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The Tree That Would Not Fall: An Educator’S Autoethnographic Journey Of Healing Through Words, Raeanna Marie Carlson

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

To say the world has changed since the 2020 COVID-19 shut down is to minimize the micro and macro social changes that infiltrated the school system. In the wake of it all, we find a landscape marred by a both rising teacher attrition and struggling student motivation. This autoethnographic dissertation explores the deeply personal experience tethered to a deeply problematic system that contributes to not only teacher burnout but what I came to know as teacher demoralization. Personal traumas of teachers profoundly impact their experience in the classroom, and as I examined my own near departure from the classroom, I …

Between Two Worlds: A Case Study Of Third Culture Identity And Reentry For Unl International Students, John S. Tessalee

Department of Agricultural Leadership, Education, and Communication: Dissertations, Theses, and Student Research

Third Culture Kids (TCKs) and international students share many commonalities, such as their globalized nature, adaptability, and the adoption of cultural components from their host country versus their home country. However, they contain enough differences to be considered separate groups. Traditionally, people need to be immersed in a culture different from their parents’ culture between the ages of 0 and 18 to be considered a TCK, whereas international students are typically between 18 and 24 years old by the time they attend universities overseas. The cultural absorption of TCKs in their formative years is usually greater than that of international …

Volume 11 Issue 11 (Aug 1912)

The Soul Winner

No abstract provided.

The Impact Of Gender, Training Year, Medical Specialty And The Covid-19 Pandemic On Resident Wellness, Sara Beachy, Jessica Luzier, Chantel Weisenmuller, Kathleen Bors, Mary Ann Maurer, Amna Anees, Tiffany Lasky, Lisa Calderwood

Department of Family & Community Medicine Faculty Papers

INTRODUCTION: Data are limited as to which factors most strongly impact medical trainees' well-being, and few studies have assessed trainee's wellness at multiple time points during the COVID-19 pandemic. Additionally, much research has not taken an intersectional approach to understanding the ways in which different facets of a resident's identity impact their wellness. Thus, more person-centred, probability-driven statistical approaches that can produce distinct heterogenous groups of individuals are warranted to understand the way in which different identities are associated with resident wellness scores.

METHODS: A latent profile analysis was conducted using institutional data from resident surveys administered from 2019 to …

Invisible Algorithms, Visible Outcomes: Roles Of Emotional Labor And Work Gamification In Gigs, Yali Zhang, Liaoliao Li, Xiaoyu Ma, Jun Sun, Yifei Dong, Zhaojun Yang

Information Systems Faculty Publications

As algorithm governance becomes increasingly crucial in gig economy ecosystems, understanding the behavioral impact of algorithmic transparency remains a key research gap. Using the stimulus-organism-response framework and uncertainty management theory, this study examines how platform algorithmic transparency affects gig workers’ in-role and extra-role service behaviors, with emotional labor acting as a mediator and work gamification as a moderator. Analyzing survey data from 325 ride-hailing drivers using partial least squares structural equation modeling (PLS-SEM), the findings reveal that greater algorithmic transparency enhances both in-role and extra-role behaviors. Emotional labor mediates this relationship: deep acting strengthens both behaviors, while surface acting primarily …

An Evaluation Of Interactive Computerized Training To Teach Preservice Speech Language Pathologists To Implement Brief Multiple Stimulus Without Replacement Preference Assessments, Mattie L. Mecham

All Graduate Theses and Dissertations, Fall 2023 to Present

Positive reinforcement is often used when teaching new skills. When working with individuals with developmental disabilities, it can be difficult to determine reinforcing items. Preference assessments can be used to identify items that may function as reinforcers. A multiple stimulus without replacement preference assessment (MSWO) produces a ranking of preferred items and can be conducted quickly. Researchers have utilized interactive computerized training (ICT) to teach behavior analytic skills and procedures. The present investigation aimed to extend previous MSWO training and ICT research by developing and evaluating the effects of an MSWO ICT implemented with speech language pathology graduate students. The …

Cutting Propagation And Out-Planting Of White-Margined Beardtongue (Penstemon Albomarginatus M.E. Jones), A Vulnerable Herbaceous Perennial Of The Mojave Desert), Alexander Stosich

