基于人工智能的干预措施，以提高本科 STEM 学习。
An AI-based intervention for improving undergraduate STEM learning.
机构信息
Electrical and Computer Engineering, University of Nebraska-Lincoln, Lincoln, NE, United States of America.
Depts. of Community & Population Health, and Computer Science & Engineering, Lehigh University, Bethlehem, PA, United States of America.
出版信息
PLoS One. 2023 Jul 19;18(7):e0288844. doi: 10.1371/journal.pone.0288844. eCollection 2023.
Abstract
We present results from a small-scale randomized controlled trial that evaluates the impact of just-in-time interventions on the academic outcomes of N = 65 undergraduate students in a STEM course. Intervention messaging content was based on machine learning forecasting models of data collected from 537 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.
摘要
我们呈现了一项小规模随机对照试验的结果，该试验评估了即时干预对 N = 65 名 STEM 课程本科生学业成绩的影响。干预信息内容基于对前 3 年同一门课程中 537 名学生数据的机器学习预测模型。试验结果表明，干预措施显著提高了及格学生的比例。这些结果表明，即时干预在 STEM 学习中具有潜力和前景，需要进行更大规模的完全随机对照试验。
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