Digital Commons Network^™

Designing An Effective Motivational Climate: Effects On Students’ Effort And Achievement, Margaret Ellis, Brett D. Jones, Fei Gu, Hande Fenerci

International Journal for the Scholarship of Teaching & Learning

We present a case study that demonstrates how instructors can intentionally design a positive motivational climate in online and hybrid courses. We also examine the extent to which students’ perceptions of the motivational climate predict their effort and achievement across three different modalities (face-to-face [FTF], online, and hybrid) of the same course. We surveyed students in an undergraduate computer science course once a semester for three consecutive years (FTF in Year 1, online in Year 2, and hybrid in Year 3). Measures included motivation-related scales and final course grades. Our findings, based on survey responses from 981 students, demonstrate that …

Building A Grassroots Learning Assistant Program, Katie V. Johnson, Lindsay A. Singh, Laura J. Frost

International Journal for the Scholarship of Teaching & Learning

Learning Assistants (LAs) are undergraduates who work in active-learning classrooms with students facilitating discussions and encouraging deeper thinking, while also receiving pedagogical training. We describe how we built an LA program at a regional comprehensive university starting as a grassroots STEM initiative to recruit teachers, and expanding into a campus-wide multi-disciplinary program focusing on student success in a variety of general education courses. Additionally, in the 2020-2021 academic year, we conducted a formative assessment to further understand the program's impact. Our findings revealed strong alignment among students, faculty, and LAs regarding the LA's role in student learning. Qualitative themes from …

Practice What We Preach?: A Review Of Journal Publishing Practices Related To Reflective Writing In Sotl, Laura Cruz, Eileen Grodziak, Hillary H. Steiner, Laura Cruz

International Journal for the Scholarship of Teaching & Learning

Scholarship of Teaching and Learning (SoTL) scholars have long advocated for the inclusion of reflective writing as a legitimate form of scholarship. That said, for those instructors seeking to publish their reflective work, especially scholarly personal narratives (SPNs), there are persistent gaps between the aspirations of the field and the realities of scholarly publishing. The present study seeks to illuminate that gap through a systematic analysis of the policies and practices of academic journals as they pertain to the publication of reflective writing in SoTL. The ultimate aim of the study is to enable editors to close the gap between …

Starting And Sustaining An International Teacher Collaboration: Insights And Recommendations From A Sotl Project., Lindsay J. Neill, Heather Swenson Brilla, Neil Haigh

International Journal for the Scholarship of Teaching & Learning

During the COVID-19 pandemic, two higher education teachers, located respectively in the United States and Aotearoa New Zealand, collaborated in the design of curricula on the relationship between identity and food for their students. Intended to help their students develop cross-cultural knowledge and relationships, they hoped that their collaboration would also benefit their professional relationship and learning at a time when these aspects of their teaching lives were negatively impacted by COVID-19. As a contribution to the scholarship of teaching and learning (SoTL), they undertook, with the help of a researcher colleague, an investigation of (a) factors that influenced their …

Forming International Collaborations For Sotl Research: An Autoethnographic Reflection, Emily Faulconer

International Journal for the Scholarship of Teaching & Learning

This essay serves as a personal narrative to share experiences and lessons learned in using a sabbatical to form international collaborations for SoTL research. I share my motivations for seeking an international collaboration, explore my predicted and realized benefits, and address challenges encountered including time constraints and administrative barriers.

Analysis Of Vibratory Pile Drivers Using Longitudinal And Rotational Oscillations With A Purely Plastic Soil Model, Don C. Warrington

UTC Spring Research and Arts Conference

Driving piles by longitudinal vibrations has been a proven technology since the Gorky dam project in the late 1940’s. Shortly after that drivers which included both longitudinal and rotational oscillations were developed for driving tubular piles, both steel and concrete. Recent renewed interest in this technology for large offshore piles has occasioned the re-examination of the analysis of these piles using methods similar to those that Soviet developers used. In this paper a purely plastic model for both shaft and toe resistance is used parametrically to analyse the performance of these machines. Starting with the free-hanging case of no resistance …

