Digital Commons Network^™

Staff Attitudes Toward Ai Adoption At A Private Research University, Ashley C. Smith

Theses and Dissertations

This study addresses the limited research on university staff attitudes toward artificial intelligence use and adoption. Using the Unified Theory of Acceptance and Use of Technology (UTAUT) research framework, the General Attitudes towards Artificial Intelligence Scale (GAAIS), and quantitative survey methodology, the study examines the attitudes of higher education staff toward AI, specifically examining whether demographic or professional characteristics are factors. The findings indicate that staff had moderately negative attitudes toward AI while also expressing some concerns. The results suggest that more resources and support for AI are needed for staff to address concerns. It also suggests that construct-level analysis …

Middle School Students' Initial Ideas And Their Connections In Proportion Word Problems, Carrie Ann Lawton

Theses and Dissertations

In this dissertation study, I sought to identify the initial ideas that middle school students had when approaching Multiple Batches and Variable Parts proportion word problems, as well as the connections they made among those initial ideas. I conducted semi-structured individual and paired interviews with 13 sixth- and seventh-grade students at the end of their school year. I then used the Knowledge-in-Pieces theoretical perspective to identify knowledge resources that the participants accessed when approaching the tasks, prior to any intervention on my part.

Through my analysis, I identified 18 initial ideas that the middle school students employed when solving the …

Theoretical Analysis Of Filtering And Smoothing Techniques In Stochastic Time Series, Kaosarat Bola Azeez

Theses and Dissertations

Polynomial-preserving linear filters are fundamental tools for smoothing and trend extraction in noisy time series, particularly when the objective is to reduce short-run variation without distorting underlying low-degree structure. This thesis develops a general framework for such filters based on local polynomial approximation and least-squares estimation. In particular, we establish that the resulting estimators can be represented as symmetric linear filters whose weights satisfy moment conditions that ensure exact polynomial reproduction up to a specified degree. Building on this framework, we derive explicit coefficient vectors for several classical smoothing filters, including the Savitzky-Golay filters SG(5,2) and SG(7,3), as well as …

Vocabulary Assessment And Washback: English Teachers' Practices In Preparing Students For The Wassce In Ghana, Ishmael Nii Amon Neequaye

Theses and Dissertations

Persistent concerns in WAEC Chief Examiners’ Reports consistently attribute declining student performance on the WASSCE English Language examination to limited vocabulary knowledge. Despite these recurring observations, little research has explored how teachers respond to the vocabulary demands embedded within this high-stakes examination. This qualitative study investigates (1) how Senior High School English teachers prepare students for the vocabulary demands of the WASSCE English paper and (2) how the assessment pressures influence instructional practices and classroom decision-making.  Drawing on communicative competence, multiliteracies, and washback, the study employed a descriptive case study design and thematic analysis of semi-structured interviews and focus group …

Schiff Bases As Versatile Platforms: From Multinuclear Dysprosium Complexes To Halogen-Mediated Quasiracemic Crystal Engineering, Macy M. Michorczyk

Theses and Dissertations

Understanding the factors that govern molecular assembly is fundamental in both coordination chemistry and crystal engineering. This thesis investigates these processes through two studies that employ single-crystal X-ray diffraction to elucidate the structural principles underlying the formation of multinuclear metal complexes and the crystal packing of quasiracemates.

The first study examines the unexpected formation of multinuclear metal complexes. Structural characterization of a series of dysprosium complexes was used to compare molecular architectures and identify structural relationships that support a proposed pathway of formation. These findings shed insight into the assembly process that may have lead to their formation.

The second …

Does The Powder River Pass Shear Zone Exist? Geologic Map And Geochronology Of The Bighorn Mountains Caribou Creek 7.5-Minute Quadrangle, Lula G. Staley

Theses and Dissertations

This study produced a 1:24000-scale geologic map of the Caribou Creek 7.5-minute quadrangle in the Bighorn Mountains, Wyoming, by integrating field observation and U-Pb zircon age data. The results of this study will contribute to the USGS EDMAP program by subdividing the southern gneiss terrain. The quadrangle occurs almost entirely in the Bighorn National Forest and is in the drainage of Clear and Crazy Woman creeks. Elevations range from 6,800-9,400 ft. The quadrangle is dominated by Archean crystalline rocks of the Wyoming Province Beartooth-Bighorn Magmatic terrane, mainly granodiorite and tonalite gneiss with lesser migmatite. Several orientations and ages of mafic …

Reconceptualizing Instructional Supervision For Stem Education In The Digital Age, Armen Alvarez

Theses and Dissertations

This conceptual thesis reconceptualizes instructional supervision for AI-enabled STEM teaching in the Digital Age. Traditional supervision models, including clinical, developmental, and cognitive coaching, emphasize human-centered observation and feedback but lack guidance for supervising AI-mediated instruction, interpreting algorithmic outputs, and addressing neurodiverse learner variability. Using integrative literature review methodology, this thesis synthesizes scholarship across five theoretical foundations: epistemic perspectives, the neurodiversity paradigm, Universal Design for Learning, human-centered AI and educational leadership, and supervision literature.

