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Exploring Cognitive Load Theory in the Post-Secondary Engineering Classroom
Engineering programs often emphasize subject-matter expertise over pedagogical training, which can leave students struggling with course demands and contribute to retention challenges. This study applied Cognitive Load Theory (CLT) to examine how undergraduate engineering students experience the cognitive demands of their coursework compared to non-engineering classes. Using a sequential explanatory mixed methods design, cognitive load surveys were followed by interviews to address two research questions: (1) What are the differences in intrinsic and extraneous cognitive load levels between engineering courses and non-engineering courses taken concurrently by undergraduate engineering students? (2) How do engineering students perceive the unique challenges or benefits related to intrinsic and extraneous cognitive load in their early undergraduate engineering courses as compared to non-engineering courses they are taking? Broad comparisons revealed no significant differences in load, but disaggregated analyses showed that mathematics courses were rated higher than engineering in both intrinsic and extraneous load, while that of engineering courses exceeded all other non-math courses. Interviews revealed that students see math as part of engineering and described engineering courses as conceptually dense, fast-paced, and resource-limited. Findings highlight the need for CLT-informed strategies alongside flexible, student-centered practices that address peripheral factors such as anxiety, competing responsibilities, and resource accessibility
Parental Socialization Practices as Protective Factors of LGBTQ+ Youth Well-Being and Sexual Health
LGBTQ+ teens face challenges like discrimination and exclusion from school-based sex education. Support from parents is crucial for helping LGBTQ+ teens feel safe and confident. Most research has only looked at how parents react when their child comes out, and less about how parents support their child in everyday life. This two-study dissertation explored how parents help support and protect their LGBTQ+ teens’ well-being over time.
The first study looked for patterns of protective parenting across interviews with LGBTQ+ teens and their parents from diverse racial and ethnic backgrounds. Teens and parents shared their experiences of open communication, building community, and learning together to provide support to LGBTQ+ youth in racially or ethnically minoritized families. These stories showed that day-to-day actions, like listening and talking, help LGBTQ+ teens of color thrive.
The second study used survey data from LGBTQ+ young adults to test how sex education and parent-child sexual communication during high school influenced their confidence in making healthy sexual decisions. Perceptions of sex education did not influence LGBTQ+ young adults feel more confident in their sexual decision making. However, school-based sex education knowledge about STIs helped LGBTQ+ youth feel more confident in making healthy sexual decisions, and teens who often talked with their parents about relationships and decision making felt even more confident.
Together, these studies confirm that supportive parent-child relationships and inclusive sex education are important for LGBTQ+ youth well-being. When parents are open, supportive, willing to learn, and work together with their LGBTQ+ teen, it helps the teens feel seen, supported, and prepared to make safe and healthy decisions. Families raising LGBTQ+ teens may experience challenges, but consistently showing up, listening, and talking openly shows support and can prepare teens for their future
Pest Management for Utah Cut Flower Production: Insects and Their Relatives
Pest management is important in cut flower production, marketability, and farm profitability. This fact sheet focuses on animal pests (insects, arthropods, mollusks, and vertebrates), not diseases or weeds, and has two parts. Part 1 applies Integrated Pest Management (IPM): using preventive techniques, pest thresholds, and best management practices with pests in cut flower crop production. Part 2 highlights the top 10 common pests of cut flowers in Utah and their management
Compilation of a Nationwide River Image Dataset for Identifying River Channels and River Rapids via Deep Learning
Remote sensing enables large-scale, image-based assessments of river dynamics, offering new opportunities for hydrological monitoring. We present a publicly available dataset consisting of 281,024 satellite and aerial images of U.S. rivers, constructed using an Application Programming Interface (API) and the U.S. Geological Survey’s National Hydrography Dataset. The dataset includes images, primary keys, and ancillary geospatial information. We use a manually labeled subset of the images to train models for detecting rapids, defined as areas where high velocity and turbulence lead to a wavy, rough, or even broken water surface visible in the imagery. To demonstrate the utility of this dataset, we develop an image segmentation model to identify rivers within images. This model achieved a mean test intersection-over-union () of 0.57, with performance rising to an actual of 0.89 on the subset of predictions with high confidence (predicted \u3e 0.9). Following this initial segmentation of river channels within the images, we trained several convolutional neural network (CNN) architectures to classify the presence or absence of rapids. Our selected model reached an accuracy and F1 score of 0.93, indicating strong performance for the classification of rapids that could support consistent, efficient inventory and monitoring of rapids. These data provide new resources for recreation planning, habitat assessment, and discharge estimation. Overall, the dataset and tools offer a foundation for scalable, automated identification of geomorphic features to support riverine science and resource management
Design of a Low-Power Magneto-Inductive Magnetometer
Measuring magnetic fields in space helps scientists understand phenomena that can affect satellite communications and navigation systems on Earth. This research develops a new low-power magnetic field sensor for spacecraft that improves upon existing designs by moving the sensitive parts away from electrical interference and using energy-efficient digital electronics for precise measurements. The sensor’s power-efficient design is particularly important for small satellites, where power is limited and must be carefully managed. It will fly on future NASA missions to study disturbances in Earth’s upper atmosphere that can disrupt radio signals and GPS. This work contributes to our ability to better predict and understand space weather events that impact our everyday technology while advancing the development of power-efficient space instrumentation
