A Continuum of Data Literacy for Teaching

• In Event: The Complexity of Data-Based Decision Making: Evidence From the United States, Norway, New Zealand, and Belgium

Abstract

Objectives
The purpose of the current manuscript is to present a continuum for data literacy for teachers (DLFT) that spans preservice to in-service teacher education. Researchers have called for this continuum (Mandinach & Gummer, 2016) and a continuum has been developed for the construct of assessment literacy (Coombs et al., 2018) but a continuum is still needed for DLFT. This continuum provides guidance for colleges of education, local education agencies, and professional development providers regarding how to foster DLFT across the career span of an educator.

Theoretical Framework
We operationalize DLFT according to Gummer and Mandinach’s (2015) definition,
[T]he ability to transform information into actionable instructional knowledge and practices by collecting, analyzing, and interpreting all types of data (assessment, school climate, behavioral, snapshot, longitudinal, moment-to-moment, and so on) to help determine instructional steps. It combines an understanding of data with standards, disciplinary knowledge and practices, curricular knowledge, pedagogical content knowledge, and an understanding of how children learn. (p. 2)
We position DLFT as a metaconstruct (First Author et al., in preparation) that includes the construct of AL.

Techniques and Materials
This continuum was developed based on empirical work on DLFT. Specifically, we triangulated two models of DLFT to generate the skills in the continuum: Mandinach and Gummer’s DLFT conceptual framework (2016) and the data use model from the Netherlands (Kippers et al., 2018). These two frameworks were chosen because of the authors’ expertise in the field and also because the components were aligned suggesting consensus regarding the importance of these elements. Both of these frameworks included five actions that aligned to the following elements of our continuum: (a) identify issue/opportunity and set goals; (b) collect, manage, and organize high quality data; (c) transform data into information; (d) transform information into decision; and (e) evaluate outcome (see Table 1 below).

Table 1
Side-by-Side Comparison of Data Literacy for Teachers Framework and Data Use Model

Mandinach & Gummer Kippers
Identify problems/questions Set purpose
Use data Collect data
Transform data into information Analyze data
Transform data into decision Interpret data
Evaluate outcomes Change instruction

Scholarly Significance
We present this continuum as a potential path forward for researching and developing DLFT in new, novice, and veteran teachers. Our continuum represents these as discrete skills but this is not the nature of DLFT which is a composite of these (often overlapping) skills. This work is also in line with the theme of the American Educational Research Association 2021 annual meeting in that this continuum can help educators and teacher educators accept educational responsibility for evaluating the whole child. Human subjects research protection was not required for this study.

Authors

• Jori S. Beck, Old Dominion University

• Diana Nunnaley, Using Data Solutions LLC