New Teacher Induction Program For Mathematics And The Natural Sciences, Deborah A. Mcallister, Jennifer R. Lynberg, Jason R. Gordon, Lisa S. Wilkes

UTC Spring Research and Arts Conference

The induction program focused on classroom activity. Several topics were based upon Danielson’s Framework for Teaching. Induction activities were drawn from the framework’s four domains: planning and preparation, learning environments, learning experiences, and principled teaching. In addition, reading topics included high-impact teaching strategies, misconceptions in mathematics, and classroom management. Another induction segment was exploration of public science projects. Themes across responses were noted. For classroom management, common themes included all students being capable of learning, each student learns in different ways, and building strong relationships with students is critical. For lesson preparation, the most common area of strength was learning …

Booktok: The Cultural Phenomenon Introducing A Stagnated Industry To A New Generation, Daley Culberson

UTC Spring Research and Arts Conference

BookTok, a creator-driven subset of TikTok that promotes and discusses books, gained popularity in 2020. Its emergence has significantly altered the book industry, allowing once-unknown authors to transform into bestselling novelists with the click of a button. Modern romance, fantasy, and young adult novels are typically favored on BookTok. These novels are vastly different from the books in the traditional literary canon, challenging conventional ideals regarding what types of literature could be considered canonical. Additionally, BookTok is primarily driven by younger users, allowing many teenagers and young adults to rediscover the joy found through reading and writing. This research project …

Prevalence Of Pi*Z And Pi*S Alleles Of Alpha-1-Antitrypsin Deficiency: A Study On Hardy-Weinberg Equilibrium, Foster Opoku, Ziwei Ma

UTC Spring Research and Arts Conference

The α1-Antitrypsin (AT) functions as the primary serum inhibitor of proteolytic enzymes, including neutrophil elastase. The presence of these abnormal alleles disrupts the normal functioning of α1-Antitrypsin (AT), leading to Alpha-1 Antitrypsin Deficiency (AATD). Homozygotes for type Z experience a substantial reduction in serum AT concentration, increasing the risk of pulmonary emphysema or hepatic cirrhosis. Homozygous S alleles and heterozygotes of type SZ exhibit a less severe reduction in serum AT concentration. Clinicians suggest that even though the reduction is less severe, it may still lead to Mild AAT Deficiency.

The primary objective of this study was to enhance our …

Cyberbullying Detection On Twitter Data Using Machine Learning Classifiers, Pradip Dhakal

Data Science and Data Mining

This study compares some of the popular machine learning techniques like Logistic Regression, Multinomial Naive Bayes, K-Nearest Neighbor, and Extreme Gradient Boosting to classify the tweets into three different categories: cyberbullying based on religion, cyberbullying based on ethnicity, or no cyberbullying. First, various data-cleaning approaches are used to clean the tweet data. After the data is clean and ready, the word embedding techniques, such as a bag of words and term frequency-Inverse document frequency, are used to convert the words into mathematical vectors. Finally, the model will be fitted using the combination of the above-mentioned word embedding techniques and machine …

Agent-Based Modeling For The Neophyte: An Application Of Netlogo, Olcay Akman, Siddharth Bhumpelli, Christopher Hay-Jahans

Spora: A Journal of Biomathematics

Agent-based modeling has found applications in a wide range of fields including economics, sociology, ecology, epidemiology, transportation planning, and more. Its versatility allows researchers to investigate various “what-if” scenarios, test the effects of different policies or interventions, and gain insights into the underlying mechanisms driving complex systems. This article is intended for the curious student or researcher who is unfamiliar with agent based modeling, and is looking for a quick but reasonably informative exposure to the field.

Empirical Exploration Of Software Testing, Samia Alblwi

Dissertations

Despite several advances in software engineering research and development, the quality of software products remains a considerable challenge. For all its theoretical limitations, software testing remains the main method used in practice to control, enhance, and certify software quality. This doctoral work comprises several empirical studies aimed at analyzing and assessing common software testing approaches, methods, and assumptions. In particular, the concept of mutant subsumption is generalized by taking into account the possibility for a base program and its mutants to diverge for some inputs, demonstrating the impact of this generalization on how subsumption is defined. The problem of mutant …

Sustainable And Cost-Effective Work Zone Scheduling On Two-Lane Highways With Managed Lanes, Ahmed Z. Edrees

Dissertations

Roadway maintenance projects greatly influence the roadway capacity, resulting in potential traffic disturbances captured by delays. Additionally, costs associated with these projects tend to be exorbitantly extensive. Most agencies and planners try to find a solution that minimizes roadway maintenance costs, traffic delays, crash risks, and environmental impact.

