What do you support?
We can help you in two broad areas. 1) To understand classwork and get through problem sets. We know that learning coding syntax and problem solving is not easy and while we will not give you all the answers, we hope to provide additional guidance. 2) We will provide brainstorming support for the code you are working on - what are ways to use computation to inform your experimental design, what is an efficient way to analyze data, what processes are used for high-throughput ‘omics analyses. We also hope to identify where we might be most useful in future initiatives. Don’t hesitate to reach out and ask if we can help with something you are working on.
What won’t you support?
First, if you come in for a class, we will not give you the answers. But we will help you work through the assignment. We also do not plan to debug code, meaning we anticipate challenges in answering questions such as “Can you fix my code?” or “Why doesn’t my code work?”. We can, however, help you learn how to debug your own code or to walk through your code to figure out how to identify problem areas.
Who are the fellows?
Our fellows are grad students in Biological Engineering labs who love computational thinking and do it on a day to day basis in their graduate work. They also have a passion for teaching and bringing new support to the department.
What is your educational philosophy?
We believe that learning how to code is really hard. And really the only way to learn is to do it (experiential), on something that is important to you (just-in-time), and in a way that is specific to your research (discipline specific). But we also know that it can be easier to learn if someone helps, in a step by step manner. So our goal is to work with you to learn and build code together.
What is your vision?
One day, we hope to create a resource that can help all students learn how to confidently work with the data they will see in their discipline. We want to train students to generate reproducible and ethical data for the betterment of science and society.
Have you officially launched?
Yes! - we ran a pilot phase in the spring of 2020, and have now fully launched as of Fall 2020 to support coding, statistics, and computational tools.
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