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Using over 350 hours of observational data from district-level meetings, we investigate how leaders support their interpretations of problems and proposed solutions during closed-door negotiations around three policy decisions, and how they invoke race, class, and language in the process. District leaders primarily cite constraints from stakeholders, practical realities, and policies during deliberations. They also draw on beliefs, values, and—to a lesser extent—information like research and data. Race, class, and language discourses were layered with values-based reasons, and most often addressed structural challenges to equity. The balance of attention to these factors depended on the configuration of participants and the nature of the policy decision itself, particularly decision makers' perception that it would be controversial among certain groups.

While there is an abundance of data-use literature available, there is still a need to develop methodological approaches for studying naturally occurring data use in decision-making processes over time. The central contribution of this paper is a strategy to understand the use of data in long-term observations of educational leaders' policy-making deliberations. Using longitudinal and observational data, we created 'decision trajectories' that traced microprocesses of deliberation around specific decisions over time. We employed frame theory to locate when and how data entered decision-making processes within these trajectories. Our approach addresses the use of data as they arise in the context of longitudinal observations - a method that provides insight into how data may be used to inform, frame, or justify educational decisions.

This article presents a comparative case analysis of three U.S. rural science teachers who participated in an online course focused on designing assessments aligned with the Framework for K-12 Science Education and the Next Generation Science Standards (NGSS). Data from surveys, designed assessments, classroom observations, and interviews were used to investigate and compare these rural teachers ' experiences before, during, and after the course. This article describes the variations among rural science teachers in their local teaching contexts, relevant prior experiences, and how they engaged in and learned from professional development. The case study teachers entered the course with differences in their knowledge and professional learning opportunities related to the NGSS as well as in the degree to which they were connected with other science educators in their community or state. However, findings showed that all these teachers drew resourcefully on social and material supports provided by the course and made large shifts in their designed assessments. In some cases, teachers ' beliefs and practices changed as well. This study highlights the unique backgrounds of each teacher and the variation in their growth trajectories, as they entered and exited the course in different places along their journey toward gaining expertise in science assessment. We argue that professional learning opportunities for rural science teachers should be designed to leverage and support the breadth of assets and needs that vary between distinct rural communities.

This dissertation is an ethnographic and discourse analytic study of youth identity and participation in the context of one high school reform. The study explores what it means for youth to be \"connected\" in and to high school. The research site was a large, metropolitan high school in a small city in the Midwest U.S., which was explicitly attempting to engage students more fully and equitably in the social, academic, and extracurricular life of the school through a federally-funded, comprehensive school reform. Grounded in social practice theories of discourse and identity and ethnographic studies of adolescents in school, this study examines how youth construct identities for themselves in their everyday lives in school, and how young people's opportunities and possibilities for participation in school are mediated by cultural and institutional practices, discourses, and dynamics of power. This dissertation presents a series of case studies that focus analytically on different aspects of the sociocultural processes through which adolescents positioned themselves and were positioned in this school. The first analysis examines discursive constructions and cultural models of youth \"connectedness\" both in the talk of teachers and administrators at the school, and also embodied in the structure of the reform. The second analysis focused on three young women at Lakeville High through an entire school year, analyzing their practices of identification and how they were positioned in and by the school as certain kinds of students. The third analysis discusses a public controversy around a school newspaper that illuminates how this local conflict was related to broader enduring struggles over issues of belonging, school reform, and the production of youth as \"kinds of people\" in school. The dissertation highlights the importance of understanding youth \"connections\" in school as deeply cultural, contextual, and political.

Melt and supraglacial lakes are precursors to ice shelf collapse and subsequent accelerated ice sheet mass loss. We used data from the Landsat 8 and Sentinel-2 satellites to develop a threshold-based method for detection of lakes found on the Antarctic ice shelves, calculate their depths and thus their volumes. To achieve this, we focus on four key areas: the Amery, Roi Baudouin, Nivlisen, and Riiser-Larsen ice shelves, which are all characterized by extensive surface meltwater features. To validate our products, we compare our results against those obtained by an independent method based on a supervised classification scheme (e.g., Random Forest algorithm). Additional verification is provided by manual inspection of results for nearly 1000 Landsat 8 and Sentinel-2 images. Our dual-sensor approach will enable constructing high-resolution time series of lake volumes. Therefore, to ensure interoperability between the two datasets, we evaluate depths from contemporaneous Landsat 8 and Sentinel-2 image pairs. Our assessments point to a high degree of correspondence, producing an average R2 value of 0.85, no bias, and an average RMSE of 0.2 m. We demonstrate our method’s ability to characterize lake evolution by presenting first evidence of drainage events outside of the Antarctic Peninsula on the Amery Ice shelf. The methods presented here pave the way to upscaling throughout the Landsat 8 and Sentinel-2 observational record across Antarctica to produce a first-ever continental dataset of supraglacial lake volumes. Such a dataset will improve our understanding of the influence of surface hydrology on ice shelf stability, and thus, future projections of Antarctica’s contribution to sea level rise.

Surface meltwater generated on ice shelves fringing the Antarctic Ice Sheet can drive ice-shelf collapse, leading to ice sheet mass loss and contributing to global sea level rise. A quantitative assessment of supraglacial lake evolution is required to understand the influence of Antarctic surface meltwater on ice-sheet and ice-shelf stability. Cloud computing platforms have made the required remote sensing analysis computationally trivial, yet a careful evaluation of image processing techniques for pan-Antarctic lake mapping has yet to be performed. This work paves the way for automating lake identification at a continental scale throughout the satellite observational record via a thorough methodological analysis. We deploy a suite of different trained supervised classifiers to map and quantify supraglacial lake areas from multispectral Landsat-8 scenes, using training data generated via manual interpretation of the results from k-means clustering. Best results are obtained using training datasets that comprise spectrally diverse unsupervised clusters from multiple regions and that include rock and cloud shadow classes. We successfully apply our trained supervised classifiers across two ice shelves with different supraglacial lake characteristics above a threshold sun elevation of 20°, achieving classification accuracies of over 90% when compared to manually generated validation datasets. The application of our trained classifiers produces a seasonal pattern of lake evolution. Cloud shadowed areas hinder large-scale application of our classifiers, as in previous work. Our results show that caution is required before deploying ‘off the shelf’ algorithms for lake mapping in Antarctica, and suggest that careful scrutiny of training data and desired output classes is essential for accurate results. Our supervised classification technique provides an alternative and independent method of lake identification to inform the development of a continent-wide supraglacial lake mapping product.