Digital Commons Network^™

Ai-Powered Lawyering: Ai Reasoning Models, Retrieval Augmented Generation, And The Future Of Legal Practice, Daniel Benjamin Schwarcz, Sam Manning, J.J. Prescott, Patrick Barry, David R. Cleveland, Beverly Rich

Articles

Generative AI is set to transform the legal profession, though its most promising uses and ultimate effects are still unclear. While AI models like GPT-4 improve efficiency, they can also “hallucinate” and may undermine legal judgment, particularly in complex tasks typically handled by skilled lawyers. This article examines two emerging AI innovations that may mitigate these concerns: Retrieval Augmented Generation (RAG), which grounds AI-powered analysis in legal sources, and AI reasoning models, which structure complex reasoning before generating output. We conduct the first randomized controlled trial assessing these technologies, assigning upper-level law students to complete legal tasks using a RAG-powered …

Grading Machines: Can Ai Exam-Grading Replace Law Professors?, Kevin L. Cope, Jens Frankenreiter, Scott Hirst, Eric A. Posner, Daniel Schwarcz, Dane Thorley

Articles

In the past few years, large language models (LLMs) have achieved significant technical advances, enabling legal-advocacy organizations to adopt them as complements to—or substitutes for—lawyers and other human experts. The role of LLMs in legal education, however, is underexplored. While several studies have examined LLMs’ performance in taking law school exams, finding mixed results, there have been no published studies systematically analyzing LLMs’ competence at one of law professors’ chief responsibilities: grading law school exams. This paper presents results of an analysis of how LLMs perform in evaluating student responses to legal analysis questions of the kind typically contained in …

Assessing Interdisciplinary Learning And Knowledge: A State-Of-The-Art Review And Heuristic, Kacey Beddoes, Kristi Bartlett

Product Design Faculty Publications

Background – The need for interdisciplinary training is increasingly important, but assessing the effects of interdisciplinary education initiatives remains challenging. One of the leading difficulties is identifying and selecting the best instrument or technique for a given purpose.

Purpose -- To help researchers and educators identify available options and determine the best options for their purposes, we conducted a literature review and created a heuristic table of available techniques. Our review addresses the questions: 1) What domain-general techniques and instruments exist for assessing interdisciplinary learning or knowledge? 2) What research scenarios, populations, and questions are each technique or instrument most …

The Transport Of New Make Spirits Through American White Oak, Taylor E. Scott, Jarrad Gollihue, Michael P. Sama, Michael Shaffer, Brad J. Berron

Biosystems and Agricultural Engineering Faculty Publications

Why was the work done: The reduction of maturation loss is a significant opportunity for increased revenue in aged spirits and varies through several factors. This work aims to better understand maturation loss by isolating and measuring spirit flow through wood.

How was the work done: Bourbon stave disks were fabricated by computer numeric control milling and loaded into a sealed module consisting of flanges holding the stave disk over a liquid filled pipe. The modules were filled with new make spirit at 50, 62.5 or 70% ABV, with either liquid or vapour contact with the stave disk. Further, the …

Modeling Determinants Of Significant Noncompliance In The U.S. Mining Sector: A Fixed Effects Logistic Regression Approach, Eli Johnson

Dissertations, Master's Theses and Master's Reports

This study examines environmental compliance behavior among mining facilities regulated under the U.S. Clean Water Act (CWA). Using a national quarterly panel of National Pollutant Discharge Elimination System (NPDES)-permitted mining facilities, the analysis evaluates whether local socioeconomic and demographic indicators are associated with the likelihood that a facility enters significant noncompliance (SNC) status. Facility compliance histories are compiled from the U.S. Environmental Protection Agency’s Enforcement and Compliance History Online (ECHO) database and is merged with county- and state-level socioeconomic indicators and election data. A fixed-effects logistic regression model is used to account for time-invariant facility heterogeneity. The results suggest that …

Expanding The Good Samaritan Program: Cleaning Up The Colorado River, One Mine At A Time, Jordan Carlson

Wyoming Law Review

The headwaters of the Colorado River Basin supply nearly 90% of the river’s flow and are among the most hydrologically sensitive areas in the U.S. During the nineteenth and early twentieth centuries, westward expansion and the allure of gold and other valuable minerals drove thousands of miners into the basin. When the mining boom ended, the mines were left behind. Today, thousands of abandoned hardrock mine sites continue to leach acidity and heavy metals into streams, leaving a lasting impact on water quality. For decades, strict environmental liability laws made cleanup nearly impossible, creating a chilling effect that discouraged even …

Full Issue, Wyoming Law Review Editorial Board

Wyoming Law Review

No abstract provided.