All Graduate Theses and Dissertations, Fall 2023 to Present

Plant biodiversity is crucial for the proper functioning of ecosystems, with many species needed to maintain the variety of functions provided, especially with increasing environmental change. However, plant biodiversity is threatened in many different ecosystems, primarily through habitat loss. Species can be conserved by protecting their original habitat and mitigating for threats such as invasive species or altered disturbance regimes (plant conservation); however, with declining population numbers and continued habitat loss and/or disturbance, it may be necessary to actively move plants (plant restoration). Plant restoration is dependent on developing the capacity to a) reliably propagate plants in a nursery and …

Effects Of Elevation, Fire Age, Burn Severity, And Pre-Fire Vegetation On Post-Fire Sagebrush Songbird Communities, William D. Harrod

All Graduate Theses and Dissertations, Fall 2023 to Present

The Sagebrush Biome of western North America has been threatened by a combination of interconnected threats. In the Great and Columbian Basins, a large portion of sagebrush loss has been due to an increase in higher-severity wildfires, caused by invasive annual grasses. As sagebrush declines, numerous wildlife species that rely on the biome have experienced similar trends. Sagebrush-adapted songbirds such as sage thrasher, Brewer's sparrow, and sagebrush sparrow as well as steppe-songbirds, have all experienced population declines. Currently, limited information exists as to how fire severity or recovery affect these songbirds or what resource managers can do to improve their …

Conceptions Of Climate Change Skepticism: A Phenomenographic Investigation On Perspectives From Climate Scientists And Climate Activists, Candace L. Penrod

All Graduate Theses and Dissertations, Fall 2023 to Present

This study addresses how climate change denial is understood by climate scientists and climate activists. This research also investigates what communication strategies addressing climate change denial are used by climate scientists and climate activists. Phenomenography was selected as a methodology to address the qualitative and quantitative aspects of this inquiry. Pre-recorded data from interviews with six climate scientists and six climate activists living in the Intermountain West were used as the data source. Interview transcripts were read, marked, and coded to identify how climate scientists and climate activists understood climate change denial. Five conceptions of climate change skepticism were identified …

Enabling Sustainability Transitions For Great Salt Lake: Framing Of Public Opinion, Boundary Work, And Policy, Anna Mcentire

All Graduate Theses and Dissertations, Fall 2023 to Present

This dissertation explores how people think about, talk about, and take action to save Great Salt Lake, which reached historic low levels in 2021. Using surveys, public records, and legislative documents primarily from 2022 to 2024, the research examines public opinions, collaborative efforts, and policy changes related to the lake. The first chapter looks at what people value about the lake and what actions they want to see taken. It finds that people are very concerned and want significant efforts to stop the lake's decline. The second chapter investigates how different groups work together publicly to negotiate new understandings, create …

Linking Variation In Mule Deer Nutritional Condition And Age To Population Performance In A Temperate Environment, Kent R. Hersey

All Graduate Theses and Dissertations, Fall 2023 to Present

The amount of body fat animals have as they enter and exit winter can have major impacts on how well they survive and reproduce. Mule deer are widely distributed herbivores whose survival and reproduction are strongly tied to weather patterns and the quality of vegetation they consume, which in turn impacts nutritional condition. The objective of this study was to identify and quantify the factors (animal specific, climatic, or habitat) influencing mule deer body fat during both summer and winter in Utah and examine how nutritional condition influences survival. We found December body fat was most affected by December lactation …

Evaluating The Effects Of Two Key Temporal Intervals During Pavlovian Training On Conditioned Reinforcement, Gabrielle M. Sutton

All Graduate Theses and Dissertations, Fall 2023 to Present

Reinforcers are anything that increases or maintains the frequency of a behavior that precedes their occurrence. Reinforcers can be separated into two types, primary and secondary. Primary reinforcers are biologically relevant stimuli like food, water, or drugs that can influence behavior without any prior training. Secondary reinforcers are those that impact behavior through their trained relationship with a primary reinforcer, like money and tokens. For this reason, they are also known as conditioned reinforcers. Conditioned reinforcers are used in therapies and training designed to increase desirable behaviors, but they are also involved in the development and maintenance of maladaptive behaviors …

A Focus On Student Education: Determining Student Attitudes Towards Transparent Autograding And Developing Artificially Intelligent Tools To Help Students Succeed, Andra Rice

All Graduate Theses and Dissertations, Fall 2023 to Present

This thesis is composed of two parts both relating to helping students succeed. First, the focus is on determining how we can help students feel more comfortable using an AI tool that can provide them immediate feedback. Second, machine learning algorithms are explored in relation to tracking student tasks to encourage healthy study habits.

