Discourse to Improve Student Conceptual Understanding of Statistics in Inclusive Settings

Curry College, Milton MA

Investigators

Abstract

This project aims to serve the national interest by investigating the conditions under which improved student learning occurs in introductory statistics classes. Traditional approaches to teaching statistics focus on theoretical models that describe the features of sampling distributions. Research has reported that implementing a different approach, called Simulation-Based Inference (SBI), enhances students’ conceptual development of statistics. The SBI approach has also been shown to reduce achievement gaps for students of color and students with learning disabilities and executive functioning challenges. This project aims to identify the qualities of instructional practice in inclusive SBI classes that increase student-to-student and instructor-to-student discourse and further enhance the development of students’ conceptual understanding. The project is expected to develop an online compendium of audio-visual and text resources to support instructors’ implementation of an SBI approach to teaching. The long-term goals of the project are to contribute to the professional development of statistics instructors, who will in turn support their students’ development of conceptual understanding of introductory statistics ideas. This project will systematically investigate the affordances of the simulation-based inference approach to the post-secondary, algebra-based introductory statistics course for students, particularly students with learning and attention disabilities and other students who have been excluded from the scholarship of the discipline. Three goals guide the work of this project. First is to identify and explicate the instructional practices that support students with learning disabilities to access the content in these introductory statistics courses. Second is to identify and explicate students’ statistical conceptions – both productive and less productive – that arise in an introductory simulation-based inference statistics course. Third, and finally, is to develop resources for statistics instructors that will enhance their ability to listen for and productively respond to students’ conceptions in real time. The project team will disseminate these online resources through a growing network of instructors who are using the SBI approach. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through its Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools. 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.