Digital Commons Network^™

"I Don't Think Librarians Can Save Us": The Material Conditions Of Information Literacy Instruction In The Misinformation Age, Amber Willenborg, Robert Detmering

Faculty Scholarship

This national qualitative study investigates academic librarians’ instructional experiences, views, and challenges regarding the widespread problem of misinformation. Findings from phenomenological interviews reveal a tension between librarians’ professional, moral, and civic obligation to address misinformation and the actual material conditions of information literacy instruction, which influence and often constrain librarians’ pedagogical and institutional roles. The authors call for greater professional reflection on current information literacy models that focus on achieving ambitious educational goals but which may be unsuitable for addressing the larger social and political crisis of misinformation.

Shame On Me: Emotions And Gender Differences In Taking With Earned Endowments [Post-Print], Brianna Halladay

Faculty Scholarship

We study gender differences in a taking-framed dictator game. We expand on past studies documenting gender differences in the taking-framed dictator game by asking whether gender differences persist when endowments are earned. We find a strong and robust gender effect. Women take less than men both in terms of overall amounts and share taken. We further elicit emotions following the taking game. Shame is positively correlated with taking behavior; this could be a contributing factor to taking aversion documented in the literature. Interestingly we do not observe gender differences in reported emotions or emotional intensity by either dictators or receivers.

Differences In Perceived Energy And Macronutrient Requirements Across Divisions In Ncaa Athletes, K. Michelle Singleton, Andrew Jagim, Jamie Mcallister-Deitrick, Marcos Daou, Chad M. Kerksick

Faculty Scholarship

Background

Sports nutrition is an impactful component to sports performance. The purpose of the current study was to investigate the sports nutrition knowledge of National Collegiate Athletic Association collegiate athletes and assess self-reported perceived requirements for energy and macronutrient intake. A secondary aim was to evaluate the awareness of physical and emotional perceptions associated with mindful eating.

Methods

Participants included NCAA Division I (DI, n = 45), II (DII, n = 31), and III (DIII, n = 47) athletes. Athletes completed a validated questionnaire designed to assess sports nutrition knowledge and were asked questions about their perceived dietary energy and …

Architectural Elements Contributing To Interpretability Of Deep Neural Networks (Dnns), Emily Barnes, James Hutson

Faculty Scholarship

The interpretability of Deep Neural Networks (DNNs) has become a critical focus in artificial intelligence and machine learning, particularly as DNNs are increasingly used in high-stakes applications like healthcare, finance, and autonomous driving. Interpretability refers to the extent to which humans can understand the reasons behind a model's decisions, which is essential for trust, accountability, and transparency. However, the complexity and depth of DNN architectures often compromise interpretability as these models function as "black boxes." This article reviews key architectural elements of DNNs that affect their interpretability, aiming to guide the design of more transparent and trustworthy models. The primary …

Perceptions And Aspirations Of Undergraduate Computer Science Students Towards Generative Ai: A Qualitative Inquiry, James Hutson, Theresa Jeevanjee

Faculty Scholarship

This article presents a comprehensive study conducted during the spring semester of 2024, aimed at exploring undergraduate computer science students’ perceptions, awareness, and understanding of generative artificial intelligence (GAI) tools within the context of their Artificial Intelligence (AI) courses. The research methodology employed qualitative techniques, including human-subject research and focus groups, to delve into students’ insights on the evolution of AI as delineated in the seminal textbook by Russell and Norvig. The study-initiated discussions on the historical development of AI, prompting students to reflect on the aspects that intrigued them the most, and to identify which historical concepts and methodologies, …

The Sources And Consequences Of Disputes Over Contractual Meaning, Randy D. Gordon

Faculty Scholarship

With some frequency, parties agree to the particular words used in a contract they sign, only to later disagree as to the meaning of those words and their legal effect. That is, they each assent to something, but that “something” is something different for each of them. In this Article, I first categorize and trace the sources of recurring points of disagreement as a matter of language and linguistics. Then, I look at the consequences of a dispute that leads a fact finder to conclude that the parties genuinely did not agree to the same thing, which is to say …

Present Case Studies Highlighting Practical Implications Of Architectural Design Choices, Emily Barnes, James Hutson

Faculty Scholarship

The interpretability of deep neural networks (DNNs) has become a crucial focus within artificial intelligence and machine learning, particularly as these models are increasingly used in high-stakes applications such as healthcare, finance, and autonomous driving. This article explores the impact of architectural design choices on the interpretability of DNNs, emphasizing the importance of transparency, trust, and accountability in AI systems. By presenting case studies and experimental results, the article highlights how different architectural elements—such as layer types, network depth, connectivity patterns, and attention mechanisms—affect model interpretability and performance. The discussion is structured into three main sections: real-world applications, architectural trade-offs, …

