PRME Implementation in a Canadian Business School

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Description
Students in higher education require the skills and knowledge to creatively solve some of the pressing social, economic, and environmental issues confronting humanity. In 2015, the United Nations and its member states developed the Sustainable Development Goals (SDGs) to address

Students in higher education require the skills and knowledge to creatively solve some of the pressing social, economic, and environmental issues confronting humanity. In 2015, the United Nations and its member states developed the Sustainable Development Goals (SDGs) to address complex global issues and systemic barriers to achieving sustainable development across the world. The SDGs help guide the Principles for Responsible Management Education (PRME), an initiative of the UN Global Compact that aligns signatory business schools with a set of values consistent with responsible management principles. This action research study examined bridging the knowledge gap of faculty transitioning from teaching traditional business curriculum to PRME and the SDG implementation in the curriculum in a polytechnic setting. Rogers’ Diffusion of Innovation (DOI) theory was used as the guiding theoretical framework. An intervention in the form of a faculty development micro-credential was created and implemented for study participants. Using a quantitative research design with pre-intervention and post-intervention surveys, participants reported a statistically significant increase in knowledge after the PRME micro-credential.
Date Created
2024
Agent

Making it Work Anyway: Inspiring Online University Students to Stay Connected to Online Coursework Despite Access Barriers

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Description
The Internet is poised to open access to higher education for students no matter where they live. However, many students still live in places where barriers keep them from getting and staying connected to online coursework. These barriers include power

The Internet is poised to open access to higher education for students no matter where they live. However, many students still live in places where barriers keep them from getting and staying connected to online coursework. These barriers include power outages, high internet data costs, and lack of computers or smartphones. BYU-Pathway Worldwide’s PathwayConnect prepares students living around the world to matriculate into online certificate and degree programs. When students drop out PathwayConnect, many cite these technical barriers. However, other PathwayConnect students have employed a series of know-hows, or strategies to stay connected to the online coursework. The aims of this action research dissertation were to discover these specific know-hows, design a way for PathwayConnect students to read and discuss them in the Canvas course shell, and measure the impact of sharing the know-hows. While quantitative data analysis showed no change in student persistence between the treatment and control groups, students in the treatment group reported high engagement with the know-hows. Moreover, qualitative data analysis revealed extensive use and adaptation of the know-hows among the treatment group.
Date Created
2024
Agent

Teacher Recruitment and Preparation Through High School Grow Your Own Teacher Training and the Application of Mentorship Before Graduation

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Description
Nationally, schools in the United States struggle to recruit and retain highly qualified teachers. Previous research supports using teacher pedagogy training and mentorship to increase retention. This study examines the use of mentorship in a high school Grow Your Own

Nationally, schools in the United States struggle to recruit and retain highly qualified teachers. Previous research supports using teacher pedagogy training and mentorship to increase retention. This study examines the use of mentorship in a high school Grow Your Own teacher training program and student career selection. The action research study used a mixed-methods approach framed by social cognitive career theory. The study explores how student self-efficacy beliefs and career selection evolved through a semester-long mentorship program. The study also examines mentors' ability to identify student pedagogy strengths. This study builds on previous research about teacher recruitment and retention. The findings outlined in this study highlight the use of mentorship in a high school grow your own teacher training program and the student's future career selection. Most participants changed their perception of the teaching profession through the four-year teacher training program. Mentors also reported a high level of confidence in identifying student pedagogy strengths. The fluidity of student career selection through high school allows for professional training programs to inform their decision. High school career training program designers can also use the information collected through mentorship to shift their actions based on the information received. The use of grow your own professional training and mentorship in this study could be applied to professions outside of teacher training to develop high-skill workforce pipelines. Keywords: Teacher Recruitment, Teacher Retention, Grow Your Own, Career and Technical Education, Teacher Shortage
Date Created
2024
Agent

Leveraging Sports Events to Increase Social Capital and Foster a Sense of Community

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Description
Sports facilities are constructed across the United States using public subsidies and there is limited research about how the community benefits from these investments. Broader community benefits need to be established to justify public funding of sports facilities, including how