Work zones on two-way two-lane roadway typically avoids high-demand periods. Lane-closure scenario is commonly used and converts the open lane into a phantom intersection, alternating two-direction movements on one lane with the help of a flagger or a temporary signal. Alternatively, using shoulders as temporarily managed lanes allows for simultaneous two-way movements …

Network Slicing And Noma Enabled Mobile Edge Computing For Next-Generation Networks, Mohammad Arif Hossain

Dissertations

The advent of next-generation wireless networks ushers in a new era of potential, harnessing cutting-edge technologies like mobile edge computing (MEC), non-orthogonal multiple access (NOMA), and network slicing as pivotal drivers of transformation. Within this landscape, an innovative approach is proposed by introducing a NOMA-enabled network slicing technique within MEC networks. This approach aims to achieve multiple objectives: meeting stringent quality of service requirements, minimizing service latency, and enhancing spectral efficiency. By seamlessly integrating NOMA with network slicing in edge computing environments, significant reductions in overall latency are achieved, alongside ensuring optimal resource allocation for NOMA users. To address these …

Integrating Laser Charging And Drones For Secure Edge Computing, Weiqi Liu

Dissertations

Drone-mounted base stations (DBSs) have emerged as a promising solution to enhance the flexibility and coverage of wireless networks, potentially revolutionizing communication systems. This dissertation explores the integration of DBSs into 5G and beyond networks, focusing on methodologies to optimize their deployment and performance. A laser charging-enabled DBS framework is proposed to extend flight time and enhance network coverage. By leveraging laser charging technology, the DBS can receive continuous energy transmission from a ground-based charging station while providing communication services to users. The framework is formulated as an optimization problem to jointly maximize flight time and communication data rate, while …

On The Ubiquity, Properties And Evolution Of Small-Scale Magnetic Flux Ropes In The Heliosphere, Hameedullah Farooki

Dissertations

The solar wind is a plasma constantly blowing out from the Sun with a large-scale magnetic field having significant local complexity at small scales. Small-scale magnetic flux ropes (SMFRs), plasma structures with twisted field lines, are an important element of this complexity. This dissertation contributes several studies that further our understanding of SMFRs. The first study applies machine learning to measurements from Wind labeled by the presence of SMFRs and magnetic clouds (MCs). MCs were distinguished from non-MFRs with an AUC of 94% and SMFRs with an AUC of 89% and had distinctive plasma properties, whereas SMFRs appeared to be …

Computational Microscopy For Biomedical Imaging With Deep Learning Assisted Image Analysis, Yuwei Liu

Dissertations

Microscopy plays a crucial role across various scientific fields by enabling structural and functional imaging with microscopic resolution. In biomedicine, microscopy contributes to basic research and clinical diagnosis. Conventionally, optical microscopy derives its contrast from the amplitude of the optical wave and provides visualization of the physical structure of the sample qualitatively. To understand the function at the cellular or tissue level, there is a need to characterize the sample quantitatively and explore contrast mechanisms other than light intensity. Image enhancement or reconstruction from microscopic imaging systems is known as computational microscopy, and it involves the application of computational techniques …

Interaction Of Particles With Plasma And Shock Produced By Pulsed Spark Discharge, Shomik Mukhopadhyay

Dissertations

Interactions of powders with high-temperature plasma and shockwaves occur in diverse scenarios, such as nuclear blasts, accidental industrial dust explosions, solid propellant combustion in explosive charges and when removing contaminants from surfaces. Electrostatic Discharge (ESD), known for generating shock and plasma, is a promising lab-scale technique for simulating these interactions. Studies with ESD involved placing powders near a spark-producing gap between electrodes and observing mechanical and chemical processes like particle motion and ignition. A limited range of spark conditions and material properties have been tested, which facilitated the development and validation of preliminary computational models describing this system. Significant gaps …

