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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2019-Fall-CSCE235-All.csv text/csv 3.7 KB 02/08/2023 06:02:AM

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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V1 [2023-02-08]

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