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Preparing the Effective Elementary Mathematics Teacher

NOYCE team 2022
Our current scholars include (front left to right) Emily Perez, Arnold Rosas, Tania Lopez Robles, Caitlin Lobosco (graduated), Hunter Smith, Gianna Fazzini, and Amber Hammond. Our scholars are supported by faculty advisors (rear left to right) Dr. Joseph DiNapoli, Dr. Steven Greenstein and Dr. Jennifer Robinson.

An Update on the Noyce Scholarship Program

Scholarship Flyer

Noyce Program Flyer

Goal of the Noyce at Montclair Mathematics Project

This scholarship program aims to Prepare Effective Elementary Mathematics Teachers. We provide exemplary preparation to students for effective elementary mathematics teaching in high-need K-12 educational settings. Our scholars obtain an undergraduate degree in mathematics along with a K-6 elementary teaching certification. Each Noyce @ Montclair scholar receives $15,000 (to cover tuition and fees) and a $10,000 stipend each year for two years with additional money available for local conference travel and digital backpacks. In return for the funds, students agree to work two years in a high-needs school for each year of funding received (if you receive funds for two years, you would teach in a high-need setting for four years).

Noyce Scholar Testimonials

Program Components

BS in Mathematics with K-6 Teaching Certification

Noyce Scholars obtain an undergraduate degree in mathematics along with K-6 teaching certification. This degree program consists of the same core mathematics coursework as other BS mathematics degrees with some substitutions for meaningful alignment to elementary teaching.

Inquiry-based Instructional Supplement

In this workshop model, students are exposed to inquiry-oriented, group-worthy problem sets for Calculus I and Calculus II that are designed to promote students’ problem-solving activity and give workshop leaders experiences facilitating inquiry-oriented group work in mathematics.

Early and Ongoing Field Experience

Field experiences are specifically designed to align with the philosophy of this program and provide community knowledge-building efforts that support pre-service teachers as they assimilate a broader notion of the “field” to include the community that houses the school in which they observe or teach.

Undergraduate Research Experience

In our effort to familiarize scholars with research, MATH 491: Research in Mathematics Education is an elective that provides students with undergraduate research experience.

Induction Support

three-year induction program supports each scholar’s transition into full-time teaching through site-based coaching and mentoring, social/networking events, and ongoing professional development for teaching and leadership.

Who Is Eligible?

  • Undergraduate students enrolled in the program leading to a Mathematics degree with K-6 teacher certification (MAEL)
  • Juniors and Seniors admitted to the Teacher Ed. Program must have a 3.0 overall GPA, 2.75 mathematics GPA
  • Eligible applicants should apply to the Noyce Scholarship program at the same time that they apply to the Teacher Ed. program.
  • Search the Teacher Cancellation Low Income (TCLI) directory if you wish to determine which schools are labeled “high-needs.” There are a lot of them, which is why we need you!

Applicants for this scholarship program should apply at the same time they apply for admission to the Teacher Education program. The fall application deadline is September 15; the spring deadline is February 1.

Learn more about the Undergraduate Teacher Education Program and eligibility criteria and application process for the Teacher Ed program.

Contact

Steven Greenstein profile photo

Steven Greenstein

Associate Professor, Mathematics

Phone
973-655-4287
Email
greensteins@montclair.edu
Location
Center for Computing and Information Science, 425K
Joseph DiNapoli profile photo

Joseph DiNapoli

Associate Professor, Mathematics

Phone
973-655-6802
Email
dinapolij@montclair.edu
Location
Center for Computing and Information Science, 425B

This material is based upon work supported by the National Science Foundation under Grant Number 1660719. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.