Expected and Unexpected Outcomes of a Service-Learning Program Rooted in Social Justice and Pragmatic Constructivism

Service-learning, an experiential learning and teaching pedagogy, provides students and teachers the opportunity to take classroom knowledge and put it to work in real world applications in the greater community. This qualitative case study dissertation explored the expected and unexpected outcomes of a service-learning program at an urban charter high school. Through a review of current literature, the history of service-learning is traced from its modern roots to present day incarnations. Grounded in the overlapping frameworks of pragmatic constructivist theory and practice, and service-learning with a social justice model, best practices were examined through interviews and focus groups of current students and students who have completed the SL program. The findings to the three research questions suggested: The expected outcomes addressed activism, awareness, and social development; the unexpected outcomes spoke to the development of interpersonal transformations surpassing expectations and agency, unexpected contentbased outcomes, and unexpected abstract outcomes; the implementation data focused on the need for institutional support and adaptability. Recommendations for future implementation were also discussed

A Likelihood-Free Inference Framework for Population Genetic Data using Exchangeable Neural Networks

An explosion of high-throughput DNA sequencing in the past decade has led to a surge of interest in population-scale inference with whole-genome data. Recent work in population genetics has centered on designing inference methods for relatively simple model classes, and few scalable general-purpose inference techniques exist for more realistic, complex models. To achieve this, two inferential challenges need to be addressed: (1) population data are exchangeable, calling for methods that efficiently exploit the symmetries of the data, and (2) computing likelihoods is intractable as it requires integrating over a set of correlated, extremely high-dimensional latent variables. These challenges are traditionally tackled by likelihood-free methods that use scientific simulators to generate datasets and reduce them to hand-designed, permutation-invariant summary statistics, often leading to inaccurate inference. In this work, we develop an exchangeable neural network that performs summary statistic-free, likelihood-free inference. Our framework can be applied in a black-box fashion across a variety of simulation-based tasks, both within and outside biology. We demonstrate the power of our approach on the recombination hotspot testing problem, outperforming the state-of-the-art.Comment: 9 pages, 8 figure

Sense of Place and Perceived Impacts in the Rural Industrialized Nexus: Insights for Sustainability Pathways

As representative of the water-energy-food nexus, fossil fuel development and industrial agriculture are rural industries thatcontinue to expand and increasingly occur in the same areas. Being a top agricultural export county and the fossil fuel capitalof California while ranking among the worst in the US for industrial pollution, Kern County is a poster child of rural nexusdevelopment and, thus, an essential place for initiating sustainability transitions. Such transitions rely on policy support andthe adoption of methods by individuals and communities who may disagree with such changes. While sense of place andimpact perceptions are recognized as playing critical roles in sustainability management, they have yet to be utilized in nexusresearch. A survey (N = 256) of the perceived impacts of nexus industries with place meaning and place attachment aspossible drivers for perceptions was conducted in nexus industry pollution exposure risk zones. Factor analysis and bivariatecorrelations showed that place meaning and place attachment are drivers for perceptions while also being drivers for concernfor changes in nexus industries. While perceptions of impacts indicated contested place meanings, participants stronglyperceive the economy and environment as being in decline. To build support for sustainability policy, directing funds fromKern County’s renewable energy industry to local sectors of society, implementation of regenerative agriculture, cooperativemanagement, and nurturing place meaning as aligned with nature’s restorative quality are important paths forward. Thesenexus management foci could strengthen place attachment, build trust in government, and repair environmental alienation

Historical Political Economy: What Is It?

In this chapter, we define what historical political economy (HPE) is and is not, classify the major themes in the literature, assess the relative strengths and weaknesses of the literature, and point to future directions. We view HPE as social scientific inquiry which highlights political causes or consequences of historical issues. HPE is different from conventional political economy in the emphasis placed on historical processes and context. While we view HPE in the most inclusive manner reasonable, we define it to exclude works that are either solely of contemporary importance or use historical data without any historical context (e.g., long-run macroeconomic time series data). The future of HPE is bright, especially as more historical data from around the world become available via digitization. Consequently, the future frontier of the field likely falls outside of the US, which is the concern of a disproportionate amount of the current literature

How Secure is Your System? Examining the Influence of Technical, Managerial, and Educational Controls on Users’ Secure Behavior

IT security policies play an important role in outlining employees’ secure behavior that supports organizations’ strategic and competitive goals. However, history is full of examples of employees engaging in behaviors contrary to their organization’s security policy often resulting in undesirable outcomes. This research-in-progress presents a dual-processing model explaining and predicting secure behavior while interacting with strategic information systems. The model posits that the number of security layers (technical controls), the manifestation of managerial attitudes of compliance (managerial controls), and training (educational controls) influence secure behavior directly and also indirectly through system satisfaction. We will test our model in an experiment utilizing a realistic corporate environment that captures user’s security-policy compliance. We suspect to find that managerial controls and educational controls will positively influence secure behavior while technical controls will negatively influence secure behavior directly and also indirectly through system satisfaction

Behaviorally Measuring Ease-of-Use by Analyzing Users’ Mouse Cursor Movements

Ease-of-use—the extent to which a technology is free of effort—is a hallmark of many successful websites and is a predictor of important user outcomes including intentions to use a system and a system’s perceived usefulness. We propose a behavior-based measure of ease-of-use based on the analysis of users’ mouse cursor movements. As a basis for this measure, we explain how ease-of-use influences the precision of users’ mouse cursor movements, extending Attentional Control Theory and the Response Activation Model. We propose two mousing statistics—Normalized Area under the Curve and Normalized Additional Distance—and predict that they are correlated with PEOU and can be used to differentiate ease-of-use among different tasks. We end by describing next steps to test our hypotheses and highlight potential implications

Exploring the Effect of Arousal and Valence on Mouse Interaction

Determining a user’s affective state can be an important element when trying to understand human-computer interactions. Accurately assessing affect during system use, however, can be very difficult, especially in a non-laboratory setting. Extensive previous research in neuroscience has shown that arousal and valence influence motor control. In this research, the prior relevant neuroscience findings inform the investigation of mouse movement behavior under conditions of low and high arousal as well as positive and negative valence. A controlled laboratory experiment was conducted, providing support for hypotheses predicting that arousal and valence may be inferred by monitoring for differences in the distance, speed, and trajectory of mouse movement. Implications of these results for future research and practice are explored