Equipping Preservice Elementary Teachers for Data Use in the Classroom

ABSTRACT

Current preservice teacher education practice related to data use has been deemed inadequate, in that it is unevenly distributed and often superficial. In response, this article describes a course-based classroom assessment data-literacy experience for preservice elementary teachers. Grounded in extant theory and research concerning data literacy and data use and interventions to promote data use processes among educators, the 6-hour experience involves preservice teacher scoring of teacher-developed assessments, and analyzing, interpreting, and making decisions based on these data. The pedagogical strategy’s design (objectives, materials, and activities) and implementation process are illustrated for the reader. It is hoped that members of the teacher education community will adopt or adapt the strategy for implementation with preservice teachers within other programs and institutions. In doing so, teacher educators can provide preservice teachers with rich, in-depth experiences by which to equip them for this salient but difficult facet of their professional practice.

KEYWORDS:

• Data-driven decision making
• data literacy
• data use
• preservice teachers
• teacher education

Notes

1. Studies by McDougall et al. (2007), Carlson et al. (2011), and van Geel et al. (2016) were experimental (or quasi-experimental) in nature, whereas others cited in this section used other research designs. Although the set of design features identified here are implicated in prior research, more randomized studies are needed to understand unequivocally the optimal design of data use capacity-building activities for teachers.

2. In some cases, the preservice teachers’ assessments have more scored components (e.g., items), or more students were assessed, than there are columns or rows (respectively) in the raw data worksheets; in such cases, the instructor modifies the raw data worksheet. The instructor also offers to check any preservice teacher’s raw data worksheets to make sure they are formulated and are analyzing data correctly.

3. If a constructed-response item is scored using an analytic rubric, score the item with respect to each rubric dimension separately and then aggregate each rubric dimension score to yield a total score for that item.

Additional information

Notes on contributors

Todd D. Reeves

Todd Reeves is an assistant professor of educational research and evaluation at Northern Illinois University. His research focuses on teacher education relative to assessment and data use.