Browsing by Author "Green, Jennifer L."

Now showing 1 - 7 of 7

Defining Program Effects: A Distribution-Based Perspective
(2017-08) Green, Jennifer L.; Stroup, Walter W.; Fellers, Pamela S.
In an age of accountability, it is critical to define and estimate the effects of teacher education and professional development programs on student learning in ways that allow stakeholders to explore potential reasons for what is observed and to enhance program quality and fidelity. Across the suite of statistical models used for program evaluation, researchers consistently measure program effectiveness using the coefficients of fixed program effects. We propose that program effects are best characterized not as a single effect to be estimated, but as a distribution of teacher-specific effects. In this article, we first discuss this approach and then describe one way it could be used to define and estimate program effects within a value-added modeling context. Using an example dataset, we demonstrate how program effect estimates can be obtained using the proposed methodology and explain how distributions of these estimates provide additional information and insights about programs that are not apparent when only looking at average effects. By examining distributions of teacher-specific effects as proposed, researchers have the opportunity to more deeply investigate and understand the effects of programs on student success.
The Development and Evolution of an Introductory Statistics Course for In-Service Middle-Level Mathematics Teachers
(2014-11) Schmid, Kendra K.; Blankenship, Erin E.; Kerby, April T.; Green, Jennifer L.; Smith, Wendy M.
The statistical preparation of in-service teachers, particularly middle school teachers, has been an area of concern for several years. This paper discusses the creation and delivery of an introductory statistics course as part of a masterâ€™s degree program for in-service mathematics teachers. The initial course development took place before the advent of the Common Core State Standards for Mathematics (CCSSM) and the Mathematics Education of Teachers (MET II) Reports, and even before the GAISE Pre-K-12 Report. Since then, even with the recommendations of MET II and the wide-spread implementation of the CCSSM, the guidance available to faculty wishing to develop a statistics course for professional development of inservice teachers remains scarce. We give an overview of the masterâ€™s degree program and discuss aspects of the course, including the goals for the course, course planning and development, the instructional team, course delivery and modifications, and lessons learned through five offerings. With this paper, we share our experiences developing such a course, the evolution of the course over multiple iterations, and what we have learned about its value to the middle-level teachers who have participated. As more and more universities are being asked to develop courses specifically for in-service teachers, we wrote this
Fostering conceptual understanding in mathematical statistics
(2015-12) Green, Jennifer L.; Blankenship, Erin E.
In many undergraduate statistics programs, the two-semester calculus-based mathematical statistics sequence is the cornerstone of the curriculum. However, 10 years after the release of the Guidelines for the Assessment and Instruction in Statistics Education (GAISE) College Report, 2005, and the subsequent movement to stress conceptual understanding and foster active learning in statistics classrooms, the sequence still remains a traditional, lecture-intensive course. In this article, we discuss various instructional approaches, activities, and assessments that can be used to foster active learning and emphasize conceptual understanding while still covering the necessary theoretical content students need to be successful in subsequent statistics or actuarial science courses. In addition, we share student reflections on these course enhancements. The course revision we suggest doesn’t require substantial changes in content, so other mathematical statistics instructors can implement these strategies without sacrificing concepts in probability and inference that are fundamental to the needs of their students. Supplementary materials, including code used to generate class plots and activity handouts, are available online.
Fostering Conceptual Understanding in Mathematical Statistics
(2015-12) Green, Jennifer L.; Blankenship, Erin E.
In many undergraduate statistics programs, the two-semester calculus-based mathematical statistics sequence is the cornerstone of the curriculum. However, 10 years after the release of the Guidelines for the Assessment and Instruction in Statistics Education (GAISE) College Report, 2005, and the subsequent movement to stress conceptual understanding and foster active learning in statistics classrooms, the sequence still remains a traditional, lecture-intensive course. In this article, we discuss various instructional approaches, activities, and assessments that can be used to foster active learning and emphasize conceptual understanding while still covering the necessary theoretical content students need to be successful in subsequent statistics or actuarial science courses. In addition, we share student reflections on these course enhancements. The course revision we suggest doesn't require substantial changes in content, so other mathematical statistics instructors can implement these strategies without sacrificing concepts in probability and inference that are fundamental to the needs of their students. Supplementary materials, including code used to generate class plots and activity handouts, are available online.
Primarily statistics: Developing an introductory statistics course for pre-service elementary teachers
(2013-11) Green, Jennifer L.; Blankenship, Erin E.
We developed an introductory statistics course for pre-service elementary teachers. In this paper, we describe the goals and structure of the course, as well as the assessments we implemented. Additionally, we use example course work to demonstrate pre-service teachers’ progress both in learning statistics and as novice teachers. Overall, the course aims to help pre-service teachers recognize the importance of statistics in the elementary curriculum, as well as the integral role they, as teachers, can play in a student’s entire statistical education. Our course serves as a model/resource for others interested in pre-service teacher development.
Teachers and Data Literacy: A Blueprint for Professional Development to Foster Data Driven Decision Making
(2016-04) Green, Jennifer L.; Schmitt-Wilson, Sarah; Versland, Tena M.
Standardized testing and the implementation of the Common Core State Standards has brought the importance of data literacy and data driven decision making (DDDM) to the forefront of district professional development needs. Many states currently require school districts to collect student performance data in the pursuit of increasing student achievement. However, most school districts do not have a clear vision for how these data will be used to inform and improve instruction (Creighton, 2006). Moreover, few educators have been trained in DDDM. In this paper, we share our insights and experiences in designing and providing professional development for teams of teachers and administrators in order to establish, support and sustain a data-driven culture within their schools and districts. We begin by discussing the need for DDDM, continue by describing the process of designing and implementing training opportunities for educators, and conclude with a discussion and evaluation of the initiative's success. This research offers practical suggestions for creating a culture of DDDM within schools and districts. Our insights provide important direction for university faculty and school district administration as they seek to develop partnerships where university providers design professional development and outreach opportunities that support student learning.
Teaching highs and lows: Exploring university teaching assistants’ experiences
(2010-11) Green, Jennifer L.
Recent reforms in statistics education have initiated the need to prepare graduate teaching assistants (TAs) for these changes. A focus group study explored the experiences and perceptions of University of Nebraska-Lincoln TAs. The results reinforced the idea that content, pedagogy, and technology are central aspects for teaching an introductory statistics course. The TAs addressed the need for clear, specific guidelines and examples, as well as collaboration between colleagues. The TAs also sought opportunities to enrich their teaching skills and, ultimately, their impact on students’ learning. These findings support previous research on graduate TAs and highlight the need for additional exploration of the role graduate statistics TAs play in introductory statistics education.