Mattern, Paul

Jann Paul Mattern is a post-doc at the Department of Ocean Sciences at University of California, Santa Cruz. By bringing together observations of ocean properties and computer models, he uses mathematical techniques to investigate changes in ocean physics and biology. Paul is currently anticipating to continue his academic career, pursuing two of his passions, research and teaching. PDP has greatly helped Paul to design and teach a graduate-level course already and he is looking forward to continue using the skills gained in his PDP training in his future teaching experience.   jmattern@ucsc.edu

Teaching Activity Summary

Name of Teaching Activity: Statistical significance using p-values

Teaching Venue & Date: Full graduate level course with 2 classes per week. The course "Python programming for Ocean Scientists"

Learners: 5 grad students

Reflection on how learners engaged with a STEM practice during the inquiry:

One of the core practice goals for the course was focused on learners building algorithms, i.e. translating a given task into a logical flow of instructions expressed in the Python programming language. Specifically, this goal contained two major components: (1) developing the algorithm in a more abstract sense, and (2) implementing it in a practical application using Python. Both components are essential to building the algorithm, and dependent on each other. For example, tools available in the Python programming languages that are known to the learners may inform the development of the algorithm. I expected the second component (2) to be more challenging and therefore require more facilitation because all learners expressed they had worked with other programming languages before.

I designed an extended worksheet problem, split over several worksheets, specifically aimed at this practice goal. The problem included the examination and analysis of a dataset contained in a long text file, a task that was difficult to perform manually, without the help of a computer. The worksheet problem itself proved to be a useful tool for engaging the students. One of the steps required to find the solution involved developing a relatively complex algorithm. I had focused the facilitation more on the implementation component (2) and realized in class that the learners had struggled with the algorithm development (1). In response, we developed a flow diagram of the algorithm in the following class. This mapping step greatly helped some learners understand the mechanics of the algorithm and "how a computer thinks" to write algorithms in the future. This is an aspect I would now change by including the flow diagram earlier, thereby making the learners develop and understand the algorithm first before attempting to implement it.