How should we present data for decision making? Score reporting research as a way of understanding how end-users interact with data

• In Event: Data use for improved programming and sustainable outcomes: case studies in applying the collaborating, learning, and adapting (CLA) approach

Proposal

According to USAID’s Learning Lab, “organizations that apply more adaptive leadership and data-driven practices perform better when compared with organizations that focus less on those practices.”[1] While this is no doubt true, applying data-driven practices can be challenging, as illustrated by an example from the large USAID/UKAID-funded ACCELERE!1 education project in the Democratic Republic of the Congo. In that project, various types of monitoring and evaluation data are collected to report on project progress. Standard M&E methods are used to collect data against indicators contained in the project’s results framework and a log frame. Fidelity of implementation data are collected to test the project’s theory of change. Data from Early Grade Reading Assessments (EGRAs) and curriculum-based quarterly assessments are collected to measure changes in students’ reading ability over time. Each of these types of data serves a reporting purpose, yet efforts to share results with project staff to inform decision-making have met with varying degrees of success. Efforts included print and electronic dashboard formats and face-to-face interactions. This presentation will summarize the various types of data use strategies employed by this project and their relative effectiveness as measured by score reporting research, used by researchers and industry professionals so they can develop more effective mechanisms for interpreting and using assessment data (Zapata-Rivera, ed., 2019).

References: Zapata-Rivera, D. (Ed.). (2019). Score Reporting Research and Applications. New York: Routledge

Author

• Mark Lynd, School-to-School International