Supporting Model Based Inference as an Integrated Effort Between Mathematics and Science (NSF #1942770)

This project is exploring how to productively coordinate instruction around data, statistics, modeling, and inference in middle grades mathematics and science classes. We will conduct design-based research to develop and study innovative tools that support students to generate knowledge about ecological systems by using models of variability to make inferences.

Image: 
Target Audience: 
Grades 6-7; Math and Science Classes; Diverse Student Population
STEM Discipline(s): 
Statistics; Data Science; Science; Ecology
What Issue(s) in STEM Education is your Project Addressing?: 

Data models of variability inform inferences within STEM communities across disciplines. Making inferences from models of variability is an increasingly important learning goal for both science and mathematics education. For STEM professionals, these inferences involve interdisciplinary networks of ideas and practices that emerge from local questions and problems. But institutional boundaries in schools separate mathematics and science disciplines in ways that undermine interdisciplinarity, and students are rarely supported to develop a coherent image of how ideas and practices from different disciplinary communities inform one another.

Our project aims to support middle grades students to create, revise, and use models of variability to make inferences about ecological systems. We are developing innovative curricular infrastructures to help mathematics and science teachers coordinate their instruction and support students to use interdisciplinary networks of ideas as they make inferences about organisms in local ecological systems. We are using a design-based research approach in partnership with middle grades math and science teachers to iteratively design, implement, and study these curricular infrastructures. This project is designed to generate new knowledge about how to conceptualize and support interdisciplinary learning goals related to making inferences with data.

What are your Findings?: 

This project’s funding recently began in the spring of 2020. We anticipate that our project will contribute knowledge about how to help teachers support interdisciplinary learning goals as a collaborative effort across math and science, how students make use of mathematical ideas as epistemic tools to generate knowledge about ecological systems, and how new questions about ecological systems motivate a need for new mathematical tools.

Products: 

We anticipate developing three types of products:

  1. A design framework for coordinating disciplinary learning goals in math and science around the interdisciplinary practice of making inferences with data,
  2. 4 integrated investigations for 6th and 7th grade, and
  3. Exemplars of students’ reasoning as they create, revise, and use models of variability to make inferences about ecological systems.
PI: 
Ryan "Seth" Jones