The resulting conceptual framework organizes supervisory attention into four interconnected domains:

• human-centered AI use in teaching and assessment,
• neurodiversity- and UDL-informed pedagogy,
• relational and compassionate classroom climate, …

Effects Of Interpersonal Emotion Regulation Strategies On Job Attitudes And Well-Being, Kara Cannon

Theses and Dissertations

Interpersonal emotion regulation involves using social interactions to influence their own or another’s emotions (Gross, 1998). Although previous research has examined the relationships between intrapersonal emotion regulation and workplace outcomes, there is a lack of research on interpersonal emotion regulation in the workplace context. The current study extends this research by examining the relationships between interpersonal emotion regulation strategies, co-rumination, well-being, and job satisfaction, and examines which interpersonal emotion regulation strategies are better predictors of the outcome variables than others. Positive correlations between interpersonal emotion regulation strategies and well-being and between co-rumination and well-being were found. Perspective taking and enhancing …

Investigating Phosphorus Load Trends And Driving Factors In Illinois Watersheds Using Machine Learning Algorithms, Hannah Lartey

Theses and Dissertations

Phosphorus (P) pollution in Illinois watersheds has become a significant water quality concern. Recent studies have shown increasing concentrations in streams and rivers, leading to eutrophication, which damages aquatic ecosystems and threatens human health. This study examines temporal trends in total phosphorus loads across 79 monitoring stations in Illinois from 1979 to 2020 and identifies the main environmental factors that influence P load variability. Trend analyses were conducted using the nonparametric Mann-Kendall and Sen’s slope methods. GIS-based climate, hydrology, and soil property datasets were assembled for each monitoring station. These datasets were used to build machine learning models using the …

How And Why Preservice Mathematics Teachers’ Respond To Students’ Statistical Thinking, Radhika Pathak Kharel

Theses and Dissertations

Researchers have found that how preservice teachers (PSTs) respond to students' thinking is crucial to their students' learning and to PSTs' own teaching effectiveness. Although there are some research studies on how teachers respond, there is relatively scarce research on why PSTs respond to students’ thinking the way they do. Such understanding is crucial for designing mathematics methods courses and other professional development opportunities that enable PSTs to create more thoughtful and effective teaching plans. I examined how and why PSTs respond in-the-moment to students’ statistical thinking. The study involved 16 PSTs who enrolled in a middle school mathematics methods …

Resilience For Whom? A Study In Pathways And Production Of Unequal Risk In The Rockaways, Aaryan M. Nair

Publications and Research

This paper investigates how climate adaptation policies in the Rockaway Peninsula of New York City produce unequal outcomes despite their ostensibly neutral design, framing resilience as an environmental and climate justice problem. Situated within a landscape marked by stark socioeconomic disparities, aging housing stock, and high exposure to coastal flooding, the study demonstrates that existing adaptation strategies—centered on uniform technical standards, insurance frameworks, and large-scale coastal infrastructure—systematically advantage actors with greater financial and institutional capacity while leaving low-income residents, particularly renters, disproportionately vulnerable.

The analysis identifies three core dynamics underlying this “unequal-by-design” resilience regime: (1) the stratified feasibility of compliance …

The Law And Economics Of Resilience, Doni Bloomfield, Jeff Gordon

Faculty Scholarship

The field of law and economics has long studied externalities, the costs and benefits actors create and yet fail to internalize. But scholars have largely overlooked a set of externalities that lead firms across the economy to systematically underinvest in resilience, with macroeconomically harmful consequences. In this Article, we address this gap with a theory of the law and economics of resilience, by which we mean the ability of markets to reliably and optimally meet demand for goods and services without extreme price fluctuations. 

