Improving Learning through Data Standards for Educational Technologies

Authors: John Whitmer, Aaron E. Silvers, and Megan Bowe


The surge in education technology use in response to COVID-19 represents a massive natural experiment: an opportunity to learn what works at scale, for which students, and under which conditions. However, without the right data standards in place we risk incomplete or inaccurate inferences from this experiment.

The COVID-19 pandemic has dramatically increased use of educational technologies. There is evidence that this “emergency onlining” will lead to learning loss, especially among underserved communities. To understand and address the extent of learning loss—as well as to explore and support potential future uses of educational technologies—the U.S. Department of Education (ED) must systematically implement established open-data standards that allow us to understand how students engage with learning technologies. Wide-scale implementation of these standards will make it possible to combine and analyze validated data sets generated by multiple technologies. This in turn will provide unprecedented, on-demand reporting and research capabilities that can be used to precisely identify gaps and create targeted interventions. Specifically, we recommend that ED mandate the use of the open Experience API (xAPI) standard for educational technology purchased with federal funds. We further recommend that ED invest time, talent, and resources to further develop this standard and pilot efforts to leverage educational-technology data for insights through the Institute for Education Sciences (IES) and other agencies.

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About the Authors

Aaron E. Silvers is a Manager with Elsevier Inc., responsible for data strategies to support clinical learning and patient engagement. In previous roles leading applied research & development for MakingBetter, Advanced Distributed Learning (ADL) and Grainger, Aaron facilitated the evolution of the xAPI community into several related working groups: produced exemplars, functional models, and reference software. He currently chairs the IEEE xAPI Profiles Standard Working Group, 9274.2.1. Contact: |