - 10:30 AM
23. October 2017: 8:00 - 10:30 AM
30. October 2017: 8:00 - 10:30 AM
6. November 2017: 8:00 - 12:00 AM
13. November 2017: 8:00 - 10:30 AM
20. November 2017: 8:00 - 10:30 AM
27. November 2017: 8:00 - 10:30 AM
4. December 2017: 8:00 - 10:30 AM
Information
Aims, contents and method of the course
Assessment and permitted materials
Attendance, Homework, Examination, Term Paper
Minimum requirements and assessment criteria
- Attendance (absence on max. 2 units)
- Homework (positive evaluation of min. 3 out of 5 for admission to the examnination)
- Examination (50% of final grade; 60 minutes)
- Term Paper (50% of final grade; 4 pages, in terms of a technical report)
- Homework (positive evaluation of min. 3 out of 5 for admission to the examnination)
- Examination (50% of final grade; 60 minutes)
- Term Paper (50% of final grade; 4 pages, in terms of a technical report)
Examination topics
- Basic knowledge about the presented theoretical contents of processes in physical geography --> Examination
- Evaluation of modelling results and structural summary in terms of a technical report --> Term Paper
- Evaluation of modelling results and structural summary in terms of a technical report --> Term Paper
Reading list
Provided via Moodle.
Association in the course directory
(MG-S1-PI.m, Block A) (MG-S2-PI.m, Block A)
Last modified: Mo 07.09.2020 15:42
- Basic knowledge about static and dynamic modelling processes
- Knowledge about digital data pre-processing
- Autonomous application of models and manipulation of model codes
- Ability for reliable assessment and interpretation of modelling results