Sarah Veatch is the Associate Director of Graduate Studies and Professor of Biophysics and Physics at the University of Michigan.
She teaches Introduction to Scientific Computing, an interdepartmental programming course that introduces students to Python. With around 75 students per semester, Sarah's goal is to develop computational literacy in her students, giving them the foundation to succeed in future courses and empowering them to work independently. “It opens up doors for students to do things independently,” she noted, calling it “a really valuable skill.”
The Challenges Before CodeGrade
Before adopting CodeGrade, Sarah’s course faced several hurdles. The class, initially only 20-30 students, was easier to manage. However, as enrollment increased, the process of manual grading became slow and inefficient. “Students didn’t get the immediate feedback they needed, and if they got something wrong, they could fix it—but it was a large amount of work.” The course’s reliance on Jupyter Notebooks and manual grading meant a heavy workload for instructors, and as the class scaled up, this was no longer feasible.
Finding the Right Solution
In search of an efficient tool, Sarah conducted extensive research before selecting CodeGrade. One of her colleagues highlighted the value of CodeGrade being a bespoke solution, emphasizing its personalized effort to help educators succeed.
She also appreciated the cost-effectiveness of the platform: “In the beginning, I was worried it was going to be more expensive than other options, but when we did the math, it worked out about the same or even cheaper.”
Sarah praised the support she received from the CodeGrade team, highlighting the fast responses to her questions, even when dealing with more complicated issues. “The support has been amazing—that was very helpful.”