Sports facilities are constructed across the United States using public subsidies and there is limited research about how the community benefits from these investments. Broader community benefits need to be established to justify public funding of sports facilities, including how social capital and sense of community are developed in a sport context. This research was composed of three studies that explored the benefit of providing access to sports events as a generator of social capital, the importance of developing social spaces at sports facilities to provide opportunities for attendees to nurture a sense of community and the value of virtual spaces in maintaining sense of community when isolated. The first study was a case study of Arizona State University (ASU) football season ticket holders to understand whether ticket donations to games can facilitate social capital by providing fans an opportunity to meet new people and develop long-term relationships. Findings indicated that donating tickets to sports events facilitate social relationships among fans that can build social capital, which advances existing research that focused primarily on the economic impact, and provides practical applications by encouraging sport managers to donate unused tickets. The second study examined sense of community by evaluating how fans use social spaces at a Denver Broncos National Football League (NFL) game and the Ironman World Championships (IWC). This study demonstrated that sense of community can originate in social spaces because attending a sport event and interacting in social spaces facilitates positive feelings about the community for the attendees. The third study focused on the impact of the COVID-19 pandemic on sport participants’ sense of community. This study examined the impact the pandemic had on sense of community among members of USA Triathlon, the Olympic and Paralympic National Governing Body for the sport in the United States. The research showed that USA Triathlon members adopted alternative virtual engagement opportunities that replaced in-person activities and were not materially impacted by the pandemic. Overall, these three studies advanced the understanding of how sports events, whether in-person or virtual, can facilitate social capital and enhance sense of community.
Date Created
2024
Agent

K-12 Organization-Wide Book Study: A Quantitative Action Research Dissertation

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Description
The purpose of this quantitative action research study was to evaluate the effectiveness of an organization-wide book study in the K-12 environment. A growing charter school network was working towards an improved organizational culture to meet its mission. This study

The purpose of this quantitative action research study was to evaluate the effectiveness of an organization-wide book study in the K-12 environment. A growing charter school network was working towards an improved organizational culture to meet its mission. This study examined whether an organization-wide book study can make a difference in workplace belongingness, one of the core beliefs of the network. Bloom's Revised Taxonomy shaped the design of three distinct format options for the book study: facilitated, book club, and asynchronous. The study compared participants and non-participants in workplace belonging. Workplace belonging was measured using the Jena and Pradhan Workplace Belongingness Scale. Additionally, the study analyzed how the three different formats are more or less effective according to the Kirkpatrick Four-Level Model of Evaluation. The book study format effectiveness was measured using a modified version of the Lau, Henry, and Ebekozien training survey. Results were mixed. There was no significant difference found in workplace belonging among the three formats, and there was no significant difference found between the control group and experimental group. Significant difference was found in the facilitated format’s overviews and discussions when compared to the asynchronous group. Significant difference was also found in the book club’s discussions when compared to the asynchronous group.
Date Created
2024
Agent

Campus Recreation Professionals: Supporting Employee Retention Through Professional Development Workshops

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Description
Arizona State University's Sun Devil Fitness and Wellness department plays a vital role in enhancing the physical health and well-being of its student population. However, the demanding responsibilities placed on campus recreation professionals, combined with the high expectations for student

Arizona State University's Sun Devil Fitness and Wellness department plays a vital role in enhancing the physical health and well-being of its student population. However, the demanding responsibilities placed on campus recreation professionals, combined with the high expectations for student engagement, have led to a concerning rise in employee turnover. To address this issue, a comprehensive series of professional development workshops was designed, aiming to empower campus recreation professionals in navigating their roles effectively and improving their overall experience. This mixed-methods action research study was conducted to address the challenge of employee retention among entry-level campus recreation professionals at Arizona State University. The research encompassed both quantitative and qualitative assessments, focusing on critical factors such as self-efficacy, career success, job satisfaction, sense of belonging, and motivation. The study aimed to determine whether significant differences existed in these variables before and after the intervention. Data collection involved surveys, open-ended questions, and interviews, offering a comprehensive understanding of the impact of the professional development workshops. The results of this study indicate that the professional development workshops served as an effective intervention on various constructs. Quantitative data showed a positive change in career success, motivation, and job satisfaction among staff members, while qualitative data shed light on key factors influencing employee retention. These factors included the lack of professional development opportunities, unclear career advancement pathways, a strong desire for more substantial recognition, and the paramount importance of supportive leadership and a positive work environment.
Date Created
2024
Agent

