Using TinkerPlots as a Tool for Teaching Statistics (2011-14)
Project Purpose (Research Question/Problem Statement):
Landmark College is investigating the effectiveness of TinkerPlots (software developed as part of NSF grant DRL-9818946) as a tool in helping students with a diagnosed LD develop an understanding of key concepts in statistics. The goal of this project is to increase the number of students with an LD who successfully complete introductory statistics courses and who develop a strong enough grasp of the concepts to consider furthering their education in a STEM field. This project is intended as a demonstration project and proof that it is possible to increase the number and diversity of students who can successfully understand and work with statistical data and hence pursue careers in data-driven STEM fields.
The approach was pilot tested in introductory statistics courses at Landmark College in Putney, VT, as well as comparable level courses at Holyoke Community College in Holyoke, MA. The students at Landmark College consisted exclusively of individuals with a diagnosis that affects their learning, whereas the students at Holyoke Community College served as a comparison group reflecting a more typical student profile, one that includes students with disabilities and other conditions that influence learning (e.g. first-generation college status, minority status, primary language other than English).
NSF RDE Grant HRD-1128948: Investigating the Effectiveness of TinkerPlots in Helping Students with Learning Disabilities Understand Statistical Concepts
In many STEM fields, the ability to understand statistics and perform data analysis is an essential component. In fact, today’s scientists are increasingly expected to be expert statisticians. This makes developing an understanding of statistical concepts and being able to truly comprehend and work with a dataset essential to the successful pursuit of many STEM careers. These skills are not merely important in order to pass statistical courses that are often gatekeepers in scientific STEM academic programs, but they are an essential part of the daily work of most scientists, engineers, network administrators, and others in the STEM arena.
Statistics is becoming such a critical component of our daily lives that the National Council of Teachers of Mathematics proposes introducing statistical concepts to students as early as first grade (NCTM, 2000). Unfortunately, most adults tend to form incorrect interpretations of statistical data (Konold, 1995) and often rely or shortcuts or heuristics rather than sound statistical reasoning (Kahneman, Slovic, & Tversky, 1982). Given these findings, one would be correct in deducing that students generally struggle in traditional statistical classrooms and often have trouble reasoning about aggregate data. However, advances in technology have allowed for the development of tools that allow us to quickly produce, manipulate, and represent large amounts of data. One particular tool, TinkerPlots (Konold & Miller, 2005), has shown promise in enhancing the understanding of students ranging from elementary school to graduate school (Paparistodemou & Meletiou-Mavrotheris, 2008; Lesh, Ader, & Bas, 2010).
Dr. Ibrahim Dahlstrom-Hakki and Dr. Michelle Bower presented findings from this research on Tuesday, February 4, 2014, at the EDUCAUSE Learning Initiative Annual Meeting in New Orleans. The presentation was titled Making Data Accessible to Diverse Populations of Students. Dahlstrom-Hakki and Bower are continuing to analyze their data and are in the process of preparing a manuscript for publication.
Dahlstrom-Hakki holds a Ph.D. in Cognitive Psychology from the University of Massachusetts Amherst. He is a Research and Education Specialist in the Landmark College Institute for Research and Training (LCIRT). Bower is the Chair of the Mathematics and Computer Science Department. She received a Ph.D. in Mathematics Education from Illinois State University. Frank Klucken, a member of the Mathematics & Computer Science Department at Landmark College, has also presented on this project at conferences and is a member of the research team. Klucken holds an M.A.T. in Teaching Using Internet Technologies from The Graduate Center of Marlboro College.
Dahlstrom-Hakki notes, “We believe the approach we used tends to work better not only for our students but for the general student population, and the data backs that up.” In the courses that he and Bower tested, students interacted with real-world data as soon as possible. They were encouraged to develop gut feelings and intuitions about the data, then to transition those gut feelings and intuitions into formal statistical understanding. “Students learn better and better understand statistical concepts when they engage in real data collection and analysis,” Bower adds.