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Ph.D. student Jesse Harden’s current research is focused on large, high-resolution displays and their use in and benefits for data science.

“I am particularly interested in how we can better design software for large displays for data science. And in the future, I hope to look into how machine learning can be used to improve interactions with large screen UIs for both individual and collaborative use scenario,” said Harden, whose concentration in this area was influenced by reading the past works of his advisor, Chris North, and through their subsequent discussions.

Harden’s prior research is focused on minimizing instructor effort in automating feedback for computer science education.

“Given the time constraints that instructors have, making it easier and quicker to specify pattern-matching tests that give appropriate feedback can enable them to write more in-depth automated feedback tests which may, in turn, help student learning,” he said.

He developed a specification language — that currently works for Pedal, a feedback infrastructure for Python — to make it easier for busy instructors to create tests coupling mistake patterns with feedback.

Harden’s paper on this topic, “A Specification Language for Matching Mistake Patterns with Feedback,” was published last week in the proceedings of the 2021 SIGCSE 52nd ACM Technical Symposium on Computer Science Education.

Harden earned a bachelor’s degree in mathematics with a concentration in statistics, and a master’s degree in data and information management, both from Radford University.

Looking at Ph.D. programs in computer science, Harden said he was attracted to Virginia Tech and the Sanghani Center by several factors: “great people, great opportunities, and great location.”

Before making a final decision, Harden said he had quite a few great interactions with both current students and professors which helped him solidify his choice.

“Now as a Ph.D. student at the Sanghani Center, I like being able to work with very knowledgeable individuals on interesting challenges and the benefit of available funding opportunities,” he said.

Harden is projected to graduate in Spring 2024 and would like to pursue a career in academia as a professor.