Optimizing Memory and Storage Disaggregation for Data-intensive Systems

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Description
Data-intensive systems such as big data and large machine learning (ML) systems experience serious scalability challenges due to the ever-increasing data demand from ML and analytics applications and the resource fragmentation caused by conventional monolithic server architecture. Memory and storage

Data-intensive systems such as big data and large machine learning (ML) systems experience serious scalability challenges due to the ever-increasing data demand from ML and analytics applications and the resource fragmentation caused by conventional monolithic server architecture. Memory and storage disaggregation emerges as a pivotal technology to address these challenges by decoupling memory and storage resources from individual servers and managing and provisioning them to applications as a shared resource pool. This dissertation investigates several important aspects of memory and storage disaggregation and proposes novel solutions to support data-intensive applications.First, caching is a fundamental way to utilize disaggregated storage, but building a large disaggregated cache is challenging because the commonly-used fix-sized cache block allocation scheme is unable to provide good cache performance with low memory overhead for diverse cloud workloads with vastly different I/O patterns. The dissertation proposes a novel adaptive cache block allocation approach that dynamically adjusts cache block sizes based on changing I/O patterns. This approach significantly improves I/O performance while reducing memory usage, outperforming traditional fixed-size cache systems in diverse cloud workloads. Evaluation shows that it improves read latency by 20% and write latency by 9%. It also reduces the amount of I/O traffic to cloud block storage by up to 74% while achieving up to 41% memory savings with only 2 ms. Second, large ML applications such as large language model (LLM) inference are memory demanding, but to support them using disaggregated memory brings challenges to memory management since disaggregated memory has higher memory access latency compared to local memory. The dissertation proposes latency-aware memory aggregation which cautiously distributes memory accesses to minimize the latency gap between local and disaggregated memory. It also proposes NUMA-aligned tensor parallelism to further improve the computing efficiency. With these optimizations, LLM inference achieves substantial speedups. For example, first token latency improves by 61%, and end-to-end latency improves by 43% for a LLM inference task which uses a model of 66 billion parameters when the batch size is 8. Finally, to address the cost, power consumption, and volatility of DRAM, the dissertation proposes to incorporate flash memory into memory pools within the disaggregation framework. By establishing a tiered memory architecture which combines fast-tier local DRAM with slow-tier DRAM and flash memory in the memory pool and effectively migrates data based on hotness across memory tiers, this approach not only reduces expenses but also maintains the overall performance and scalability of data-intensive systems. For example, with 50% saving in memory cost, the performance degradation of training ResNet50 on ImageNet dataset is only 2.68%. Together, these contributions systematically optimize the use of memory and storage disaggregation to deliver more efficient, scalable, and cost-effective systems for supporting the data explosion in today’s and future computing systems.
Date Created
2024
Agent

Aerodynamic Nuances on Wings Subjected to Ground Effect

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Description
This thesis aims to determine how finite wing aerodynamic loads change in proximity to the ground. In this study, the primary design tool is an inviscid panel method code, VORLAX. The validation tool is a commercial volume grid CFD package,

This thesis aims to determine how finite wing aerodynamic loads change in proximity to the ground. In this study, the primary design tool is an inviscid panel method code, VORLAX. The validation tool is a commercial volume grid CFD package, ANSYS FLUENT. I use VORLAX to simulate wings with different incidences and aspect ratios to look at how ground effect impacts spanwise loading and incipient flow separation. Then the results were compared to widely published equations such as McCormick, Torenbeek, and Hoerner & Borst. Because I found that these “famous” equations function best only for specific conditions, I propose a new empirical equation to estimate ground effect lift as a function of aspect ratio and incidence. Using Stratford’s method to predict signs of flow separation in the inviscid solutions, I found that variations in the height above the ground were not significant enough to change the stall angle of low aspect ratio wings. I did find early signs of flow separation with increasing aspect ratio. I observe significant changes in spanwise loading when in ground effect; as I narrow the gap, the transverse loading builds higher near the center of the wing. These effects were more apparent in wings with smaller aspect ratio; higher aspect ratio wings experience a higher loading gradient near the tips in proximity to the ground. I found that high aspect ratio wings have a smaller stall angle compared to that of lower aspect ratio wings; these trends are consistent between the potential flow solution and the volume grid CFD viscous solution.
Date Created
2024
Agent