The development of effective autograders is key for scaling assessment and feedback. While AI based autograding systems for open-ended response questions have been found to be beneficial for providing immediate feedback, autograders are not always liked, understood, or trusted by students. Our research tested the effect …

Temperature Effects On Fruit Doubling And Bloom Prediction In Tart Cherry, Josette M. Moon

All Graduate Theses and Dissertations, Fall 2023 to Present

Tart cherry (Prunus cerasus) is a key horticultural crop in Utah. Extreme summer heat and cold weather in late spring are challenges to tart cherry production causing economic losses. These problematic weather conditions are influenced by the local landscape and are exacerbated by changing climate. This research explores (1) the impact of summer heat stress on fruit deformities, and (2) the accuracy of temperature-based predictions of spring bud development. High temperatures and water stress after harvest are known to cause a deformity known as twin or double fruits, resulting in unmarketable fruit. This disorder has been studied in …

Optimization And Utilization Of Microbial Electrolysis Cells In Waste To Product Applications, Hayden Harrison

All Graduate Theses and Dissertations, Fall 2023 to Present

As the world searches for cleaner and more sustainable energy solutions, turning waste into fuel is an increasingly attractive strategy. This research focuses on microbial electrolysis cells, a new technology that uses bacteria and a small amount of electricity to convert organic waste—like food scraps or wastewater—into useful gases such as hydrogen and methane. These gases can be used as energy sources to reduce dependency on more traditional fuels.

This thesis tackles two key challenges that limit the real-world use of microbial electrolysis systems. First, it introduces a simpler and more effective method to stop hydrogen losses in single-chamber cells. …

Identifying And Examining Stressors In The Secondary And Post-Secondary Classroom, Benjamin S. Alter

All NMU Master's Theses

Students in secondary and post-secondary classrooms are openly exposed to stressors that can be considered impactful in their day-to-day lives.These stressors can be categorized as either “positive,” which serve as motivators, or “negative,” which often cause anxiety. In order to understand the stressors that students experience, students in a rural teacher education program at Northern Michigan University were asked to respond anonymously to a survey asking about stressors at the secondary and post-secondary levels. The survey was given to students enrolled in the Winter & Fall semesters of 2023, and the Winter semester of 2024. Students identified stressors from their …

Are We Safe Yet? Experimental Analysis Of Emergency Post-Alert Messages, Hugh D. Walpole, Jeannette Sutton, Michele K. Olson

Emergency Preparedness, Homeland Security, and Cybersecurity Faculty Scholarship

Wireless Emergency Alerts can offer timely warnings and crucial guidance for people at risk from natural and technological hazards. However, at the time an alert is issued, it is rarely clear how long hazardous conditions will persist and when affected people can return to normal activities. This highlights the potential benefits of issuing post-alert messages to indicate that the hazard has passed; yet in practice, these post-alert messages are rarely used. When they are used, they frequently use operational language focused on the status of the associated alert (i.e. “the alert has expired” or has been “canceled”) rather than information …

Revitalizing Literary Engagement: Innovative Approaches To Teaching Willa Cather In High School English Classes, Sarah Hoyt, Phu Vu

Language Arts Journal of Michigan

This study explores methods to enhance student engagement and interest in high school English literature classes, focusing on the analysis of Willa Cather's novels. It addresses the challenge of motivating students to engage deeply with full-length novels, crucial for cultural and literary education. Employing a qualitative approach and triangulated data sources, the study reveals significant improvements in student engagement, comprehension, and literary analysis. Additionally, students demonstrated a heightened ability to connect with the themes and characters in the prose.

Unburying The "Bury Your Gays" Trope In Young Adult Literature, Brooke Armbrustmacher

Language Arts Journal of Michigan

In this paper, I unpack what the "Bury Your Gays" trope is, how it originated, its purpose, and its contemporary use and impacts. Through analysis of example novels and referenced scholarly articles, I explain how character deaths do or do not align with the trope, exemplifying the broader patterns of the trope and its impacts on young adults. Educators can learn to contextually identify the trope, gain the tools to spark classroom discussion through analysis, and identify examples of novels that disrupt this trope to be implemented in classroom libraries and reading lists.