Evaluating Methods For Assessing Interpretability Of Deep Neural Networks (Dnns), Emily Barnes, James Hutson

Faculty Scholarship

The interpretability of deep neural networks (DNNs) is a critical focus in artificial intelligence (AI) and machine learning (ML), particularly as these models are increasingly deployed in high-stakes applications such as healthcare, finance, and autonomous systems. In the context of these technologies, interpretability refers to the extent to which a human can understand the cause of a decision made by a model. This article evaluates various methods for assessing the interpretability of DNNs, recognizing the significant challenges posed by their complex and opaque nature. The review encompasses both quantitative metrics and qualitative evaluations, aiming to identify effective strategies that enhance …

The Effects Of A Brand-Specific, Hemp-Derived Cannabidiol Product On Physiological, Biochemical, And Psychometric Outcomes In Healthy Adults: A Double-Blind, Randomized Clinical Trial, Gianna F. Mastrofini, Bridget A. Mcfadden, Alexa J. Chandler, Blaine S. Lints, Harry P. Cintineo, Nathaniel D. Rhoades, Caroline S. Vincenty, Sten O. Stray-Gundersen, Abbi D. Lane, Shawn M. Arent

Faculty Scholarship

Background

Cannabidiol (CBD) is a non-psychoactive phyto-cannabinoid derived from the Cannabis sativa plant. CBD exhibits various interactions at receptor sites, prompting the research of its potential anti-inflammatory, immunomodulatory, psychological, and pain-relieving effects. This study aimed to investigate the physiological, biochemical, and psychometric effects of a brand-specific, hemp-derived CBD product in healthy adults over a 12-week observation period.

Methods

54 healthy males and females (age = 25 ± 7y; BMI = 24.82 ± 3.25 kg/m2) recruited from a large Southeastern University completed the study. Participants arrived at the laboratory after > 8 h of fasting, and > 48 h without alcohol consumption and …

Louisville’S Economic Opportunity Zones: A Rerun Of The Old Louisville Enterprise Zone Program?, Thomas E. Lambert

Faculty Scholarship

In 2017 the US Congress passes and President Donald J. Trump signs the 2017 Tax Cuts and Jobs Act. Part of the legislation allows states to create economic opportunity zones (EOZs), census tracts which will be targeted for business investment and economic development through federal tax incentives. In Louisville, Kentucky, as in other jurisdictions throughout the US over the last several decades, special district “zones” have been used by local, state, and/or the federal government(s) to try to revive low-income, deteriorated, and blighted areas. These have been typically urban areas but sometimes have included semi-rural and rural areas. Whether named …

Navigating The Complexities Of Ai: The Critical Role Of Interpretability And Explainability In Ensuring Transparency And Trust, Emily Barnes, James Hutson

Faculty Scholarship

The interpretability and explainability of deep neural networks (DNNs) are paramount in artificial intelligence (AI), especially when applied to high-stakes fields such as healthcare, finance, and autonomous driving. The need for this study arises from the growing integration of AI into critical areas where transparency, trust, and ethical decision-making are essential. This paper explores the impact of architectural design choices on DNN interpretability, focusing on how different architectural elements like layer types, network depth, connectivity patterns, and attention mechanisms affect model transparency. Methodologically, the study employs a comprehensive review of case studies and experimental results to analyze the balance between …

Navigating The Ethical Terrain Of Ai In Higher Education: Strategies For Mitigating Bias And Promoting Fairness, Emily Barnes, James Hutson

Faculty Scholarship

Artificial intelligence (AI) and machine learning (ML) are transforming higher education by enhancing personalized learning and academic support, yet they pose significant ethical challenges, particularly in terms of inherent biases. This review critically examines the integration of AI in higher education, underscoring the dual aspects of its potential to innovate educational paradigms and the essential need to address ethical implications to avoid perpetuating existing inequalities. The researchers employed a methodological approach that analyzed case studies and literature as primary data collection methods, focusing on strategies to mitigate biases through technical solutions, diverse datasets, and strict adherence to ethical guidelines. Their …

Patterns Of Prospective Memory Errors Differ In Persons With Multiple Sclerosis., Caitlyn A Nguyen, Sarah A Raskin, Aaron P Turner, Zaenab Dhari, Lindsay O Neto, Elizabeth S Gromisch

Faculty Scholarship

INTRODUCTION: Prospective memory (PM) deficits have been documented in multiple sclerosis (MS). This study aimed to explore the specific types of errors made by persons with MS (PwMS), including differences between PwMS and healthy controls (HC) and PwMS who do and do not have impairments in processing speed and/or verbal learning and memory.

