Project Spotlight: Predicting STEM Career Choice from Computational Indicators of Student Engagement within Middle School Mathematics Classes

Project Spotlight: Predicting STEM Career Choice from Computational Indicators of Student Engagement within Middle School Mathematics Classes

Friday, February 13, 2015

STELAR recently had the opportunity to interview Ryan Baker about his ITEST Project, Predicting STEM Career Choice from Computational Indicators of Student Engagement within Middle School Mathematics Classes,  which is examining how "disengagement" predicts later outcomes of STEM learning and career advancement.

1) Can you share how your ITEST project impacts youth?

We are studying how student engagement, emotion, and learning within middle school mathematics can predict long-term student outcomes, including end-of-year standardized exam results, college attendance, and college major. This project impacts youth by creating better understanding of malleable factors that can improve student outcomes, and automated models that can identify if a student is at-risk, and which areas a specific student needs support in.

  1. 2) What do you think is your most important learning in this area based on your project work to-date?

We have determined that several aspects of student engagement in middle school are predictive of long-term outcomes. For example, students who intentionally misuse educational software in middle school are less likely to enroll in college, and are less likely to major in careers involving math and science. By contrast, students who experience engaged concentration during middle school math are more likely to enroll in college.

3)  What kinds of STEM experiences best support student competency, motivation and persistence?

Students who experience positive engagement and emotion during mathematics activities are more likely to attend college and major in STEM careers than other students.