The Mobilization of Social Networks in Professional Development Decision-Making – A Mixed Methods Study in a Technical Field

Vast technological innovations have been transforming labor markets and workplaces. Against this background, identifying ways to foster a skilled and resilient technical workforce and determining what role industry, higher education institutions, and policymakers play in this regard has become a core concern of political and societal debates. The dissertation contributes to this discourse by looking at how adults working in tech decided to invest in skill development and professional advancement through the pursuit of an online graduate degree in computer science. The dissertation seeks to understand whether, when, and how social networks influenced this decision process. The focus on networks is important since it addresses a distinct gap as to how decision-making has traditionally been conceptualized. The results support the central argument that the decision to pursue an online graduate degree is seldom an internal, autonomous thought process, but is often shaped by social relationships through consultation, advice, and support. Family members, friends, coworkers, supervisors, and acquaintances all matter in this process – albeit to varying extents and in different capacities. A complex set of individual and contextual factors influence the broad range of social support-seeking during decision-making. The results validate the importance of examining professional development choices in social contexts, offer several theoretical and policy implications, and open avenues for future research

Financing Georgia’s Schools

Georgia’s state and local governments each commit substantial financial resources toward public K-12 education, which served 1.7 million students in FY 2015. State and local government educational expenditures are greater than any other functional category within their budgets. This report begins with a review of Georgia’s traditional K-12 public school system structure, including the legal framework, local system organization, and a brief overview of the funding sources. Then, state, local, and federal sources used to finance K-12 education are explained. This includes how the various sources of revenue are utilized by school systems and the methods used by various government entities to determine their funding allocations. In reviewing the allocation methodology for school systems, the report has a stronger focus on state revenue sources due to the size and complexity of state financial support as compared to local and federal funding. The next section discusses the governance and funding sources for charter schools, and the final section concludes the report

The Mobilization of Social Networks in Professional Development Decision-Making – A Mixed-Methods Study in a Technical Field

THE MOBILIZATION OF SOCIAL NETWORKS IN PROFESSIONAL DEVELOPMENT DECISION-MAKING –A MIXED-METHODS STUDY IN A TECHNICAL FIELD Isabel Ruthotto 171 pages Directed by Dr. Julia Melkers Vast technological innovations have been transforming labor markets and workplaces. Against this background, identifying ways to foster a skilled and resilient technical workforce and determining what role industry, higher education institutions, and policymakers play in this regard has become a core concern of political and societal debates. The dissertation contributes to this discourse by looking at how adults working in tech decided to invest in skill development and professional advancement through the pursuit of an online graduate degree in computer science. The dissertation seeks to understand whether, when, and how social networks influenced this decision process. The focus on networks is important since it addresses a distinct gap as to how decision-making has traditionally been conceptualized. The results support the central argument that the decision to pursue an online graduate degree is seldom an internal, autonomous thought process, but is often shaped by social relationships through consultation, advice, and support. Family members, friends, coworkers, supervisors, and acquaintances all matter in this process – albeit to varying extents and in different capacities. A complex set of individual and contextual factors influence the broad range of social support-seeking during decision-making. The results validate the importance of examining professional development choices in social contexts, offer several theoretical and policy implications, and open avenues for future research.Ph.D

Simultaneous adaptive smoothing of relaxometry and quantitative magnetization transfer mapping

Attempts for in-vivo histology require a high spatial resolution that comes with the price of a decreased signal-to-noise ratio. We present a novel iterative and multi-scale smoothing method for quantitative Magnetic Resonance Imaging (MRI) data that yield proton density, apparent transverse and longitudinal relaxation, and magnetization transfer maps. The method is based on the propagation-separation approach. The adaptivity of the procedure avoids the inherent bias from blurring subtle features in the calculated maps that is common for non-adaptive smoothing approaches. The characteristics of the methods were evaluated on a high-resolution data set (500 μ isotropic) from a single subject and quantified on data from a multi-subject study. The results show that the adaptive method is able to increase the signal-to-noise ratio in the calculated quantitative maps while largely avoiding the bias that is otherwise introduced by spatially blurring values across tissue borders. As a consequence, it preserves the intensity contrast between white and gray matter and the thin cortical ribbon

Simultaneous adaptive smoothing of relaxometry and quantitative magnetization transfer mapping

Attempts for in-vivo histology require a high spatial resolution that comes with the price of a decreased signal-to-noise ratio. We present a novel iterative and multi-scale smoothing method for quantitative Magnetic Resonance Imaging (MRI) data that yield proton density, apparent transverse and longitudinal relaxation, and magnetization transfer maps. The method is based on the propagation-separation approach. The adaptivity of the procedure avoids the inherent bias from blurring subtle features in the calculated maps that is common for non-adaptive smoothing approaches. The characteristics of the methods were evaluated on a high-resolution data set (500 mym isotropic) from a single subject and quantified on data from a multi-subject study. The results show that the adaptive method is able to increase the signal-to-noise ratio in the calculated quantitative maps while largely avoiding the bias that is otherwise introduced by spatially blurring values across tissue borders. As a consequence, it preserves the intensity contrast between white and gray matter and the thin cortical ribbon