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Exploring the Utopic Promise of Smart City Engagements
Get PDFThis research is intended for practitioners and explored how smart city engagements are negotiated to better understand and recognize underlying complex relational power dynamics. This was accomplished through a conflict resolution reflective and facilitative lens as it pertains to trust and value alignments. Practical insights generated from understanding these influential dynamics create the opportunity to have better decision-making and transformative capabilities. The existing literature highlighted conflicts around geopolitical and operational security concerns. In contrast, the research conducted for this study showed much of the smart city industry was more naturally collaborative and artificially competitive than originally theorized. Additionally, the research uncovered a shift in the smart city industry of embracing a more inclusive and human-centered approach, rather than a one-size-fits-all model. The concept of utopia and Root Narrative framework were used to identify value commitments, while other organizational models were used to help position the engagements and understand issues around trust. Overall, while this research may not address all the issues related to this topic, it expands the application of the conflict resolution domain to areas of practice not previously explored. Research Question: How do relational power dynamics shape smart city engagements
SOCIAL NETWORKS, AGENT-BASED MODELS, AND DATA SCIENCE: FROM INDIVIDUAL DECISIONS AND SOCIAL INTERACTIONS TO AGGREGATE OUTCOMES
Get PDFUnderstanding how the behaviors of individual people aggregate to produce socialpatterns is the foundational question in the social sciences. In the same way it is often hard to understand how the driving behavior of individuals leads to traffic jams, a wide variety of social phenomena are not well understood in terms of the actions of the people involved. In this dissertation I use the methods of modern computational social science, including agent-based models (ABM), social network analysis (SNA), and data science, to study how human communication leads to cross-border migration flows, how corruption arises via social influence, and how retention levels in higher education result from social interactions. In each of these three cases I focus on the decision-processes people engage in and then use computing tools to assess how myriad decisions scale to the aggregate level. Each case is different, but each has the common theme of micro motives leading to macro-outcomes. This is achieved by modeling patterns of behavior from the real world and seeing what emerges in the model, and how it compares to patterns of behavior observed in the real-world. This provides a way to promote interdisciplinary research and work towards more comprehensive and tested solutions to problems in the social sciences. The three essays provide three different examples of how this can be done, particularly with a lens of understanding the effects of external influence on decision-making and behavior
The Role of Environmental Visual Noise on Decision-Making
Get PDFBirds are well known for having good vision. This is particularly true for color perception and in some cases, visual acuity. They rely on their visual systems to gather information about their surroundings and then use this information to navigate, forage, and avoid threats. Although avian vision is incredible in many respects, no system is perfect, and any visual information is subject to noise from various sources. Noise in visual information can occur both in the environment and at the neurons themselves (when visual information is processed). Therefore, understanding how noise impacts signal reception is crucial for our understanding of how birds make decisions based on visual stimuli.
For a stimulus to be detected, it must be differentiable from its background. Thus, the strength of a signal must exceed the background noise. When signal-to-noise ratios are high, signals are more recognizable. While the role of neural noise has long been appreciated, fewer studies have explicitly explored the role of other environmental noise that can limit the detection of visual signals. This is likely because environments can be complex with noise at spatial and temporal levels that are hard to measure in the wild. In this thesis, I explore the role of noise on avian visual perception, using avian window collisions and avian brood parasitism as model systems. In both instances, birds must make decisions based on visual stimuli, where making incorrect choices can have negative fitness consequences.
Avian window collisions are a prime example of how decisions based on visual stimuli can lead to mortality. These collisions cause an astounding amount of mortality each year. Although there are several reasons why a bird might collide with a window, reflections on the window's surface are one of the main purported reasons. Birds may strike windows if they cannot recognize the difference between reflected and actual habitats. An inability to differentiate the reflected scene from the reflective object (the window) may result in attempts to fly toward elements in these reflected scenes, causing a window collision. While there has been much research into why avian window collisions happen and how to best mitigate them, no one has measured the level of reflection of the windows and related it to window collision mortality. In this study, I set out to determine whether windows with stronger and clearer reflections were more likely to be struck than windows with weaker and less clear reflections. I found that buildings with glossier surfaces, clearer reflections, and more window coverage had a higher chance of being struck. This has important implications for how people may mitigate window collisions.
