Democratizing Access to Core Mathematics Across Grades 9-12

Principal Investigators
Stephen Hegedus, UMass Dartmouth
Brenda Berube, UMass Dartmouth (Co-PI)

Funding
US Department of Education: Institute of Education Sciences
$2,300,000

Abstract

The US Department of Education has funded a 4-year longitudinal study ($1,979,295) that builds upon 12+ years of research funded by various NSF grants, collectively known as the “SimCalc Projects.” SimCalc Connected MathWorlds (SCM) combines two innovative technological ingredients to address core mathematical ideas in deep and sustainable ways for mathematics learners. Software that addresses content issues through dynamic representations and, wireless networks that enhance student participation in the classroom. We have begun to develop materials that fuse these two important ingredients in mathematically meaningful ways and aim to revise and develop new curriculum materials to replace core mathematical units in Algebra 1 & 2 at high school for the purpose of transforming students’ experiences in deep and sustainable ways. We will measure the impact of implementing these materials on student learning, and high-stakes State examinations in local districts in Massachusetts. This will enable us to assess student’s likelihood of entering university and hence the impact of our program on enabling students to get past the “algebra bottleneck”; an issue of national concern and security.

Our work will be conducted in a wide variety of school settings. Eight school districts have agreed to participate in the study (New Bedford, New Bedford Vocational, Dartmouth, Fairhaven, Westport, Wareham, Dighton-Rehoboth and Old Rochester Regional), a mix of urban and smaller town schools in the South Coast Region of Massachusetts. Their State mathematics performances range from low (63% less than proficient) to Very High (22% less than proficient). We wish to work with such a diverse mixture of students to investigate whether our materials can aid all students; not just low achievers. More than half of the students in New Bedford (62.7%) are classified as low-income. New Bedford, and many of the region's suburban towns have educational attainment levels that are below state averages. Low income figures in our participating schools range from 5% to 65%. Percentage of African American or Latino from 2% to 37%. Our hypothesis is that students will be more intrinsically motivated to want to further their study of mathematics in 11th and 12th grade and so increase the number of students entering universities in MA to study mathematics and science degrees. We will track retention rates of students across their whole high school career. Our aim is to democratize access to a wider variety of students, a deeper and more sustainable understanding of mathematics that informs them of why mathematics is an important part of their life. Through this intervention and study, we will expect to see increases in numbers of students (particularly minority students given our participant districts) entering university (particularly at UMass Dartmouth) aiming to pursue a degree program in mathematics, science or engineering.

Intervention: Software, curriculum materials & teacher training to replace 8-12 weeks of Algebra 1 materials and 6-8 weeks of Algebra 2 materials. We will collect similar pre-post test and survey data from two classrooms per school (randomly selected). They will be using their existing curriculum (e.g., Bellman et al, 1998). We will occasionally conduct classroom observations. Our treatment interventions will be in 9th and 11th grade classrooms but we will also track some students when they are in 10th and 12th grade collecting simple questionnaire data. Our study will be a small-scale cluster randomized experiment where we cluster at the classroom level, randomly assigning two teachers in each school to treatment in our main studies. We will use an instrument comprised of standardized test items to measure student’s mathematical ability and problem-solving skills before and after each intervention and analyze it using mixed-HLM and ANCOVA methods. We will also collect survey and classroom observation data to assess changes in attitudes to learning mathematics, classroom participation and motivation.