An AI-based intervention for improving undergraduate STEM learning
Principal Investigator(s): View help for Principal Investigator(s) Mohammad Hasan, University of Nebraska-Lincoln
Version: View help for Version V1
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Project Citation:
Hasan, Mohammad. An AI-based intervention for improving undergraduate STEM learning. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2023-02-08. https://doi.org/10.3886/E184642V1
Project Description
Summary:
View help for Summary
We present results from a small-scale randomized controlled trial that evaluates the
impact of just-in-time interventions on the academic experiences and outcomes of N=65
undergraduate students in a STEM course. Intervention messaging content was based
on machine learning forecasting models of data collected from 427 students in the same
course over the preceding 3 years. Trial results show that the intervention produced a
statistically significant increase in the proportion of students that achieved a passing
grade. The outcomes point to the potential and promise of just-in-time interventions for
STEM learning and the need for larger fully-powered randomized controlled trials.
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