Another system where noise can impact decision-making and fitness is avian brood parasitism. Obligate avian brood parasitism occurs when a parasite lays its eggs in the nest of a heterospecific. In doing so, the parasite transfers the cost of nestling care to the host, which accrues fitness costs due to intrabrood competition or even the killing of its own young. Since hosts can suffer serious fitness costs from raising the parasite’s young, it is expected that they would evolve mechanisms to avoid parasitism. Indeed, some host species reject parasitic eggs by ejecting them from their nests. However, rejection rates vary between, and even within, species. One reason for variation in rejection rates within species could be noise in the environment, such as dappled light, which is caused by light passing through gaps in vegetation, creating patterns of light and shadow that can create confusion. This noise can be enhanced if the vegetation is moving, creating a dynamic background. While prior research has shown that these types of environmental noise can complicate decision-making by masking signals in the environment, this question has not yet been addressed in the avian brood parasitism system. Here, I hypothesized that hosts of a brood parasite will be more likely to reject a parasitic egg when there is a limited amount of dappled light, and there is no dynamic background. These conditions are stable and should facilitate decision-making. By contrast, hosts will be more likely to accept a foreign egg when their light environment is variable due to dappled light and dynamic backgrounds. These conditions can make decision-making more challenging. Alternatively, they may also accept eggs because they lack recognition ability, even when nesting under stable light environments. As a result, acceptors should be found across a wide range of light environments. I found that acceptors nested in habitats with more variable light environments, while rejectors nested in habitats with less variable light conditions, and were only found in low-noise light environments. This shows that noise is one of the factors affecting whether birds can reject parasitic eggs.
In this thesis, I examined two examples of noise and how it can affect decision-making in birds. I found that window collisions are caused in part by strong reflections giving false signals that birds perceive as unobstructed openings. Likewise, I found that noise from the environment caused by dappled light and dynamic backgrounds can cause birds to accept parasitic eggs. Both of these studies highlight how noise can impair a bird’s ability to make decisions, and in both cases, suboptimal decisions lead to reduced fitness. Thus, my research opens the door to addressing new questions about noise and decision-making in wild birds
Understanding and Measuring Teacher Empathy: And Why It Matters
Get PDFTeacher empathy has often been considered vital to successful and equitableteaching practices; however, empirical results have been inconsistent as to the effect of teacher empathy on educational outcomes. Further, researchers have questioned the effectiveness of both recent operationalizations of teacher empathy as well as its application in diverse classrooms. This multiple manuscript dissertation—in which I developed a conceptual framework for effective teacher empathy, developed an instrument to operationalize this conceptual framework using student perceptions of student-teacher interactions, and applied this measure to middle and high school mathematics students to examine its relationship to educational outcomes—is my attempt to address these gaps in the literature. In the first manuscript, I examined both historical and recent conceptualizations and measures of teacher empathy as well as pertinent critiques from researchers and developed a conceptual framework for effective teacher xiv empathy. I further examined this conceptual framework as it may influence equitable teaching practices in middle and high school settings. In the second manuscript, I operationalized effective teacher empathy with an instrument assessing middle school student perceptions of interactions with their teachers. Results from this study provided strong evidence for this measure’s validity and reliability in a middle school setting. In the third manuscript, I applied this measure to middle and high school mathematics classrooms and found that student perceptions of teacher instructional empathy predict math achievement through the mediation of self-efficacy. Additional results suggest student-teacher ethnic match among minoritized students may influence student perceptions of instructional empathy. Collectively, these studies examine the role of teacher empathy in middle and high school classrooms, particularly with a focus on supporting equitable teaching practices for diverse groups of students. In the final chapter, I examine the findings of all three manuscripts along with limitations as they pertain to future research and implications for teacher practice
Conflict Update (February)
No full textThe report summarizes the impact on civilians of the violent clashes between the Sudan Armed Forces (SAF), Rapid Support Forces (RSF), and other armed combatants.Produced with the support of the Bureau of Conflict and Stabilization Operations, United States Department of State
An Investigation into How Teachers Learn to Teach Writing to Students with High-Incidence Disabilities
Get PDFHistorically, both special education and inclusive general education teachers report feeling unprepared to teach writing, specifically for students with high-incidence disabilities (HID) and those considered to be low-performing writers. Unfortunately, in the United States, these student populations are not making adequate gains in their written performance and require high-quality teachers of writing to improve their overall academic outcomes. This exploratory dissertation includes three complimentary studies that analyzed the pre- and in-service training and preparation that special education teachers (SETs) and inclusive educators (i.e., general education teachers) receive for teaching writing and explore the interplay of this training on the instructional practices implemented in inclusive classroom settings. This mixed methods dissertation investigated (a) empirical writing intervention research in which the student’s primary classroom teacher serves as the interventionist to examine the impact of teacher training factors on student writing outcomes; (b) the existing literacy curriculum across nationally ranked special education teacher preparation programs (TPP) for evidence of content aimed at teaching writing for students with HID; and (c) the influence of professional development (PD) and preparation on the instructional practices and adaptations for writing utilized by inclusive science teachers. Findings synthesized across the three analyses comprising this dissertation offer substantial empirical contributions including the need for increased and targeted pre- and in-service training and continued support in writing for teachers of students with HID. Ultimately, the outcomes of this dissertation underscore the importance of developing comprehensive training initiatives for equipping teachers with the necessary skills and knowledge to proficiently instruct students with HID in writing across all subject areas
