Research Projects

Stephanie A. Casey

Mathematics Education

1) ESTEEM II: Enhancing Data Science & Statistics Teacher Education --Transforming and Building Community

Dr. Casey is a Co-PI on this 5-year National Science Foundation Improving Undergraduate STEM Education (IUSE) grant

This project aims to serve the national interest by building a community that will transform undergraduate teacher preparation so that future K-12 mathematics teachers are prepared to effectively teach modern data science and statistics (DS&S). Society demands that citizens be statistically and data literate, resulting in growing efforts at the secondary level to include more DS&S in the curriculum. To meet these demands, new teachers will need additional preparation to foster students’ statistical and data literacy. Secondary mathematics teacher education programs often minimally address DS&S in comparison to other branches of mathematics, and new teachers tend to lack content knowledge and confidence to teach statistics topics. Transformative activities of this project focus on modifications of curriculum within courses and programs, innovations to technological tools, and faculty development at a broad range of institutions. The project aims to examine the current state of DS&S teacher education and intends to assemble an extensive community of faculty, organizations, initiatives, and projects focused on transforming undergraduate teacher preparation in DS&S education.

The challenge of transforming teacher preparation programs to integrate DS&S is met using tools, methods, and approaches of improvement science as a guiding theory of change. There are three specific project goals: A) investigate the current systems in undergraduate teacher preparation for teaching DS&S by examining early career mathematics teachers through surveys and classroom observations, and a second survey and interview study to identify problems of practice for DS&S of mathematics teacher education programs; B) build and sustain a DS&S teacher education networked improvement community through partnerships with national organizations and projects and extensive faculty learning opportunities; and C) reach a broad, large, and diverse teacher education audience through developing, curating and disseminating high quality DS&S teacher education curriculum materials. The Common Online Data Analysis Platform (CODAP) of the Concord Consortium, “an easy-to-use data analysis environment designed for grades 5 through 14,” is the primary technology to be used in engaging with data, simulation and modeling. In this project, CODAP functionality is to be expanded and capabilities modified. 

The PI for the Project is Hollylynne Stohl Lee (NC State). Other Co-PIs are Rick Hudson (University of Southern Indiana), Bill Finzer (Concord Consortium), and Gemma Mojica (NC State).

2) Mathematics of Doing, Understanding, Learning and Educating for Secondary Schools (MODULE(S2)

Dr. Casey is a co-PI on this 5-year National Science Foundation Improving Undergraduate STEM Education (IUSE) grant.

The ambitious goal of MODULE(S2) is to develop course materials that mathematics and mathematics education faculty can use in content courses to develop preservice secondary mathematics teachers’ (PSMTs’) mathematical knowledge for teaching (MKT) in algebra, geometry, statistics, and modeling. The project has three major objectives:

Dr. Casey is on the statistics module writing team and the professional development team.

Hear more about Dr. Casey's work on the ESTEEM and MODULE(S^2) projects by listening to the October 15, 2020 episode of the Teaching Math Teachers Podcast!

3) Validity Evidence for Measurement in Mathematics Education (V-M^2Ed)

Dr. Casey is  co-leader of the Statistics Education Synthesis Group for this 5-year National Science Foundation DR K-12 grant. The project is developing a framework to assess the validity evidence of mathematics measures then conducting a peer-reviewed synthesis of measures to create a publicly available repository of quantitative measures in mathematics and evidence of their validity.

COMPLETED RESEARCH PROJECTS

1) AIM-ELLs:

The purpose of this research project is to develop a professional development program (AIM ELLs) for mathematics teachers in a local high school whose classes include English Language Learners. It involves the collaboration of two new faculty members, Dr. Stephanie Casey, a mathematics education professor, and Dr. Zuzana Tomaš, a specialist in teaching ELLs, as they develop, pilot, and evaluate this novel professional development program aimed at improving the mathematics achievement of ELLs. Supported by Eastern Michigan University's New Faculty Research Award.

