CAREER: Transforming College Students' Statistical Thinking: Data, Technology & Modeling

Terc Inc, Cambridge MA

Investigators

Abstract

The Faculty Early Career Development (CAREER) program is a National Science Foundation (NSF)-wide activity that offers awards in support of junior faculty who exemplify the role of teacher-scholars through outstanding research, excellent education, and the integration of education and research within the context of the mission of their organizations. Statistics and data analysis plays an increasingly important role in modern society. Without the ability to work with data (e.g. organize, represent, summarize and model) it is impossible to adequately understand and begin to solve major social issues and it is difficult to make important decisions regarding personal health, finances, and political choices. This CAREER project seeks to develop frameworks for understanding how students learn to represent, model, and organize data as part of their understanding of statistics and data analysis. In addition, it will result in tools for undergraduate statistics instruction to better support statistics teaching and learning for undergraduates. This work will inform educational strategies in the statistics classroom for all students. The project features a research-based investigation of new curricular approaches to undergraduate statistics teaching and learning with extensive use of software for learning about data organization, representation, modeling and simulation. This project should enhance and complement an existing research-based curriculum, CATALST (Change Agents for Teaching and Learning Statistics) that incorporates technology for students' learning. This project intends to investigate conjectures made within the statistics education community about the advantages of using technology to teach statistical inference from a modeling and simulation approach as well as using technology for data detective work (organizing, representing and summarizing data). The collection of rich data gathered in classrooms that explores the ways students use technology to construct models and run simulations to answer statistical questions or to use technology to organize, represent and interpret data sets will allow the principal investigator to construct models of students' statistical learning and understanding. The data to be collected includes classroom observations and video, student interviews, and assessments of student learning. The principal investigator has integrated research and education as part of this CAREER award by investigating classes she teaches and by integrating mentoring of graduate students as statistics education researchers throughout the project.