Adaptive Control For A Robotic Bipedal Device Using A Hybrid Discrete-Continuous Reinforcement Learning Strategy, Karla Rincon-Martinez, Wen Yu, Isaac Chairez

Mathematics Faculty Publications

This research develops and implements a novel reinforcement learning (RL) architecture to address the trajectory-tracking problem in bipedal robotic systems under articulated-joint constraints. The proposed RL framework extends previously designed adaptive controllers characterized by state-dependent gain structures. The learning mechanism comprises two hierarchical adaptation layers: the first employs an adaptive dynamic programming (ADP) formulation to approximate the Bellman value function using a class of continuous-time dynamic neural networks. In contrast, the second uses an iterative optimization scheme based on the deep deterministic policy gradient (DDPG) algorithm. The resulting control strategy minimizes a robust performance index defined over the tracking trajectories …

The Fiction Of Separation: Racial Gerrymandering Disguised As Partisan Redistricting, Crystal Barnes-Bullock

University of the District of Columbia Law Review

While constitutional doctrine formally distinguishes between racial and partisan gerrymandering, this distinction has become increasingly untenable in the modern electoral landscape. In many jurisdictions, particularly in the South, race and political affiliation are deeply intertwined. As a result, what courts treat as “partisan” redistricting often operates as de facto racial gerrymandering, shielding racially discriminatory practices from judicial review. The legal separation of race and party not only reflects a formalist fiction but also undermines the protections the Equal Protection Clause and the Voting Rights Act were designed to provide. The current legal framework that distinguishes racial gerrymandering from partisan gerrymandering …

Silos, Gaps, And Bridges: A Call To Action For Law Schools To Facilitate Collaboration Across The Curriculum At The Dawn Of The Nextgen Bar, Elizabeth Usman, Andrea Gemignani

University of the District of Columbia Law Review

Now is a time for action. With the advent of the NextGen bar exam and the recent changes to the ABA accreditation standards for law schools, which both focus on valuing practical legal skills, law schools have a unique opportunity. By coordinating practical and doctrinal content across the curriculum, law schools can ensure that all graduates are proficient in fundamental lawyering skills and prepared for both the bar exam and practice success. ...

Part I of this article examines the foundations of American legal education from apprenticeships to the emergence of the case study method. It then explores the calls …

Navigating Racist Spaces Through Radical Self-Care: A Photovoice Exploration Of The Experiences Of Black Graduate Students, Laetitia Adelson, Cherese Fine, Dion Harry, Keneisha Harrington, Rebecca Lynn Morgan Ph.D., Tomiko Smalls, Jerad Green, Courtney Allen, Anuoluwapo Bankole, Robin Phelps-Ward

Faculty Publications

This manuscript examines the impact of racist campus climates for Black graduate students at a predominantly white institution. Using a photovoice methodological design, this study illuminates students’ ability to thrive through radical self-care despite the many racist factors, incidents, and systems at the institution. The paper ends with recommendations for improving campus racial climate in graduate education.

What The Wild West Can Teach Us About Space Exploration, Kody George

Journal of Air Law and Commerce

Currently, the laws governing property in outer space are inadequate and underdeveloped, yet space exploration by private entities is rapidly growing. In this legal vacuum, private companies’ actions heavily influence, and in some cases, provide the basis for, legal precedent. The policies that for-profit corporations prefer are different from those that most government actors will prefer and are much different from those that support the common heritage of mankind doctrine. Rewarding entrepreneurship, innovation, and investments by governments, while balancing the interest all mankind has in outer space is why this Article proposes a tiered, patent land system that would grant …

When Planes Fall And People Die: An International And Domestic Overview Of Disaster In The Sky, Clayton Rainey

Journal of Air Law and Commerce

Commercial aviation disasters expose catastrophic breakdowns in engineering, regulatory oversight, corporate governance, and human systems. From the Boeing 737 MAX tragedies involving Lion Air Flight 610 and Ethiopian Airlines Flight 302 to the recent domestic crash of American Airlines Flight 5342, modern aviation disasters have become defining legal events that test the boundaries of product liability, federal preemption, sovereign immunity, and transnational treaty law. This Article examines how aviation mass-casualty events evolve into complex litigation involving aircraft manufacturers, airlines, regulatory agencies, and governmental entities, and how those legal frameworks differ in international versus domestic contexts.