Bio-Based Scour Mitigation for Underwater Foundation Systems

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Description
In the marine ecosystem, mangrove forests protect the coastline due to their unique prop root system functions as a natural barrier to stabilize sediment and mitigate erosion. Such distinct characteristics provide a design inspiration to reduce local scour around underwater

In the marine ecosystem, mangrove forests protect the coastline due to their unique prop root system functions as a natural barrier to stabilize sediment and mitigate erosion. Such distinct characteristics provide a design inspiration to reduce local scour around underwater foundation systems such as the monopile foundation of offshore wind turbines. In this study, a ring of skirt piles in a circular layout inspired by the mangrove root structure has been proposed which aims to protect the centered monopile foundation. Three main aspects of the mangrove prop root system have been extracted to investigate the scour mitigation effect from the hydraulic, geotechnical, and bio-cementation perspectives. Laboratory flume tests have been conducted to evaluate the anti-scour potential using the proposed skirt pile groups. 3D reconstruction using the photogrammetric method has been employed to reconstruct the scoured bed for quantitative analysis. Computational fluid dynamics (CFD) and discrete element method (DEM) simulations have been performed to investigate the pile-flow and pile-sediment interactions, respectively. Results indicate the proposed skirt pile group reduces the scour depth and the volume of the scour hole by up to 57% and 85%, respectively. DEM simulation implied the installation of skirt piles demonstrates not only hydraulic but also geotechnical benefits due to the soil plug effect. In addition, a reactive transport model framework that simulates the bio-grouting process using microbially induced calcite precipitation (MICP) via shallow underwater injection has been developed to model the key processes such as bacterial attachment and detachment, urea hydrolysis, and calcite precipitation. The simulated cementation distribution exhibits a decent agreement with the experimental results, which could potentially be served for strategic optimization before conducting large or field-scale underwater injection tests. The model framework has been incorporated to simulate the MICP injection using skirt piles. Preliminary findings from this study demonstrated the feasibility of using mangrove-inspired skirt piles to mitigate scour for underwater foundation systems.
Date Created
2024
Agent

Sensing for Wireless Communication: From Theory to Reality

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Description
Millimeter-wave (mmWave) and sub-terahertz (sub-THz) systems aim to utilize the large bandwidth available at these frequencies. This has the potential to enable several future applications that require high data rates, such as autonomous vehicles and digital twins. These systems, however,

Millimeter-wave (mmWave) and sub-terahertz (sub-THz) systems aim to utilize the large bandwidth available at these frequencies. This has the potential to enable several future applications that require high data rates, such as autonomous vehicles and digital twins. These systems, however, have several challenges that need to be addressed to realize their gains in practice. First, they need to deploy large antenna arrays and use narrow beams to guarantee sufficient receive power. Adjusting the narrow beams of the large antenna arrays incurs massive beam training overhead. Second, the sensitivity to blockages is a key challenge for mmWave and THz networks. Since these networks mainly rely on line-of-sight (LOS) links, sudden link blockages highly threaten the reliability of the networks. Further, when the LOS link is blocked, the network typically needs to hand off the user to another LOS basestation, which may incur critical time latency, especially if a search over a large codebook of narrow beams is needed. A promising way to tackle both these challenges lies in leveraging additional side information such as visual, LiDAR, radar, and position data. These sensors provide rich information about the wireless environment, which can be utilized for fast beam and blockage prediction. This dissertation presents a machine-learning framework for sensing-aided beam and blockage prediction. In particular, for beam prediction, this work proposes to utilize visual and positional data to predict the optimal beam indices. For the first time, this work investigates the sensing-aided beam prediction task in a real-world vehicle-to-infrastructure and drone communication scenario. Similarly, for blockage prediction, this dissertation proposes a multi-modal wireless communication solution that utilizes bimodal machine learning to perform proactive blockage prediction and user hand-off. Evaluations on both real-world and synthetic datasets illustrate the promising performance of the proposed solutions and highlight their potential for next-generation communication and sensing systems.
Date Created
2024
Agent