Project Details
Description
This project aims to serve the national need of recruiting, preparing, and retaining a robust and diverse workforce of secondary mathematics teachers who implement culturally responsive mathematics instruction in high-need schools. The project directly addresses the documented nationwide shortage of secondary mathematics teachers and the high faculty attrition experienced by schools serving high-need communities. It seeks to build a teacher education program that will prepare prospective teachers to teach secondary mathematics using innovative teaching approaches that combine mathematical modeling, emerging technologies, and culturally responsive practices. The project involves hands-on coursework and rich field experiences in secondary classrooms at partner schools. These experiences have the potential to build preservice teachers’ skills in teaching mathematics and in meaningfully incorporating students’ cultural backgrounds and home languages in school learning. A comprehensive induction support system will include mathematics coaches who will provide instructional and social-emotional support to the secondary mathematics teachers to promote their retention in high-need schools upon completion of the project. Project outcomes include the certification of secondary mathematics teachers who will be supported into careers in high-need schools, and the establishment of a vigorous teacher education program that will continue to fill documented workforce shortages even after the conclusion of funding. This project at Penn State Harrisburg (PSH) includes partnerships with Harrisburg, Central Dauphin, Middletown Area, Steelton-Highspire, and Susquehanna Township School Districts. Project goals include enhancing the current teacher certification program and increasing the number of certified secondary mathematics teachers who will be well prepared to make a positive difference in secondary students’ learning of mathematics through long-term careers in high-need classrooms. The project is particularly focused on recruiting 16 racially and ethnically diverse prospective teachers (scholars) over five years who are undergraduate mathematics majors or post-baccalaureate candidates who have an undergraduate degree in mathematics or other STEM disciplines. Additional project outcomes include a positive impact on the scholars’ self-efficacy beliefs towards culturally responsive mathematics teaching and their capacity to select, design, and implement mathematical-modeling activities in high-need classrooms. The project builds on research that demonstrates that planning for diversity can promote higher student engagement and performance. The project’s broader impacts include preparing secondary mathematics teachers who can develop mathematical-modeling activities that leverage students’ cultural and linguistic capitals, along with emerging technologies, to support students’ active engagement in and learning of mathematics. The innovative mathematics curriculum that results from the project will be shared through a project website, the university scholarly repository, professional-development offerings, publications, and presentations at state and national mathematics education conferences. This Track 1: Scholarships and Stipends project is supported through the Robert Noyce Scholarship Program (Noyce). The Noyce program supports talented STEM undergraduate majors and professionals to become effective K-12 STEM teachers and experienced, exemplary K-12 teachers to become STEM master teachers in high-need schools. It also supports research on the persistence, retention, and effectiveness of K-12 STEM teachers in high-need school districts.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.
Status | Active |
---|---|
Effective start/end date | 2/15/22 → 1/31/27 |
Funding
- National Science Foundation: $1,200,000.00
Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.