Machine Learning-Based Design Of Doppler Tolerant Radar, Kyle Peter Wensell

Dissertations

In this work, machine learning theory is applied to the design of a radar detector in order to train a machine learning-based detector that is robust against Doppler shifts. The radar system is designed to work with data that would be otherwise intractable to conventional optimal detector design, such as transmitted noise waveforms and the effects of one-bit quantization at the receiver. The detection performance of the one-bit receiver is shown to match the performance of the derived square-law sign correlator detector. The resulting learning-based detector also introduces Doppler tolerance to the system, which allows for the successful detection of …

Information Theoretic Bounds For Capacity And Bayesian Risk, Ian Zieder

Dissertations

In this dissertation, the problem of finding lower error bounds on the minimum mean-squared error (MMSE) and the maximum capacity achieving distribution for a specific channel is addressed. Presented are two parts, a new lower bound on the MMSE and upper and lower bounds on the capacity achieving distribution for a Binomial noise channel. The new lower bound on the MMSE is achieved via use of the Poincare inequality. It is compared to the performance of the well known Ziv-Zakai error bound. The second part considers a binomial noise channel and is concerned with the properties of the capacity-achieving distribution. …

Financial Time Series Fusion, Completion, And Prediction With Deep Neural Networks, Dan Zhou

Dissertations

Time-series analysis is essential for a wide range of financial applications, including but not limited to bond valuation, firm earnings forecasts, firm fundamentals predictions, and firm characteristics imputations. Given its considerable value, the financial community has shown a strong interest in refining and advancing time-series analysis techniques. The study in this dissertation contributes to this field by employing advanced machine learning approaches, specifically graph neural networks, deep neural networks, and matrix/tensor methods. The primary objectives are twofold: first, to reveal complex correlations within financial time series to improve prediction accuracy, and second, to enhance the process of integrating and imputing …

Sensing With Integrity: Responsible Sensor Systems In An Era Of Ai, David Eisenberg

Dissertations

Deep and machine learning now offer immense benefits for consumer choice, decision-making, medicine, mental health and education, smart cities, and intelligent transportation and driver safety. However, as communication and Internet technology further advances, these benefits have the potential to be outweighed by compromises to privacy, personal freedom, consumer trust, and discrimination. While ethical consequences for personal freedom and equity rise from these technological advances, the issue may not be the technology itself but a lack of regulation and policy that allow abuses to occur. A first study examines how emerging sensor-based technologies, limited to only accelerometer and gyroscope data from …

A Molecular Dynamics Study On The Destruction Mechanism Of Per And Polyfluoroalkyl Substances Due To Ultrasound Technology, Bruno Bezerra De Souza

Dissertations

Per- and polyfluoroalkyl substances (PFAS) are a group of stable synthetic chemicals that are highly persistent and harmful pollutants to the environment and human health. PFAS have caused a strong public and regulatory response due to their ubiquitous presence in the environment and toxicity to humans. The application of ultrasound is one of the most effective treatment technologies for the mineralization of PFAS in contaminated water. However, this technology is treated as a black box causing the inability to be optimized. Therefore, there is a pressing need to investigate the intricate dynamics of PFAS degradation under ultrasound to unlock its …

Graph-Based Modeling And Optimization Of Wpt Systems For Evs, Matthew J. Hansen, Greg Droge, Abhilash Kamineni

Electrical and Computer Engineering Student Research

A model of a system of wireless power transfer (WPT) pads is developed, where each WPT pad is modeled as a node and the coupling between pads is modeled as graph edges. This modeling approach is generalized to admit primary, secondary, and booster coils, where power can flow among the pads and a pad can fill multiple roles. An excitation in one pad induces voltage and current in all neighboring pads, causing each pad to act as both a booster coil and either a transmitter or a receiver. Power flow through the entire system can be modeled with the graph …

Shifting The Ice: Analyzing The Impact Of The 2013 Nhl Cba To The Competitive Balance Of The League, Ryan Lacy