We argue that corporate resilience is determined by a conflict between two basic forces: the resilience …

High Stakes And Random Rewards: A Critical Look At Loot Boxes And Illegal Gambling, Brian T. Wersan

Touro Law Review

Since their inception in the mid-2000s, loot boxes have been legal and virtually unregulated in the United States. Ever-growing mountains of evidence demonstrate the harms of loot boxes, but their structure has not yet been found to be in violation of any current U.S. gambling law, leading to a complete lack of recovery for victims. Certainly, if people experience harm, a legal avenue providing justice must exist. While other avenues are referenced, this Note ultimately argues that loot boxes can be interpreted by courts to satisfy the elements of, and thus, violate multiple state gambling laws, revealing a path to …

Evaluating Supplementation Strategies Using Precision Livestock Technologies And Energy Based Models In Developing Beef Heifers Grazing Dormant Rangeland, Kali-Jo Bentz

Electronic Theses and Dissertations

Replacement beef heifer development in extensive grazing systems is challenged by variation in forage quality, supplement intake, and animal behavior, all of which influence the ability to achieve targeted growth prior to breeding. Precision livestock technologies (PLT) enable continuous monitoring of individual animal performance, while energy-based nutritional models support individualized supplementation. However, their application under extensive grazing conditions remains poorly understood. Therefore, the objectives of this thesis were to (1) evaluate heifer utilization of multiple precision livestock technologies and their relationship with animal performance and (2) evaluate the accuracy of an individualized energy-based supplementation model by comparing predicted supplement allotments …

Beyond Assumptions: What Students Really Think About School Wellbeing Programs, Amanda Madden

Research outputs 2022 to 2026

The study examined students’ perceptions of effective components in school-based wellbeing programs, addressing a critical gap where adolescent voices are absent. Data was gathered through a questionnaire, individual interviews, and focus groups conducted with 36 Year 12 students across three independent co-educational schools in Western Australia. Thematic analysis identified seven key components essential for effective wellbeing programming: targeted content providing respite from academic pressures, engaging and relatable presenters, strategic timing, developmental appropriateness, meaningful measurement, genuine teacher engagement, and authentic incorporation of student voice. Students valued practical, non-academic content and expressed scepticisms about teacher-delivered programs. Timing emerged as a previously underexplored …

Reflecting On Themes From Telehealth Consultations Early In The Pandemic: An Opportunity To Learn From Multiprofessional Colleagues, Maggie Meeks, Laura R. Joyce, John Dean, Lorna Davies, Tika Ormond, Philippa Seaton, Dale Sheehan, Dean Sutherland, Melanie Welfare, Arindam Basu

Research outputs 2022 to 2026

Aims: This study is aimed at documenting the reflections of New Zealand healthcare professionals on the use of synchronous telehealth consultations. Methods: A qualitative narrative inquiry was conducted to explore the practice of telehealth in New Zealand. Purposive sampling was used to identify clinicians from multiple professions who used telehealth during the initial phase of the COVID-19 pandemic. Fifteen semistructured interviews were conducted between October 2020 and May 2021 with clinicians from primary and secondary care, including multiple professional backgrounds. Interview transcripts were analysed thematically. Results: Six themes were identified: (1) equitable access: There were concerns regarding equitable access to …

Optimizing Subgroup Selection In Petrochemical Industries: A Robust Data Envelopment Analysis Approach For Uncertainty Management, Sadegh Niroomand, Hilda Saleh, Morteza Shafiee, Dragan Pamucar, Ali Mahmoodirad

Research outputs 2022 to 2026

This study addresses the critical challenge faced by organizations in selecting an optimal subgroup of decision-making units (DMUs). Such a selection procedure can significantly influence efficiency, profitability, and strategic development. Recognizing the limitations of existing methods in handling inexact data and incorporating managerial preferences, this study proposes a novel framework that integrates data envelopment analysis (DEA) with binary linear programming models. The model applies belief-degree–based representations of uncertainty to capture imprecise inputs and outputs. For this model, two solution approaches—namely, chance-constrained programming and expected value approaches—were developed. These approaches are suitable for real-world applications using standard optimization software. The effectiveness …

Feeling Giggity: Ambiguous Emojis In Teaching And Learning Communications, Mary Kynn, Nicole Reinke, Eva Hatje

Research outputs 2022 to 2026

There is an increase in the number of digital platforms used in higher education classrooms that promote using emojis to capture students’ emotions. However, there is little evidence to suggest that interpretation of emojis is reliable in this context. This pilot project explored if emojis can reliably signify the emotions expressed by first-year university students. Students were asked to record their emotions by selecting a representative emoji and using free text to describe its meaning. A total of 72 responses were recorded in an anonymous online survey. Happy face emojis were used more frequently than emojis representing neutral or unpleasant …

