Augmenting, Piloting, and Scaling Computational Notebooks to Train New Graduate Researchers in Data-Centric Programming


“Virtually all graduate STEM training programs are currently confronting challenges to ensure their students have the computational skills required to function in increasingly data-intensive research domains,” observed Hollan (original PI) in the proposal. “One singularly important challenge in the current era of big data is the growing need to train new graduate students in the programming and data analysis skills needed to be able to manage and exploit large-scale data in virtually every domain.”

The Design Lab team proposed to take the popular concept of introductory “bootcamps” for new grad students, and to scale that approach while exploiting the growing movement of computational notebooks. Specifically, the researchers proposed to augment the Jupyter Notebook, a widely used open-source web application, with other pedagogical tools to support training in data-centric programming in a wide range of STEM disciplines.


> Read the abstract

> Learn more with UCSD’s Design Lab page


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