2) Project-SET:

The first year of this two-year NSF funded project focused on developing learning progressions for sampling variability and regression. Using the learning progressions as a guide, the second year of the project developed instructional materials for secondary teachers and studied their implementation. The teacher preparation materials specifically address both teacher statistical content needs as well as statistical pedagogical needs using data relevant to teachers and the education community. The instructional materials are: (1) aligned with the Common Core Standards, (2) guided by the learning framework of the GAISE report, (3) informed by student learning and designed to directly impact teacher practice, (4) target topics that have been identified as difficult for students to learn, and (5) driven by real school-based data. Dr. Casey was a consultant for this project.

3) Conceptions of Line of Best Fit

This series of research studies focused on how students and teachers intuitively think about the relationship between two quantities that vary, a standard 8th grade topic throughout the United States with the adoption of the Common Core State Standards. Co-investigators were David Wilson (SUNY-Buffalo), Nicholas Wasserman (Teacher's College of Columbia University) and Courtney Nagle (Penn State-Erie).

3b) Teachers' Interpretations and Responses to Student Placement of Informal Line of Best Fit

This study builds on previous research studies I conducted regarding 'Conceptions of Line of Best Fit' (see 3). It studied how inservice teachers interpret and respond to two student responses regarding placing a line of best fit informally. Co-investigators were Courtney Nagle (Penn State-Erie) and Michele Carney (Boise State University).

4) Interpretations and Uses of Classroom Video in Teacher Education: Comparisons across Three Perspectives

This survey study examined what mathematics teacher educators with different theoretical perspectives noticed and described about a classroom video case and how they proposed to use the video in mathematics methods courses. This study came about from attending the Scholarly Inquiry and Practices Conference for Mathematics Education Methods, held in the Fall of 2015. Co-investigators were Ryan Fox (Belmont University) and Alyson Lischka (Middle Tennessee State University).

5) LessonSketch

Working with Joel Amidon (Ole Miss) as a LessonSketch Module Inquiry Group member, we developed modules and experiences for use in mathematics teacher preparation that use the LessonSketch platform. See the June 2020 Mathematics Teacher Educator publication or listen to this MTE Podcast for a description of one of our modules used for formative assessment of teachers' professional noticing skills.

6) Horizon Content Knowledge for Teaching Statistics: Unbiased Estimators

The purpose of this study was to investigate the impact that horizon content knowledge regarding statistics as unbiased estimators of parameters (specifically mean and standard deviation) may have on preservice mathematics teachers’ (a) conceptions of the formulas and interpretations of mean and standard deviation; (b) approach to teaching standard deviation; and (c) insight into the connections between probability and statistics. Co-investigators were Joe Champion (Boise State University), Maryann Huey (Drake University), and Nicholas Wasserman (Teacher's College of Columbia University).

7) Secondary Preservice Mathematics Teachers' Noticing of Student Thinking

The aim of this project was develop and study assignments given in mathematics methods classes for preservice secondary mathematics teachers to develop their professional noticing skills. Co-investigators were Maryann Huey (Drake University), Erin Krupa (Montclair State University/North Carolina State University), Kristin Lesseig (Washington State University-Vancouver), and Debra Monson (St. Thomas University).

8) Developing Preservice Mathematics Teachers' Understanding of Function

This project studied the use of a GeoGebra file to develop in preservice mathematics teachers a deeper understanding of the definition of function using a vending machine metaphor. Lead investigators were Jen Lovett (Middle Tennessee State University), Lara Dick (Bucknell University) and Allison McCulloch (NC State).

9) ESTEEM: Enhancing Statistics Teacher Education with E-Modules

Dr. Casey was a Co-PI on this National Science Foundation Improving Undergraduate STEM Education (IUSE) grant from 2016-2022.