Empirical Economic Bulletin, An Undergraduate Journal

This paper investigates whether the 2013 National Hockey League (NHL) Collective Bargaining Agreement (CBA), which hardened the existing salary cap, increased team revenue sharing, and instituted additional restrictions on player contracts, results in a more competitively balanced league. The study incorporates an OLS regression and Quantile regression to examine the impact of the 2013 CBA on the competitive balance of the league. The results show that the changes allow for a dispersion of talent, specifically offensive talent, and demonstrated a positive relationship between spending and points obtained by teams in the top 25% of the league. Conversely, teams that did …

Molecular-To-Continuum Scale Modeling Of Aerosols: Atmospheric Application And Beyond, Ella Ivanova

Dissertations

Aerosol modeling is critical for various applications, such as climate forecasting, air quality, and human health impact assessment. During their lifetime, aerosols undergo a complex evolution, usually divided into several stages — formation, processing, transport, and removal — that occur on different scales. Thus, the choice of modeling methods depends on the stage considered. For example, certain stages of particle formation may require nano-scale modeling while aerosol-cloud interactions span from microscale to mesoscale. This study examines the modeling of aerosol behavior over a wide range of scales, from nano to microscale, with implications to mesoscale.

This dissertation focuses on two …

Microplastic Abundance And Removal In Stormwater Using Green Infrastructure, Meghana Parameswarappa Jayalakshmamma

Dissertations

Microplastics (MPs) are increasingly recognized as a pervasive environmental contaminant, conveying other contaminants, accumulating in aquatic organisms, and posing ecological risks. The existing research has primarily focused on MPs in wastewater treatment plant effluents in surface waters. However, the role of stormwater systems in MP transport has been less explored. Given the rise in MPs from urban sources, stormwater runoff from urban areas may serve as a critical conduit for transporting land-based MPs into aquatic environments. Green infrastructures (GIs) have been recognized for mitigating flooding and improving water quality from minor storms by trapping stormwater pollutants. Yet, the capability of …

A Machine Learning-Assisted Steering And Scheduling Framework For Big-Data Scientific Workflows On Heterogeneous Computing Platforms, Yijie Zhang

Dissertations

In next-generation scientific applications, the exponential growth of big data necessitates advanced techniques for efficient data storage, processing, and analysis. This has led to the construction of intricate computing workflows, managed and orchestrated by powerful engines in big data systems as exemplified by Hadoop. As scientific applications increasingly shift towards simulation-centric approaches, traditional methodologies face new challenges in accommodating the complexity of extreme-scale numerical modeling with numerous tunable parameters. To address these challenges, this dissertation propose to develop a machine learning-assisted framework that enables autonomous computational steering of scientific simulations and optimized execution of big-data workflows on heterogeneous platforms. This …

Development Of Super Hydrophobic Membranes And Their Applications, Sumona Paul

Dissertations

Effective liquid phase separation is vital across industries, especially in aviation, chemicals, fuels, and textiles. Membrane technology offers advantages over traditional methods like distillation, with low energy consumption and protection for heat-sensitive molecules. Membrane performance is assessed based on factors such as materials, surface modification, and interactions. This research targets superhydrophobic membranes for liquid-liquid filtration and antiwetting omniphobic membranes for membrane distillation, focusing on properties like contact angle and thermal resistance.

This study presents a highly hydrophobic membrane achieved by immobilizing carbon nanotubes (CNTs) onto a PTFE microfiltration membrane. It's designed for dewatering organic-water mixtures with trace water content via …

Application Of Secant Span In Medical Diagnosis, R. Narmadhagnanam, A. Edward Samuel

Neutrosophic Systems with Applications

Many common and specific characteristics engrave most diseases. Water-borne diseases differ slightly in their characteristics. Erroneous diagnoses can be attributed to shared characteristics. Current approaches tend to rely on imprecise diagnoses and lack robust techniques for differentiating between characteristics. Every illness also presents with specific symptoms. To assist doctors in approaching a likely diagnosis, the suggested method is successful in determining the connection between a class of sickness and the people with a specific pathology to the indications. Among n-valued interval neutrosophic sets, a secant span is proposed in this paper and a few of its attributes are talked about …