Using Learning Trajectories for Teacher Learning to Structure Professional Development

ABSTRACT

As a result of the increased focus on data literacy and data science across the world, there has been a large demand for professional development in statistics. However, exactly how these professional development opportunities should be structured remains an open question. The purpose of this paper is to describe the first iteration of a design experiment involving Project-SET (www.project-set.com) professional development program. Project-SET provided professional development to enhance teachers’ understanding of statistics concepts. The project constructed two learning trajectories for teacher learning and subsequently used the learning trajectories to structure the professional development curriculum. The main goal of this paper is to illustrate how the utilization of the teacher-learning trajectories to structure the professional development allowed participating teachers to develop several aspects of Statistics Knowledge for Teaching (Groth, 2013).

Notes

¹ The work described in this paper was funded by the National Science Foundation under Grant No. 1119016.

² The implementation and retrospective phases of the design experiment were repeated three times; however, this paper reports only on the first iteration. Substantive changes to the professional development design were made on the basis of the insights from the first implementation. The second and third implementations did not reveal insights leading to significant changes in the TLT-centered professional development. For this reason, we focus in this manuscript only on the first cycle.

³ In the interest of space, we present only the sampling variability TLT throughout the paper. The regression TLT underwent the same process of construction and is available upon request to the authors.

⁴ The regression TLT begins by plotting data on scatterplots and informally examining the association between two variables and ends with constructing sampling distributions for the regression parameters.