Constraint-Aware Metaheuristic Optimization for Experimental Design
Designing experiments becomes much more challenging when many variables and strict constraints are involved, as is common in modern science and engineering. This thesis introduces a new computational and mathematical framework that efficiently searches for optimal experiments in complex, high-dimensional spaces where traditional methods fail. By combining geometric techniques with flexible optimization algorithms like particle swarm optimization, our methods handle difficult constraints while scaling to real-world problems. Built in the high-performance Julia programming language and released as open-source software, this work bridges advanced theory with practical tools, offering researchers a powerful and accessible way to design better experiments under realistic conditions
Aerodynamic Parameter Estimation for a Scaled F-16: A Simulation-Based Sensitivity Analysis
The physical motion of an aircraft is determined by the resulting forces and moments acting on the aircraft. These forces and moments can be defined as a mathematical equation where the control deflections, rotation rates, and orientation of the aircraft are multiplied by individual constants and summed together to define the entire force or moment. This method results in a highly accurate model that defines the motion of the aircraft at low angles of attack and sideslip. Initial calculations of the aerodynamic model are created based on analytical estimations based on the physical properties of the aircraft. Additional refinement of the model is achieved in flight testing. During flight tests, the physical states of the aircraft, such as orientation, translational motion, and rotational motion, are recorded as well as the input commands for the aircraft. An analysis of the input commands and the output states provides the necessary data to define the aerodynamic model of the aircraft. This method of defining the motion of an object based on the input commands and the output states is called system identification. The aerodynamic model resulting from the system identification method is highly dependent on the accuracy of the input and output parameters as this is the only available information in the process. This high dependence demands a robust method to analyze and manage the error that is inherent in measurements. Most research in the area of error analysis in system identification focuses on removal or management of error. This research analyzes how much effect individual sensor error and assumptions have on the resulting aerodynamic model. This research identifies a robust maneuver input that provides sufficient measurement data for the system identification method. A best-case scenario will be tested in a simulation environment to determine what accuracy is possible with the specific maneuver case. The simulation environment provides direct control of introduced errors and assumptions, providing a platform to test the influence of each error and assumption on the resulting aerodynamic model. The results show that model assumptions need to be carefully analyzed to understand the effect on the resulting aerodynamic model. The assumption that the velocity of the aircraft can be simplified to be the forward velocity, which is the velocity measured by the pitot tube, is an erroneous assumption and highly corrupts the result. The second result that introduced significant error is using the commanded control inputs instead of the actual physical position of the control surfaces. This analysis shows the need to accurately measure or estimate the full velocity vector and the true control surface deflections. The results can provide practical guidance for designing a successful flight test, helping engineers determine what sensors are necessary and which assumptions must be avoided to build a flight test platform that can successfully find the aerodynamic model through system identification
Vines in the Landscape: Virginia Creeper
Virginia creeper (Parthenocissus quinquefolia) is a vigorous and aggressive deciduous vine in the grape family (Vitaceae), known for its rapid growth, dense foliage, and striking fall color. Some landscapers consider this plant a nuisance because of its aggressive growth, potential damage to weak structures, and difficulty in removing, but others love it for its potential for erosion control, rapid coverage, fall color, and as a bird and pollinator habitat
Effects of Beaver Dams on Components of Riverscape Health and Biodiversity in the Great Basin
Networks of rivers and their floodplains (i.e., low-lying areas adjacent to rivers and streams that could plausibly flood) have been degraded, reducing the availability of freshwater and habitat for people and wildlife. Therefore, land managers are pursuing cost-effective restoration strategies, including partnering with beavers (Castor canadensis), to promote the health of these ecosystems and associated benefits. However, our understanding of beaver-mediated restoration benefits remains incomplete. Here, we compared locations along streams with and without beaver dams to measure the benefits of beavers in the Great Basin of the Western United States. We measured the effects of beaver dams on i) stream depths and depth variability, interactions between the stream and surrounding floodplains, and water movement as ecosystem health indicators; and ii) number of unique species, diversity, and activity levels for various fish, bat, and bird taxa as biodiversity indicators. We further investigated how the benefits of beavers varied by dam status (i.e., actively maintained or abandoned), and across valley settings, from steep and narrow valleys to low-gradient and wide valleys. Our results showed deeper and more variable stream habitats, stronger connections between streams and floodplains, and slower-moving water in stream segments with beaver dams than in segments without. Importantly, we found that the benefits of beaver activity are influenced by valley setting and that many benefits persisted even after dam abandonment. Although we found little difference in biodiversity indicators, the benefits of beaver dams to other components of ecosystem health likely contribute to diverse habitats that benefit biodiversity beyond individual stream segments. As interest in nature-based restoration grows, understanding the variable effects that beavers have on ecosystem processes within and across regions can inform the feasibility, potential effectiveness, and benefits of beaver-mediated ecosystem health restoration