SBIR Phase II: Integrating Cognitive and Self-Regulatory Strategies to Improve Secondary Mathematics Outcomes

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The broader impact of this Small Business Innovation Research (SBIR) Phase II project will be improvements in math instruction, engagement, and outcomes through a holistic approach to supporting social-emotional (SE), cognitive, and academic skills in general education classrooms. By integrating these sources of student-specific data, teachers will be able to effectively identify and address additional factors that interfere with understanding, retention, motivation and engagement, all of which are critical to academic outcomes. This data-driven, scalable approach will pinpoint individual causes of students' mathematics struggles and provide evidence-based, personalized interventions. The potential to improve stagnant mathematics achievement outcomes at scale would translate directly into economic benefits to the country. The innovation is expected to have the greatest effect on minorities and girls whose motivation and engagement in STEM are disproportionately impacted by implicit biases and stereotype threat. This Small Business Innovation Research (SBIR) Phase II project will enable teachers with the data to address student variability across cognitive, SE, and academic skills, leading to increases in student engagement and math achievement. This project leverages research that cognitive assessment and student SE self-reports can explain over 60% of middle school math outcomes. This project will demonstrate the specific evidence-based, personalized interventions for engagement, social-emotional learning, and academic instruction to improve math outcomes for individualized learner profiles. This approach will advance the current state of research on engagement by addressing individual differences in cognitive and SE skills. This research will feature a longitudinal randomized control trial with a large sample representing a broad range of socio-economic status, race, and ethnicity. This rigorous design will develop the predictive validity and ability to effectively address learner variability, as well as demonstrate outcomes in diverse student populations.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.