Reimagining Positionality In Curriculum: Unlocking Consciousness Beyond Hegemonic Boundaries, Haniyeh Kheirkhah Abkenari

Language Arts Journal of Michigan

This paper examines the interplay between hegemonic systems, curriculum, and individual consciousness in diverse life contexts. It underscores the need for critical thinking skills and self-examination to challenge hegemonic ideologies embedded within curriculum materials. The paper emphasizes the potential for curriculum to shape and influence consciousness, yet it also highlights the autonomy of consciousness to critically engage with curriculum content. Positionality and identity are explored, illustrating how they impact an individual's social role and their ability to promote social justice.

Through the Currere as a autoethnography research method, the paper offers a comprehensive reflection on the author's experiences as an …

Independent- August 2025, Leslie Lozada

The Independent (1988-present)

No abstract provided.

Labor, Leisure, And Law, Aneil Kovvali, Jonathan S. Masur

Articles

Americans work harder than their counterparts in many other advanced economies. While many predicted that technological progress would eventually make work obsolete, Americans continue to pull long hours. Although stories of worker burnout and “quiet quitting” suggest that this situation is not a good fit for everyone, any problems are largely invisible to the conceptual frameworks that dominate the analysis of law. These frameworks normally assume the goal of maximizing production and often treat the human preference for leisure as a problem to be solved. This Article analyzes the problem of overwork. In doing so, it surfaces legal and policy …

Development Of A New Groundbased Instrumentation Technique For Low-Resolution Exoplanet Transmission Spectroscopy, Mary Anne Limbach, Luke M. Schmidt, Ryan J. Oelkers, Darren L. Depoy

Physics & Astronomy Faculty Publications

We present a new instrumentation technique for high-precision, ground-based spectrophotometric measurements ideal for low-resolution (R ∼ 20–60) exoplanet transmission spectroscopy. This technique employs novel thin-film coating technology for wide-band, simultaneous multi-band imaging, enabling high-precision differential photometry through self-referencing and comparison stars. Theoretical calculations and on-sky results show that this method effectively reduces 96% of amplitude scintillation noise and other systematics that typically limit ground-based spectrophotometric precision for bright stars. On-sky results are demonstrated using the custom-built Exoplanet Transmission Spectroscopy Imager (ETSI), deployed at the McDonald Observatory 2.1 m telescope in 2022. For a V = 9.7 mag star, ETSI …

Gcot: Chain-Of-Thought Prompt Learning For Graphs, Xingtong Yu, Chang Zhou, Zhongwei Kuai, Xinming Zhang, Yuan Fang

Research Collection School Of Computing and Information Systems

Chain-of-thought (CoT) prompting has achieved remarkable success in natural language processing (NLP). However, its vast potential remains largely unexplored for graphs. This raises an interesting question: How can we design CoT prompting for graphs to guide graph models to learn step by step? On one hand, unlike natural languages, graphs are non-linear and characterized by complex topological structures. On the other hand, many graphs lack textual data, making it difficult to formulate language-based CoT prompting. %Therefore we cannot directly adopt the CoT prompting methods used in the language domain. In this work, we propose the first CoT prompt learning framework …

Ai-Assisted Triage And Decision Support Of Head And Neck Cancer Screening And Diagnosis In Low-Resourced Settings, Min Hun Lee, Sean Shao Wei Lam, Shaun Xin Hong Liew, Michael Dorosan, Nicholas Graves, Jonas Karlström, Hiang Khoon Tan, Walter Tsong Lee

Research Collection School Of Computing and Information Systems

The mortality burden of head and neck cancer (HNC) is increasing globally and disproportionately affects people in low-and middle-income countries with limited medical workforce. To address this issue, artificial intelligence (AI) algorithms are increasingly being explored to process medical imaging data, demonstrating competitive performance. However, the clinical adoption of AI remains challenging as clinicians struggle to understand how complex AI works and trust it to use in practice. In addition, AI may not perform well on varying data qualities of endoscopy videos for HNC screening and diagnosis from multiple sites.In this project, our international and interdisciplinary team will collaborate with …

