Next steps for “Big Data” in education: Utilizing data-intensive research

Abstract

Data-informed instructional methods offer tremendous promise for increasing the effectiveness of teaching, learning, and schooling. Yet-to-be-developed data science approaches have the potential to dramatically advance instruction for every student and to enhance learning for people of all ages. Next steps that emerged from a recent NSF funded Computing Research Association workshop on data-intensive research in education were: 1) mobilize communities around opportunities based on new forms of evidence, 2) infuse evidence-based decision-making throughout a system, 3) develop new forms of educational assessment, 4) re-conceptualize data generation, collection, storage, and representation processes, 5) develop new types of analytic methods, 6) build human capacity to do data science and to use its products, and 7) develop advances in privacy, security, and ethics. If these steps are taken, participants agreed that data science approaches have the potential to dramatically advance instruction for every student and to enhance learning for people of all ages. This article briefly summarizes three of these themes that are particularly relevant, yet have not received as much attention as they deserve.