Fostering STEM Engagement through Evaluation: Unveiling Key Predictors of Self-Efficacy and Career Interest

This presentation explores the use of participatory approaches and predictive modeling within evaluation to communicate findings of a STEM education program impacting over 41,000 students in the K-12 setting. The program engages students in hands-on science and engineering activities during after school and summer break. As external evaluators, we examined key predictors of students’ STEM self-efficacy and STEM career interests. Using multiple linear regression models, evaluation analysts identified key predictors influencing STEM self-efficacy. The analysis of findings revealed that age and school type significantly influenced students’ STEM self-efficacy. Using the findings from this project, evaluators will discuss how project leaders were engaged on effective practices to foster sustainable impact in education. The discussion will focus on actionable insights for future program improvement, emphasizing how evaluators can empower communities by collaboratively interpreting data with stakeholders. Attendees will gain an understanding of how evaluation can be leveraged to guide stakeholders’ decision-making.

Terrence Castillo; Kelly Correa