Beyond legal doctrine, this Article …

Analytical And Semi-Analytical Modeling Of Solar Cells Using The Lambert W Function: A Comprehensive Review Of Equivalent Circuits, Adel El-Shahat, Martin Ćalasan, Snežana Vujoševic, Shady H. E. Abdel Aleem

Engineering Technology Faculty Publications

The modeling of photovoltaic (PV) cells through equivalent circuits forms a central element in the analysis, simulation, and optimization of solar energy systems. Traditional approaches often depend on iterative numerical methods to solve the implicit current–voltage (I–V) equations. In contrast, the Lambert W function has emerged as an effective mathematical tool that enables closed-form or semi-analytical expressions for a wide range of PV models. This paper presents a Lambert W-centered review of analytical and semi-analytical formulations for PV equivalent-circuit models, covering classical single-diode and multi-diode structures and modern variants incorporating additional elements, voltage-dependent parameters, and topology rearrangements. The models are …

Interpretable Machine Learning For Bridge-Pier Scour Prediction And Flood Resilience, Adil Khan, Dalya Ismael

Engineering Technology Faculty Publications

Bridge-pier scour is a leading cause of flood-induced bridge failure, yet practice still lacks transparent, physics-informed tools that link data-driven prediction with design guidance. This study develops an interpretable, physics-aware machine-learning framework to predict equilibrium scour depth and translate those predictions into actionable strategies for flood-resilient infrastructure. Using the 2014 U.S. Geological Survey Pier-Scour Database (569 laboratory cases), five models: Gradient Boosting, AdaBoost (Tree), XGBoost, Gaussian Process (RBF kernel), and Kernel Ridge (polynomial), were trained and evaluated with K-fold cross-validation. Model performance was evaluated using R², RMSE, and MAE. Gradient Boosting performed best, achieving training and testing R² of 0.99 …

Srgan-Based Deep Learning Framework For Wind Turbine Damage Detection From Sentinel-2 Imagery, Kübra Çakir, Onur Elma, Murat Kuzlu

Engineering Technology Faculty Publications

The operational reliability of wind turbines is critical for sustainable energy production in smart grids. This study proposes a remote monitoring approach using perceptually enhanced satellite imagery. Sentinel-2 multispectral data (10 m resolution) has been processed with a Super-Resolution Generative Adversarial Network (SRGAN) to improve visual quality to a perceptual resolution of 30 cm. Although true spatial refinement is not achieved, the sharper structural details enhance classification accuracy. The data set comprises 15,000 images—10,000 SRGAN-enhanced and 5000 augmented through rotation, zoom in, increasing brightness, noise addition, and blurring. A custom Convolutional Neural Network (CNN) has been trained to classify turbines …

Generative Ai And Llm Applications In Renewable Energy And Smart Grids: A Systematic Review For The Sustainable Energy Transition, Umit Cali, Ugur Halden, Merlinda Andoni, Ferhat Ozgur Catak, Si Chen, Benoit Couraud, Emre Kantar, Samuel Knapper, Ibrahim Kucukdemiral, Huseyin Kusetogullari, Murat Kuzlu, Yashar Mousavi, Sonam Norbu, Taha Selim Ustun, David Flynn

Engineering Technology Faculty Publications

The global energy transition toward decarbonization and digitalization requires advanced methods to manage decentralized, data-intensive cyber-physical energy systems. This systematic review analyzes 106 research studies on Generative Artificial Intelligence (GenAI) and Large Language Models (LLMs) in renewable energy and smart grids, organized into seven application clusters covering forecasting, system design, operation, reliability, data and cybersecurity, and energy markets. The review situates these applications within a Cyber-Physical-Social Systems (CPSS) framework. Results show that GANs dominate current applications (47.2%), followed by LLMs (10.4%) and VAEs (9.4%), with growing adoption of diffusion and score-based models (7.5% each). Selected studies report improved probabilistic forecasting …

A Large Language Model-Based Academic Advising Assistant For Engineering Technology Students, Murat Kuzlu, Vukica M. Jovanovic, Katherine Smith, Otilia Popescu, Adel El-Shahat, Ryan Cotton, Kayla Marie Seegers, William Austin Henderson

