Digital Collaboration and Classroom Practice: Educator Use of ARIS Connect

A major focus of the booming education technology sector is on products that aim to help teachers improve classroom practice. For their part, districts must figure out which of these resources will be most useful to schools. In New York City, the Department of Education developed its own Achievement Reporting and Innovation System (ARIS), which was rolled out in 2008. ARIS was an early effort at a system-wide data and teacher collaboration platform, and a major undertaking for the nation's largest school district. In 2011, the Research Alliance received a grant from the Spencer Foundation to investigate how this ambitious initiative played out in schools. Our first report focused on overall use and perceptions of ARIS. In the current phase of our study, we honed our focus onto ARIS Connect -- a component designed specifically to help educators improve their practice by sharing resources, posting questions, and giving one another feedback, both within schools and across the district. Our investigation sought to understand what educators thought of Connect, and whether, as its designers intended, Connect supported their ability to communicate with other educators and improve classroom practice. The study is based on two years of "clickstream" data, which tracks user visits to and navigation through ARIS. We also visited nine middle schools that recorded higher-than-average use of Connect, where we interviewed administrators and held focus groups with teachers. This report presents our findings, including insights on why educators did or did not use Connect; what might have made Connect more useful; and what external tools educators use for similar purposes

Particle displacements in the elastic deformation of amorphous materials: local fluctuations vs. non-affine field

We study the local disorder in the deformation of amorphous materials by decomposing the particle displacements into a continuous, inhomogeneous field and the corresponding fluctuations. We compare these fields to the commonly used non-affine displacements in an elastically deformed 2D Lennard-Jones glass. Unlike the non-affine field, the fluctuations are very localized, and exhibit a much smaller (and system size independent) correlation length, on the order of a particle diameter, supporting the applicability of the notion of local "defects" to such materials. We propose a scalar "noise" field to characterize the fluctuations, as an additional field for extended continuum models, e.g., to describe the localized irreversible events observed during plastic deformation.Comment: Minor corrections to match the published versio

Masculine domination and health: the uses of the body in middle class urban youth

Objectives: To analyze the discourse of Brazilian youth on representations of gender, their behavior and opinions on sexuality and the use of ones body, and the implications of these views on their physical and psychological health.\u2

Liberation, Learning, and Love: The Story of Harlem Preparatory School, 1967-1974

“For we've done so much, with so little, for so long, that now we can do anything, with nothing at all.” This popular phrase at the independent tuition-free school called Harlem Prep in many ways reflected Central Harlem itself in the late-1960s. On one hand, decades of racial discrimination and unfulfilled promises had defined schooling in the neighborhood. There were no public high schools in the area, and talented youth were being pushed out of formal education. Conversely, there was a resilience and continued, centuries-long desire for educational equity. As a result—and buoyed by the dynamic political environment—a handful of leaders in Harlem decided to create a school, similar to other efforts in U.S. cities. However, unlike other emerging Black alternative schools, it would be different than its peers: it would be a multicultural school, and it would be for students who had been pushed out of education and onto the streets. “Liberation, Learning, and Love” explores the unknown history of this school, Harlem Prep. Although firmly rooted in this era’s civil rights activism, Harlem Prep’s educational philosophy—its radical multiculturalism—was also distinct and innovative compared to other ideologies. The school’s leaders, teachers, and students were able to re-imagine education on a community-wide, institutional, and classroom level. Through its “unity in diversity” approach, Harlem Prep not only graduated and sent to college over 750 students, most of them previously out of school, but galvanized the notable Black community of Harlem. This project introduces multicultural education to the lexicon of Black alternative schools in the 1960s and 1970s, and reshapes how historians conceptualize equity, emancipatory education, and beyond. Harlem Prep imagined a more loving, pluralistic world for its young people. Perhaps its story can inspire those of us who strive to create a similar future for our youth today

Youth Historians in Harlem: Exploring the Possibilities in Collaborative History Research Between Local Youth and Scholars

During 2014-15 academic year, high school students and Barry M. Goldenberg work together to study the history of education in Harlem

A survey of statistical network models

Networks are ubiquitous in science and have become a focal point for discussion in everyday life. Formal statistical models for the analysis of network data have emerged as a major topic of interest in diverse areas of study, and most of these involve a form of graphical representation. Probability models on graphs date back to 1959. Along with empirical studies in social psychology and sociology from the 1960s, these early works generated an active network community and a substantial literature in the 1970s. This effort moved into the statistical literature in the late 1970s and 1980s, and the past decade has seen a burgeoning network literature in statistical physics and computer science. The growth of the World Wide Web and the emergence of online networking communities such as Facebook, MySpace, and LinkedIn, and a host of more specialized professional network communities has intensified interest in the study of networks and network data. Our goal in this review is to provide the reader with an entry point to this burgeoning literature. We begin with an overview of the historical development of statistical network modeling and then we introduce a number of examples that have been studied in the network literature. Our subsequent discussion focuses on a number of prominent static and dynamic network models and their interconnections. We emphasize formal model descriptions, and pay special attention to the interpretation of parameters and their estimation. We end with a description of some open problems and challenges for machine learning and statistics.Comment: 96 pages, 14 figures, 333 reference