EOSC 410/510

Official course description

Geoscientific Data Analysis and Empirical Modelling: Application of data analysis and empirical modelling strategies for conducting a data-oriented research in geosciences; from setting research questions and hypothesis to delivering and interpreting results. Examples are drawn from across the Earth, ocean, atmospheric and planetary sciences.

Links: >Home, >UBC Calendar, >ubcexplore, > EOAS curriculum map.

NOTE: EOSC410 and EOSC510 are undergraduate and graduate versions of the this course respectively. They are taught jointly with grads and undergrads meeting different expectations during grading of assignments and projects.

OCESE project objectives

Actions taken

This course is taken by both undergraduate and graduate students, and their computing experience ranges from nothing to extensive. The number of students identifying specific coding experience by product is summarized here. The number of types of experiences identified by each student ranged from none to nine different coding products or environments.

Students were also asked what computing & math courses they have taken, and what earth science courses or experiences they have had. The result demonstrates that this course is taken by a very diverse variety of students, from those with significant (graduate school level or more) experience in Earth sciences and/or computing, to those with no Earth science background at all, and even no computing background.

The lesson to an instructing team of such a course is that the computing environment for learning will be critical, and every effort should be made to ensure students are able to focus on the course priorities without getting bogged down in simply learnign about programing. This is why the choice was made to use Python. Ideally, learning activities and assignment can be deployed as Jupyter Notebooks using a “prepared” environment such as UBC’s “open Jupyter” hub.

Students were also asked agree/disagree questions to characterize their expectations abut the course. These data are summarized here.

Lessons learned

The OCESE project did little to contribute towards development or improvement of this course, other than to run surveys to learn about student experiences and perspectives, and to discuss options for use of Python and Jupyter notebooks.

There was a complete set of notes and assignments generated by graduate student Chris Rodell while he was a student in the course. The repository for this EOSC510 resources collection has a BSD-3-Clause license, and can be seen here.