The PI for the Project was Hollylynne Stohl Lee (NC State). Other Co-PIs were Rick Hudson (University of Southern Indiana) and Bill Finzer (Concord Consortium).

Intellectual merit. The ESTEEM project developed high quality statistics teacher education curriculum materials, including significant enhancements to the Common Online Data Analysis Platform [CODAP]. CODAP is a platform for developers and an application for students in grades 6-14, based on research of students' learning, to facilitate data analysis and visualization through dynamically linked multiple representations (e.g., table, graphs, statistical measures, map) with a drag-and-drop interface. ESTEEM improved the functionality of CODAP for teaching statistics at the secondary level through the addition and/or editing of CODAP's capabilities (e.g., graphing boxplots, working with linear models, adding shaded regions to graphs, adding a sampler for simulating chance models, graphing segmented bar graphs). These improved CODAP capabilities were then utilized in the ESTEEM teacher education curriculum materials. For our statistics teacher education curriculum materials, we created an online portal specific to ESTEEM with 3 modules (each with 12-16 hours of curriculum materials) which incorporate videos (e.g., teacher interviews, secondary class sessions, CODAP how-tos), brief readings, data investigations in CODAP, reflection assignments, discussion forums, and quizzes. Two summative assessments allow ESTEEM users to apply their knowledge by creating screencasts of data investigations using CODAP and developing contextually rich data tasks for use with future secondary students. Results from prior empirical studies on secondary mathematics teachers' knowledge and confidence to teach statistics informed the statistical content, pedagogical strategies, and CODAP enhancements in the ESTEEM curriculum materials. Prior research identified a lack of critical understandings of and confidence to teach categorical association and statistical inference, including simulation approaches. Thus, we focused two of the ESTEEM modules on these topics. 

ESTEEM materials are free and distributed using a Creative Commons Attribution Non-Commercial Share-Alike 4.0 license. Videos are available on YouTube, and CODAP-based tasks are distributed at the CODAP website. We innovated dissemination of teacher education curriculum materials through  e-modules that are easily imported into Learning Management Systems [LMSs] for adaptation and integration with other course materials. There are over 435 registered users in the ESTEEM portal who have access to these free materials. More than 130 faculty received professional development through attending 1-day in-person workshops or one of seven online webinars over the course of the grant period.

 In 2018-2020, 30 faculty were tracked from 27 U.S. institutions who implemented ESTEEM materials in a variety of courses (n=48) with 804 enrolled students, most of whom were undergraduate preservice mathematics teachers along with some practicing teachers or general undergraduate statistics students.  When preservice teachers use theESTEEM materials, there are strong positive impacts on their: confidence to teach statistics and use CODAP, perspectives on the importance of teaching statistics with real data, and ability to plan meaningful lessons with multivariate data about real world phenomena. Faculty who implement ESTEEM materials report learning more about appropriate statistics pedagogy, increasing their own comfort and confidence in engaging with data using CODAP, and helping preservice teachers develop pedagogical approaches for teaching statistics with rich data. Faculty appreciated the ease of use and quality of the ESTEEM curriculum materials, and used them in a variety of instructional modes (e.g., face-to-face, online, hybrid). 

Broader impact. By including institutions serving diverse populations of undergraduates (e.g., Univ. of Florida, Eastern New Mexico Univ., Benedictine College, Texas A&M Univ. - Corpus Christi, Washington State Univ. Vancouver, Univ. of Arizona), a diverse group of ESTEEM-prepared teachers are likely better equipped to teach statistics in dispersed geographic locations in the U.S., leading to stronger preparation of students and feeding the pipeline into STEM disciplines. Our approach to package LMS-ready modules is a model for broader solutions for online courses in higher education--a critical societal concern for educational access to online teacher education programs. The improvements made to CODAP and the ESTEEM-created CODAP activities are readily available and reach a wide audience of K-16 math and science teachers and students through the Concord Consortium website, providing a broad access to a free online tool and classroom-ready activities.