Experiment finds AI-based intervention helps undergrads pass STEM course

Artificial intelligence

Scott Schrage, November 17, 2023

Experiment finds AI-based intervention helps undergrads pass STEM course


Welcome to Pocket Science: a glimpse at recent research from Husker scientists and engineers. For those who want to quickly learn the “What,” “So what” and “Now what” of Husker research.

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U.S. college students majoring in STEM fields currently graduate about 20% less often than their non-STEM peers, a resounding clarion call for better assisting those students, especially in their first few semesters. Though systemic, long-term shifts — away from lecturingtoward the sharing of evidence-based teaching practices — should help, the inertia of academia can sometimes slow their adoption.

Some educators and researchers have looked to supplement those grander shifts with a few nudges in the right direction. One promising candidate: periodic interventions designed to help struggling students find their way.

So what?

Nebraska’s Mohammad Hasan and former Husker Bilal Khan recently investigated whether machine learning — a form of AI that can identify patterns in data, then use that learned recognition to forecast outcomes — might contribute to the cause. To start, Hasan and Khan trained a model on the homework, quiz and midterm scores, along with the final grades, of 537 Husker students who took a computer science course between 2015 and 2018.

Portrait of Mohammad Hasan

Later, they applied the model to a class of 65 undergrads enrolled in that same course. At three points in the semester — six weeks, nine weeks and 12 weeks in — 32 of the students received an automated message via the university’s course management system. That message relayed the model’s projection of a student passing the course: “Good,” “Fair,” “Prone-to-Risk” or “At-Risk.” The remaining 33 students, those in the control group, always received an “Unable to Make a Prediction” message.

Among the control group, 24 of 33 students — roughly 73% — passed the course. Those who received actual forecasts based on their trajectories, meanwhile, fared substantially better: 29 of the 32 students passed, good for a rate of nearly 91%. And of the surveyed students who reported actively checking their status, 86% said they increased their effort after seeing the forecasts.

Now what?

Hasan and Khan said the findings, though early, point to the value of integrating AI-based interventions into STEM courses. The duo plans to conduct a larger, longer-term study that could help determine whether variables beyond scores — course-related behaviors, perceptions of science, demographics — might generalize and expand the use of the interventions beyond a single uniform course.

Artificial intelligence Electrical and Computer Engineering