This project will develop and investigate mathematics language routines focused on data science topics in middle and high school. The study will investigate teachers’ use of mathematics language routines and a professional development model to support teachers’ learning. The educational integration plan in the project will build mathematics teacher expertise and create video cases to support teacher professional development.
CAREER: Understanding the Routinization of Mathematics Language Routines in Middle and High Schools
Interpreting and analyzing data provides students problems that apply mathematics and statistics to their own experiences. Mathematics teaching about data needs to include opportunities for students to discuss and explain their mathematical reasoning and problem solving. Particularly for data science, students need opportunities to communicate and discuss their ideas. Mathematics teaching requires the ability to support that learning experience with multilingual students and learn to engage all students in mathematical problem solving. Data science presents a context for middle and high school students to examine data that is personally meaningful and relevant. The project will develop and investigate mathematics language routines focused on data science topics in middle and high school. The study will investigate teachers’ use of mathematics language routines and a professional development model to support teachers’ learning. The educational integration plan in the project will build mathematics teacher expertise and create video cases to support teacher professional development. Graduate and undergraduate researchers will also have opportunities to learn about education research and mathematics teaching.
The research focuses on core practices of mathematics teaching that are regularly incorporate in teachers’ interactions with students. The project uses a studio day model for teachers to have a professional learning experience closely connected to their work and guided by a district instructional specialist. The central concept of the study is the enactment of mathematics language routines (MLRs) in data science. The three research objectives are: (1) to develop professional learning materials organized around MLR studio day cycles for four grade-level vertically articulated professional learning communities; (2) to execute and study professional learning materials organized for grade-level vertically articulated professional learning communities; (3) to understand and document students’ and teachers’ day-to-day classroom enactments of MLRs to understand their adaptive expertise related to MLRs; and (4) to create educational video case materials for in-service and preservice teachers on the use of MLRs. The research activities focus on studying how teachers develop adaptive expertise as they use MLRs, to be able to flexibly use the MLRs. The data collection focuses primarily on qualitative analysis of the professional learning communities, studio days, classroom observations, and artifacts of the mathematics learning routines. The data analysis uses an adaptive expertise framework to interpret and describe the teachers’ learning and enactment of the mathematics language routines. The educational activities attend to video case materials developed using research materials.