A Path to the Future: Creating Accountability for Personalized Learning
Common Core. Over-testing. No Child Left Behind. Few debates in education are as divisive as those over standards, testing, and accountability. The latest push to reauthorize No Child Left Behind, the 2002 law now eight years past its expiration date, has set off another frenzy.
But as lawmakers, advocates, and analysts dust off old arguments about the nation’s most significant K-12 education law, they run the risk of ignoring the future. Where NCLB was bold in its vision—all students proficient by 2014—the current proposals are remarkably lacking in ambition and new ideas. Innovation has been relegated to the fringes of the debate.
One of these innovations is personalized learning, which involves transforming students’ daily experiences so that they are customized to their individual needs and strengths. Through new kinds of learning environments, new technologies, and new ways for students to demonstrate their knowledge, personalized learning aims to meet students where they are and allow them to advance to more challenging material whenever they are ready.
Personalized learning is rooted in the expectation that students should progress through content based on demonstrated learning instead of seat time. By contrast, standards-based accountability centers its ideas about what students should know, and when, on grade-level expectations and pacing. The result is that as personalized learning models become more widespread, practitioners are increasingly encountering tensions between personalized learning and state and federal accountability structures. Common pain points include year-end summative assessments that focus exclusively on grade-level content, limited end-of-year testing windows, and rating systems that measure school performance based on student proficiency against grade-level standards rather than growth over time. Policymakers at all levels of government appear ill-equipped to handle these issues, choosing to avoid the looming conflicts and shying away from existing tools that could be deployed to ease the tensions.
This is a missed opportunity. Most personalized learning models are nascent and evolving; they need strong accountability to validate whether they work and enable the best—and only the best—to scale. Accountability systems could likewise benefit from the richer, real-time information on student performance that personalized learning models are collecting in order to customize students’ learning.
This paper seeks to help policymakers enable smart innovation and safeguard key accountability functions. By understanding the development of personalized learning and accountability, and articulating the tensions building between them, policymakers can create future accountability policies that work with personalized learning approaches and not against them.
Read the full report [PDF] here.