R2dqg: A Quality Meets Diversity Framework For Question Generation Over Knowledge Bases, Yimeng Ren, Yanhua Yu, Lizi Liao, Yuhu Shang, Kangkang Lu, Mingliang Yan

Research Collection School Of Computing and Information Systems

The task of Knowledge-Based Question Generation (KBQG) involves generating natural language questions from structured knowledge sources, posing unique challenges in balancing linguistic diversity and semantic relevance. Existing models often focus on maximizing surface-level similarity to ground-truth questions, neglecting the need for diverse syntactic forms and leading to semantic drift during generation. To overcome these challenges, we propose Refine-Reinforced Diverse Question Generation (R2DQG), a two-phase framework leveraging a generation-then-refinement paradigm. The Generator first constructs a diverse set of expressive templates using dependency parse tree similarity, capturing a wide range of syntactic patterns and styles. These templates guide the creation of question …

L3net: Localized And Layered Reparameterization For Incremental Learning, Xuandi Luo, Huaidong Zhang, Yi Xie, Hongrui Zhang, Xuemiao Xu, Shengfeng He

Research Collection School Of Computing and Information Systems

Model-based class incremental learning (CIL) methods aim to address the challenge of catastrophic forgetting by retaining certain parameters and expanding the model architecture. However, retaining too many parameters can lead to an overly complex model, increasing inference overhead. Additionally, compressing these parameters to reduce the model size can result in performance degradation. To tackle these challenges, we propose a novel three-stage CIL framework called Localized and Layered Reparameterization for Incremental Learning (L3Net). The rationale behind our approach is to balance model complexity and performance by selectively expanding and optimizing critical components. Specifically, the framework introduces a Localized Dual-path Expansion structure, …

Towards Context-Aware Traffic Classification Via Time-Wavelet Fusion Network, Ziming Zhao, Zhuoxue Song, Xiaofei Xie, Zhaoxuan Li, Jiongchi Yu, Fan Terry Zhang, Tingting Li

Research Collection School Of Computing and Information Systems

Encrypted traffic classification occupies a significant role in cybersecurity and network management. The existing encrypted traffic classification technology mostly relies on intra-flow semantics for extracting features. However, considering that some attack behaviors inherently have similar patterns to legitimate behaviors, and powerful adversaries could simulate benign users to conceal their attack intentions, intra-flow features may be similar between different categories. In this paper, we propose TrafficScope, a time-wavelet fusion network based on Transformer to enhance the performance of encrypted traffic classification. Specifically, in addition to using intra-flow semantics, TrafficScope also extracts contextual information to construct more comprehensive representations. Moreover, to cope …

Cami: A Counselor Agent Supporting Motivational Interviewing Through State Inference And Topic Exploration, Yizhe Yang, Palakorn Achananuparp, Heyan Huang, Jing Jiang, Phey Ling Kit, Nicholas Gabriel Lim, Cameron Shi Ern Tan, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Conversational counselor agents have become essential tools for addressing the rising demand for scalable and accessible mental health support. This paper introduces CAMI, a novel automated counselor agent grounded in Motivational Interviewing (MI) – a client-centered counseling approach designed to address ambivalence and facilitate behavior change. CAMI employs a novel STAR framework, consisting of client’s state inference, motivation topic exploration, and response generation modules, leveraging large language models (LLMs). These components work together to evoke change talk, aligning with MI principles and improving counseling outcomes for diverse clients. We evaluate CAMI’s performance through both automated and expert evaluations, utilizing simulated …

Assessing The Robustness Of Test Selection Methods For Deep Neural Networks, Qiang Hu, Yuejun Guo, Xiaofei Xie, Maxime Cordy, Wei Ma, Mike Papadakis, Lei Ma, Yves Le Traon

Research Collection School Of Computing and Information Systems

Regularly testing deep learning-powered systems on newly collected data is critical to ensure their reliability, robustness, and efficacy in real-world applications. This process is demanding due to the significant time and human effort required for labeling new data. While test selection methods alleviate manual labor by labeling and evaluating only a subset of data while meeting testing criteria, we observe that such methods with reported promising results are simply evaluated, e.g., testing on original test data. The question arises: are they always reliable? In this article, we explore when and to what extent test selection methods fail. First, we identify …