Engineering Technology Faculty Publications

In recent years, Artificial Intelligence (AI)-based solutions, particularly Large Language Models (LLMs), have been applied to a variety of domains, such as energy, finance, transportation, healthcare, and education. Among these domains, education has become increasingly popular due to strong interest among educators and students. This study proposes an academic advising assistant system that uses LLMs to help Engineering Technology (ET) students plan their course load based on their educational history, departmental course offerings, and personal constraints, such as their preferred semester course load. The proposed LLM-based academic advising assistant system maintains a database of students' course histories and upcoming course …

Explainable Ai-Driven Predictive Maintenance Curriculum For Smart Manufacturing, Abdullah Al Mamun, Murat Kuzlu, Katherine Smith, Vukica Jovanovic, Dalya Ismael, Adel El-Shahat, Angela Sicaja, Md. Hedayetul Islam Chy

Engineering Technology Faculty Publications

Nowadays, Industry 4.0 has transformed manufacturing industries into a data-rich system driven by IoT, automation, and Artificial Intelligence (AI). Within this context, Predictive Maintenance (PdM) provides a proactive strategy that leverages heterogeneous sensor data such as vibration, acoustic, electrical, and visual signals along with historical performance and advanced analytics to forecast equipment failures before they occur. Usually, AI-driven PdM (AI-PdM) enhances this capability by integrating AI-based sensor analytics to automate fault prediction and optimize system reliability. However, traditional AI-PdM often functions as a “black box,” providing limited interpretability of its decision-making process and posing challenges for trust, validation, and human …

Wip: Arduino-Based Pbl To Foster Entrepreneurial Mindset, Nathan Q. Holland, Vukica M. Jovanovic

Engineering Technology Faculty Publications

This work-in-progress paper examines a semester-long project-based learning initiative begun in an introductory engineering course during the Fall 2025 semester. The project aims to enhance students' hands-on experience by integrating information literacy, the engineering design process (EDP), and an entrepreneurial mindset (EM) [1]. The objective is to boost student confidence in teamwork, technical problem-solving, and application of skills, preparing them for future courses in their discipline. Students in this introduction to engineering course received an Arduino Uno R3 Controller board kit and additional sensors. They were tasked to develop a device addressing engineering in the medicine challenge of their choosing. …

Improving Medical Diagnostics With Vision-Language Models: Convex Hull-Based Uncertainty Analysis, Ferhat Ozgur Catak, Murat Kuzlu, Taylor Patrick, Michel Audette

Engineering Technology Faculty Publications

In recent years, vision-language models (VLMs) have been applied to various fields, including healthcare, education, finance, and manufacturing, with remarkable performance. However, concerns remain regarding VLMs' consistency and uncertainty, particularly in critical applications such as healthcare, which demand a high level of trust and reliability. This paper proposes a novel approach to evaluate uncertainty in VLMs' responses using a convex hull approach on a healthcare application for visual question answering (VQA). For any VLM, temperature refers to a sampling parameter used in probabilistic generation, which controls the randomness of the model's output. The LLM-CXR model is selected as the medical …

Mapping The Use And Psychometric Characteristics Of The Objective Structured Clinical Examination (Osce) In Musculoskeletal Physical Therapy Education: A Systematic Review, Luis Gómez Miranda, Tomás Reyes Amigo, Hernán Andrés De La Barra Ortiz

Health Professions Education

Purpose. Musculoskeletal disorders are a major cause of disability, underscoring the need for clearly defined and assessable competencies in physical therapy education. Although OSCEs are increasingly used in physical therapy programs, evidence regarding their design and psychometric properties is not yet fully characterized within musculoskeletal physical therapy education. This systematic review aimed to describe how OSCEs have been applied to assess musculoskeletal competencies in physical therapy education, summarize their structural characteristics and reported psychometric properties, and identify methodological gaps.