Attacks And Detections In Recommender Systems: A Comprehensive Analysis For Models, Progresses, And Trends, Yan Feng, Zhihai Yang, Kexin Li, Jianxin Li, Pinghui Wang, Zhiquan Liu

Research outputs 2022 to 2026

Recommender systems (RSs), as crucial components of online services, can help users efficiently obtain information they may like. In reality, RSs face long-term threats. Attackers manipulate recommendation results by injecting malicious data in order to obtain benefits. At present, research on the security of RSs lacks a comprehensive understanding of attack capabilities. Moreover, existing defense strategies have not yet been systematically associated with attack characteristics. More importantly, existing defense methods rarely focus on real unlabeled data in practical application scenarios for anomaly detection and forensics. Therefore, this survey systematically analyzes the security of RSs and provides new insights. Specifically, we …

Concerted Proton Transfer In Homogeneous And Heterogeneous Cyclic Hydrogen-Bonded Clusters Of H2o, Hf, And Hcl, Max R. Tucker, Yuan Xue, Nathan R. Speake, Eden Nickolson, Jeremy M. Carr, Gregory S. Tschumper

Chemistry Faculty Research & Creative Works

This work examines various homogeneous and heterogeneous clusters of hydrogen-bonded (HF)x(H₂O)y(HCl)z complexes, where x + y + z = 3 or 4. For each unique cyclic structure associated with the xyz permutations, the geometries of the reactant, product, and transition state (TS) for concerted proton transfer (CPT) were fully optimized using second-order Møller-Plesset perturbation theory (MP2) with a mixed basis set consisting of cc-pVTZ for H atoms and aug-cc-pVTZ for O, Cl, and F atoms (denoted haTZ). Harmonic vibrational frequencies were also computed at the same level of theory to verify the nature of the stationary points. Intrinsic …

Managing And Accelerating The Circular Economy Transitions Within The Construction Value Chain Using Network Governance And Game Theory Systems Perspectives, Radwa Eissa, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The fragmented nature of the construction industry has hindered its transition toward circular economy (CE) practices. While game theory (GT) has been successfully applied to support the strategic decisions of CE transitions in other sectors, CE-GT models in the construction domain remain extremely limited. This paper addresses two research questions: (1) how are CE network governance activities currently modeled using GT across domains? (2) How can such models be transferred and adapted to solve strategic interactions within the construction value chain in a manner that enables CE practices to emerge as equilibrium outcomes? These questions are driven by the need …

Multidimensional Analysis Of Human Outdoor Comfort: Integrating Just-In-Time Adaptive Interventions (Jitais) In Urban Digital Twins, Binyu Lei, Pengyuan Liu, Kunihiko Fujiwara, Mario Frei, Clayton Miller, Xuan Yun Chua, Filip Biljecki

Research Collection College of Integrative Studies

How can bidirectional information exchange be enhanced in urban digital twins, and support human-centric data and processes? Their key characteristic is the nearly real-time exchange of information, allowing adjustments to physical environments based on simulations and analytics within virtual models. Yet, achieving such interaction remains challenging, particularly regarding device deployment and infrastructure development. Embracing the concept of humans as sensors, this work develops a two-way framework based on the emerging concept of just-in-time adaptive interventions (JITAIs), exploring how urban digital twins can play a role in understanding and enhancing human comfort outdoors. Human comfort outdoors is inherently spatio-temporal and personalised, …

Curriculum Approaches To Strengthening Student Employability And Improving Graduate Outcomes In The Stm Disciplines, Denise Jackson, Michael D. O’Connor

Research outputs 2022 to 2026

In Australia and elsewhere, curriculum improvements are needed to improve the development of Science, Technology and Mathematics (STM) graduates for future work and careers. Several studies document significant STM student attrition, poor graduate preparedness for work, relatively weak employment rates post-graduation, and mismatched expectations of graduate capabilities by employers. The inclusion of work-integrated learning (WIL) activities within curricula can better prepare students for relevant employment by bridging discipline-specific teaching with work practices. Traditionally, access to WIL has been limited for STM Bachelor students and a better understanding of WIL’s benefits and impact is needed to refine and extend STM WIL …

Exploring New Poly-Anion Based Materials For Lithium – Ion Battery Cathodes, Sutapa Bhattacharya

Doctoral Dissertations

The escalating global demand for sustainable energy storage solutions has driven intensive research into novel electrode materials. Polyanion-based cathode materials have emerged as promising candidates due to their structural stability, safety, and voltage tunability enabled by the inductive effect of polyanionic groups. This research explores the synthesis, crystal structure, and electrochemical performance of new polyanion-based cathode materials featuring vanadium, molybdenum, and iron within phosphate and selenite frameworks.

