The adoption of personalized learning approaches has increased significantly in recent years. This report examines achievement in 62 public charter and district schools that are pursuing a variety of personalized learning practices, and examines implementation details in 32 of those schools. Researchers obtained achievement data for personalized learning students and a matched comparison group of students attending other schools serving similar populations. They also collected and analyzed data from site visits, interviews, and surveys to create a broad picture of the schools' efforts to implement personalized learning and the perceptions of teachers and students. The achievement findings indicate that compared to peers, students in schools using personalized learning practices are making greater progress over the course of two school years, and that those students who started out behind are catching up to perform at or above national averages. The study finds that teachers at most schools were using data to understand student progress and make instructional decisions, all schools offered time for individual academic support, and the use of technology for personalization was widespread. However, some strategies, such as competency-based progression, were less common and more challenging to implement. Key findings are grouped into four sections. The first section on student achievement finds that there were positive effects on student mathematics and reading performance and that the lowest-performing students made substantial gains relative to their peers. The second section on implementation and the perceptions of stakeholders finds that adoption of personalized learning practices varied considerably. Personalized learning practices that are direct extensions of current practice were more common, but implementation of some of the more challenging personalized learning strategies was less common. The third section relates implementation features to outcomes and identifies three elements of personalized learning that were being implemented in tandem in the schools with the largest achievement effects. Finally, the fourth section compares teachers' and students' survey responses to a national sample and finds some differences, such as teachers' greater use of practices that support competency-based learning and greater use of technology for personalization in the schools in this study with implementation data. Appended are: (1) Methods for Achievement Analysis; (2) Methods for Implementation Analyses; (3) Student Survey Scales, Personalized Learning Schools; (4) Teacher Survey Scales, Personalized Learning Schools; and (5) Personalized Learning Attributes, Definitions, and Coding.