Method. A systematic review was performed according to PRISMA guidelines. Electronic searches were conducted in PubMed, Scopus, Web of Science, EBSCOhost, …

Reimagining Patient Interviews: The Effect Of Ai-Generated Chatbots On Dpt Student Engagement - A Case Report, Leslie M. Smith, Samantha Hsu, Peter F. Bodary

Health Professions Education

Background and Purpose: Artificial intelligence generated chatbots (AIGC) present new possibilities for physical therapist education, especially for self-directed learning and skill development. Their impact on Doctor of Physical Therapy (DPT) students’ communication and interviewing skills is still underexplored. This case report evaluates DPT students’ experiences and perceptions of AIGC in a case-based classroom activity. Case Description: Participants were first-year entry-level DPT students (n=64) enrolled in a 9-week critical thinking course. They practiced history taking and interview skills with seven patient cases using AIGC and completed a post-activity survey (n=59).

Outcomes: A total of 93.2% found AIGC relevant for learning patient …

Raw Dataset For 300 University Ai Choices, Amanda Potasznik

Data and Datasets

A log of 300 universities, randomly sampled from IPEDS data, and documentation of their adoption (or not) of Generative AI technology, coded by company.

Framings Of Intercultural Competence In Australian Teacher Education: Conceptual Bases And Implications, James F. Toohey, Michael D. Carey, Peter R. Grainger

Australian Journal of Teacher Education

Developing an interculturally competent teaching workforce remains an ongoing priority in Australia, yet preparation practices vary in their conceptual grounding. This theoretical paper examines four broad paradigmatic framings that inform strategies to develop intercultural competence in preservice teachers: cognitive, dispositional, critical, and linguistic. We analyse how each paradigm foregrounds particular assumptions about culture, communication, and development, and consider the implications of their partial application in teacher education. Rather than positioning these paradigms as competing models, the paper argues that they function as complementary lenses through which intercultural preparation can be understood and refined. Particular attention is given to the linguistic …

The Effect Of Stem Learning Experiences On Stem Semantic Awareness And 21st-Century Learner Skills Of Prospective Primary School Teachers, Ahmet Oğuz Akçay, Mehmet Arif Bozan, Engin Karahan

Australian Journal of Teacher Education

STEM awareness and 21^st-century skills are recognized as two interrelated dimensions critical for the modern pedagogical competencies of pre-service teachers. This study examines how STEM learning experiences affect pre-service primary school teachers’ STEM semantic awareness and 21^st-century learner skills. STEM activities were implemented for six weeks with pre-service primary school teachers. The research was designed using a convergent mixed-methods approach. The study included 21 prospective primary school teachers who volunteered to participate. The “STEM Semantic Awareness Scale,” “21^st-Century Learner Skills Use Scale,” participant journals, and semi-structured interviews were used as data collection tools. The …

An Examination Of The Cognitive Levels And Content Dimensions In Activities Developed By Pre-Service Mathematics Teachers Within The Math Taxonomy Framework, Ayşe Tuğçe Bodur, Mevhibe Kobak Demi̇r

Australian Journal of Teacher Education

The purpose of this study is to analyze the questions included in three-dimensional modeling activities developed by pre-service mathematics teachers in terms of the cognitive levels and mathematical content dimensions of the MATH taxonomy. This analysis aims to reveal which mathematical processes and skills the pre-service teachers prioritize in their instructional materials. Adopting a case study design, one of the qualitative research methods, this research examined activities developed by 26 secondary pre-service mathematics teachers, selected through convenience sampling, for teaching three-dimensional geometric shapes. Descriptive analysis was used to evaluate a total of 122 activity questions. Regarding content dimensions, it …

Collaborative Problem-Solving (Cps) In Supporting Critical Thinking Skills: A Case Study On Quadratic Function Material, Buaddin Hasan, Arif Hidayatul Khusna

Australian Journal of Teacher Education

Theoretically, CPS can support students' critical thinking skills. However, more in-depth research is needed on how CPS can support students' critical thinking skills. This research aims to describe CPS in supporting students' critical thinking skills. Participants in this research were 24 10th-grade students consisting of 14 female students and ten male students. The 24 participants were then formed into 12 groups, with one group of two students. Data was collected by asking groups to solve a quadratic function problem. The research results show that CPS can support students' critical thinking skills because it provides opportunities for students to negotiate with …

Town Of Tilton 2025 Annual Report, Tilton Town Representatives

Tilton, NH Annual Reports

This is an annual report containing vital statistics for a town/city in the state of New Hampshire.

Town Of Hopkinton Annual Reports - 2025, Hopkinton Town Representatives

Hopkinton, NH Annual Reports

This is an annual report containing vital statistics for a town/city in the state of New Hampshire.