Novel selenite-based materials, such as LiFe(SeO₃)₂ and Li₀.₂₅V₂O₃(SeO₃)₂, were synthesized and characterized, revealing stable electrochemical cycling associated with Fe2+/Fe3+ and V⁴⁺/V⁵⁺ transitions. Additionally, a systematic investigation was conducted on molybdenum phosphate compounds, including …

Trust-Aware Algorithms For Stackelberg Ground Vehicle Routing, Doris Evelyn Meredith Brown

Doctoral Dissertations

Despite decades of research focused on reducing ground vehicle traffic congestion, urban traffic networks worldwide continue to experience traffic flows that lead to increased network travel times, largely resulting from the routing decisions of individual vehicles. To address this challenge, this work leverages a Stackelberg game framework to model the interaction between a vehicle agent and a routing authority as a leader–follower game, in which the routing authority proposes routing interventions to which the agent responds. This research contributes to existing traffic mitigation literature by exploring the role of trust in route decision-making and providing trust-aware algorithms that influence vehicle …

Essays On Accelerated Failure Time Models For Recurrent Event Data, Emmanuel Masavo Djegou

Doctoral Dissertations

Recurrent event data arise in many fields such as medicine, reliability, insurance, and economics, where the same event may occur repeatedly for a subject. Accelerated Failure Time (AFT) models provide an intuitive framework for relating covariates to event times and offer a useful alternative to proportional hazards models, allowing direct prediction of event timing under right censoring. However, existing AFT extensions for recurrent events, such as accelerated gap time (AGT) models, often fail to account for interventions between events and may not capture complex temporal patterns.

In this work, we first propose a class of semiparametric AGT models incorporating an …

Encryption And Globalization 15 Years Later: End-To-End Encryption And The Third Round Of The "Going Dark" Debate, Peter Swire, Kenesa Ahmad, Michael Specter

Fordham International Law Journal

No abstract provided.

Evaluating The Use Of Machine Learning For Road Maintenance Cost Estimation, Shahla Shirinzad, David Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

Accurate estimation of highway maintenance costs is essential for efficient resource allocation and long-term infrastructure sustainability. This study evaluates the effectiveness of advanced machine learning models, including ResNet, Transformer, and other neural network architectures, for forecasting maintenance costs using historical data from the Highway Maintenance Improvement Program (HMIP) provided by the North Carolina Department of Transportation (NC DOT). A comprehensive comparative analysis is conducted across multiple models using standard performance metrics, including R², MAE, RMSE, and MSE. The results demonstrate that advanced architectures, particularly ResNet and Transformer, consistently outperform traditional statistical approaches and baseline machine learning models, achieving …

Solving High-Dimensional Differential Equations Using Recurrent And Residual Neural Network Architectures, Hind Khaled Kolaib

Knowledge Engineering and Data Science

High-dimensional Partial Differential Equations (PDEs) form the foundation of complex process modeling in various scientific and engineering applications, including finance, physics, and optimal control. However, classical numerical methods are adversely affected by the curse of dimensionality, making them inapplicable for large-scale problems. Recently, however, deep learning-based approaches have provided a new toolbox for these high-dimensional PDEs, including methods such as the Deep Backward Stochastic Differential Equation (Deep BSDE) method. Our approach draws on a more sophisticated deep learning backbone, using neural networks (in our case, a Residual Neural Network and a Long Short-Term Memory network (LSTM) integrated into the Deep …

Deep Learning Based High-Resolution Electromagnetic Inversion Imaging Using Deep Convolutional Double-Module Structure, He Ming Yao, Shiji Song, Lijun Jiang, Michael Ng

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a novel deep learning (DL) approach has been proposed to realize high-resolution electromagnetic (EM) inversion imaging. The newly proposed approach is based on the deep convolutional double-module structure (DCDMS), consisting of the pixel-interpolating module and the corresponding quality-improving module. While the pixel-interpolating module roughly increases the 'resolution' of the initial input, the following quality-improving module realizes quantitative EM imaging in high resolution. The input of the proposed DCDMS adopts the mixed input scheme, consisting of the received EM scattered field and the initial reconstruction in much low resolution computed from Gauss-Newton method. The output of the proposed …