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Summer Research Series: Computer Science pioneers take programming data for a spin

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This summer, Emmanuel College's pioneer Computer Science students are "learning about learning."

Emmanuel College’s summer research program offers students and faculty alike the distinct opportunity to collaborate on scholarly work. This summer, 56 students across 11 disciplines and all five Academic Schools are conducting research with faculty. Through this series, we will highlight student and faculty research going on throughout the summer, which will conclude with a special poster session in the fall.

Assistant Professor of Computer Science, Dr. Mark Sherman, discusses summer research with Erica Hinkle '26 and Molly Hans '25 (online).

As part of Assistant Professor of Computer Science and Director of Emmanuel’s Integrated Digital & Data Sciences initiative Dr. Mark Sherman's ongoing research, Molly Hans ’25 and Erica Hinkle ’26 have been diving into programming students’ data. 

The project, which analyzes the students’ keystrokes in a programming course, aims to identify when a student is struggling on a problem and indicate that they need guidance.

The work from Hans and Hinkle has been key in moving the project along – and it’s the first time Sherman has had Computer Science majors working with him on his research. “Turns out that’s useful,” he said; “it’s keeping me on my toes because they’re cranking through this work.”

Emmanuel College launched its Computer Science major in Fall 2023. Hans and Hinkle have been excited to be two of the first to experience it at the College, now practicing their programming skills in a research setting rather than the classroom – which they said has been different, but in a good way.

“

It's taught us a lot along the way. The application of it [programming] is so specific, it's a useful taste of what the work is like in the real world, not just in class."

Molly Hans '25

With the Cambridge-based programming learning platform Codio, they have analyzed students in a Stanford University programming course and sifted through the data to determine when any of those students are “spinning.” A student who is “spinning” is struggling on a programming problem and not making adequate progress toward the answer. For example, “it may look like they’re working hard – but they’re not working well,” said Dr. Sherman.

At this point in the project, they’re able to identify a spinning student fairly easily, as well as chart how they come to their conclusion on the given problems. The next step is pulling out patterns and implementing an AI tech model to deduce those patterns for itself. If the model can start to pick up the patterns on its own for the given programming problems, it could potentially be applied to a broader range of problems and used to support students even further in the future.

“We’ve come a far way already,” Hinkle said, as the team prepares to make use of more of their data. They’ve compiled the work of 50 students into a data set to get the system up and running, but it’s only a piece of their six months of data they have – which is around 1,000 students – that they will continue to incorporate.

There hasn’t always been a clear solution or answer for the challenges of the research, but by applying the skills they’re learning in the classroom, they’ve been able to tackle those questions and do their own problem solving with Dr. Sherman’s guidance.

But the best part of all the research so far? For Hans and Hinkle, it’s been actively pursuing and practicing their love of programming.

“We genuinely love it – the days of programming are genuinely the best days,” Hans said.

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