A Decision Support System for Identifying Optimal Well Placement
Get PDFIn East Africa, recurrent droughts over the past few decades have contributed to severe food crises, particularly in countries heavily dependent on agriculture. To enhance sustainable resilience to drought, utilizing groundwater through borehole drilling for crop irrigation presents a viable solution. While most well placement research has focused on developing optimization models to guide local farmers in selecting optimal borehole locations, it is crucial to study groundwater characteristics before creating such models in arid and semi-arid regions with varying groundwater depths and recharge potentials.This dissertation proposes an artificial intelligence-based decision support system encompassing groundwater level prediction, groundwater recharge estimation, and well placement optimization to identify suitable borehole sites for sustainable irrigation in data-limited and water-scarce regions. The system's analysis of groundwater potential and suggested optimal well placements aim to support borehole drilling decision-making processes. Focusing on a regional watershed in southern Ethiopia, where water and data availability are limited, this study addresses the substantial water needs and the necessity for cost-effective groundwater utilization strategies. First, a non-time series database of 75 boreholes was used to construct machine learning models, including multiple linear regression, multivariate adaptive regression splines, artificial neural networks, random forest regression, and gradient boosting regression, to predict the depth to the water table. Second, an observation-constrained land surface model was proposed to estimate groundwater recharge for the data-limited, water-scarce region in the Rift Valley basin of Ethiopia. Third, deterministic mixed integer programming and two-stage stochastic mixed integer programming problems were formulated and solved to identify optimal well placements that minimize total costs and satisfy water demand from a sustainable irrigation perspective
Racial Identity Development of Black Young Children: The Relationships of African American Early Care and Education ECE Teachers and African American Families
Get PDFEarly care and education (ECE) often includes intensive family engagement constituting regular home visits, wraparound community and medical supports, child development classes for families, and advocacy opportunities for parents. This dissertation study prioritized family engagement by advancing how the field conceptualizes the race-related and cultural dimensions of family–school relationships for African American ECE teachers and economically vulnerable African American parents in ECE settings specifically. Study findings deepened qualitative understanding of relational processes in Black-majority programs and how, why, and in what culturally-grounded ways relationships between African American ECE teachers and African American families can serve as a vehicle for racial identity development. To realize this goal, African American families and African American ECE teachers can reflect on individual race-related experiences in their family history and passed down lessons for teaching and raising African American young children that developed intergenerationally. They must think critically about the collective values and beliefs that guide family-centered practices together, transmitting those values and beliefs to deepen home-school connection in joint support of African American young children’s early literacy, social and emotional growth, and positive racial identity
EXPLORING PSYCHOMETRIC PROPERTIES AND DETERMINANTS OF PLAAFP QUALITY SCORES
Get PDFThis dissertation comprises three complementary studies that aim to advance the understanding and practice of Individualized Education Programs (IEP) and Present Levels of Academic Achievement and Functional Performance (PLAAFP) development in special education. In the first study, we systematically reviewed empirical research measuring IEP quality, revealing heterogeneity in instruments used and a lack of standardized, replicated measures. In the second study, we established the reliability of scores obtained from a PLAAFP quality rubric, demonstrating strong interrater consistency (e.g., rank ICC = 0.91) and internal reliability (e.g., McDonald's ω = 0.82) through parametric and nonparametric analyses. In the third study, we investigated predictors of PLAAFP statement quality among graduate students. Results showed no significant impact of perceived school protocols but revealed improvements in PLAAFP scores after instruction (d = 0.59) and moderate social validity. Substantial variability across participants (45.1% ICC) and time points (10.1% ICC) highlighted individual differences and temporal dynamics influencing PLAAFP quality.Synthesizing findings across studies, key recommendations include: (a) replicating IEP quality measurement studies to accumulate reliability evidence; (b) establishing guidelines on sufficient reliability before implementing rubrics at scale; (c) emphasizing data skills in teacher preparation for composing high-quality IEPs; (d) exercising caution when standardizing IEP processes without reliability evidence. This dissertation provides a comprehensive examination of IEP and PLAAFP quality assessment, reliability, and determinants, informing teacher preparation practices and evidence-based policymaking to enhance educational outcomes for students with disabilities
Ground-based Light Curve Follow-up Validation observations of TESS object of interest TOI 5886.01
Get PDF“This study aims to conduct a follow-up investigation and validate the observations of a potential exoplanet candidate, Target of Interest TOI 5886.01, discovered by the Transit Exoplanet Survey Satellite (TESS) program by NASA and confirm its existence. For this study, we obtained observational data from the ground-based George Mason University (GMU) Observatory. This data was then reduced through Alnitak and visualized through AstroImageJ. We created a final light curve plot despite removing some images due to streaking. However, uncertainties remained, which did not allow us to clear the possibility of a false positive caused by a NEB or Hot Jupiter. As a result of the difference between the predicted transit and that shown on both light curves produced by this study and the TESS project, along with the previously mentioned uncertainties, the results for this research are inconclusive. Although there is currently no concrete statement as to the status of TOI 5886.01, statistical false-positive validation analysis should be conducted in the future, along with more intensive data collection, to better confirm this detection's origin.