Predicting Student Participation in STEM Careers: The Role of Affect and Engagement during Middle School



Published Aug 23, 2020
Ma Victoria Quintos Almeda Ryan Shaun Baker


Given the increasing need for skilled workers in science, technology, engineering, and mathematics (STEM), there is a burgeoning interest to encourage young students to pursue a career in STEM fields. Middle school is an opportune time to guide students' interests towards STEM disciplines, as they begin to think about and plan for their career aspirations. Previous studies have shown that detectors of students' learning, affect, and engagement, measured from their interactions within an online tutoring system during middle school, are strongly predictive of their eventual choice to attend college and enroll in a STEM major (San Pedro et al., 2013; 2014). In this study, we extend prior work by examining how the constructs measured by these detectors relate to the decision to participate in a STEM career after college. Findings from this study suggest that subtle forms of disengagement (i.e., gaming the system, carelessness) are predictive and can potentially provide actionable information for teachers and counselors to apply early intervention in STEM learning. In general, this study sheds light on the relevant student factors that influence STEM participation years later, providing a more comprehensive understanding of student STEM trajectories.

How to Cite

Almeda, M. V. Q., & Baker, R. S. (2020). Predicting Student Participation in STEM Careers: The Role of Affect and Engagement during Middle School. Journal of Educational Data Mining, 12(2), 33–47.
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STEM participation, affect detection, knowledge modeling, educational data mining

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