METHOD: PwMS (

RESULTS: Nearly 93% of PwMS made at least one PM error, compared to 76% of HC (

CONCLUSIONS: PM errors are common in PwMS, particularly when there are longer delays and time-based cues. Not only do PwMS make more errors than demographically similar HC, …

A Dose-Response Study To Examine Paraxanthine's Impact On Energy Expenditure, Hunger, Appetite, And Lipolysis, Kristen N. Gross, Leah E. Allen, Anthony M. Hagele, Joesi M. Krieger, Paige J. Sutton, Esther Duncan, Petey W. Mumford, Ralf Jäger, Martin Purpura, Chad M. Kerksick

Faculty Scholarship

This study investigated if paraxanthine (PX) impacts energy expenditure, lipolysis and perceptual responses. In a randomized, double-blind, placebo-controlled, crossover fashion, 21 adults (13 M, 8 F; 26.0 ± 6.4 years, 174.9 ± 11.5 cm, 81.0 ± 15.7 kg body mass, 26.3 ± 3.4 kg/m2) consumed a placebo (PLA), 100 mg (PX100), 200 mg (PX200), and 300 mg of PX (PX300, enfinity®, Ingenious Ingredients, L.P. Lewisville, TX, USA). Venous blood was collected 0, 30, 60, 90, 120 and 180 min (min) after ingestion and analyzed for glycerol and free fatty acids. Resting hemodynamics, metabolic rate and perceptual indicators of hunger, appetite …

Simulacra And Historical Fidelity In Digital Recreation Of Lost Cultural Heritage: Reconstituting Period Materialities For The Period Eye, Trent Olsen, James Hutson, Charles O'Brien, Jeremiah Ratican

Faculty Scholarship

The advancement of digital technologies in art history has opened avenues for reconstructing lost or damaged cultural heritage, a need highlighted by the deteriorated state of many artworks from the 1785 Salon. Grounded in the concept of the “Period Eye” by art historian Michael Baxandall, which emphasizes understanding artworks within their original historical and cultural contexts, this study proposes a subfield focused on Reconstituting Period Materialities for the Period Eye. This methodology bridges comprehensive historical research with generative visual artificial intelligence (AI) technologies, facilitating the creation and immersive virtual reality viewing of artworks. Beyond mere visual replication, the approach aims …

Advancing Sentiment Analysis Through Emotionally-Agnostic Text Mining In Large Language Models (Llms), Jay Ratican, James Hutson

Faculty Scholarship

The conventional methodology for sentiment analysis within large language models (LLMs) has predominantly drawn upon human emotional frameworks, incorporating physiological cues that are inherently absent in text-only communication. This research proposes a paradigm shift towards an emotionallyagnostic approach to sentiment analysis in LLMs, which concentrates on purely textual expressions of sentiment, circumventing the confounding effects of human physiological responses. The aim is to refine sentiment analysis algorithms to discern and generate emotionally congruent responses strictly from text-based cues. This study presents a comprehensive framework for an emotionally-agnostic sentiment analysis model that systematically excludes physiological indicators whilst maintaining the analytical depth …

Resonant Perceptions: Exploring Autistic Aesthetics Through Embodied Cognition, James Hutson, Piper Hutson

Faculty Scholarship

No abstract provided.

The Role Of Student Motivation In Integrating Ai Into Web Design Education: A Longitudinal Study, Jason Lively, James Hutson

Faculty Scholarship

Amidst the current wave studies of artificial intelligence (AI) in education, this longitudinal case study, spanning Spring 2023 to Spring 2024, delves into the integration of AI in the UI/UX web design classroom. By introducing both text-based and image-based AI tools to students with varying levels of skill in introductory web design and user experience (UX) courses, the study observed a significant enhancement in student creative capabilities and project outcomes. The utilization of text-based generators markedly improved writing efficiency and coding, while image-based tools facilitated better ideation and color selection. These findings underscore the potential to augment traditional educational methods, …

Optimizing Adult Learner Success: Applying Random Forest Classifier In Higher Education Predictive Analytics, Emily Barnes, James Hutson, Karriem Perry

Faculty Scholarship

This study examines the application of the Random Forest Classifier (RF) model in predicting academic success among adult learners in higher education. It focuses on evaluating the model's effectiveness using key statistical measures like accuracy, precision, recall, and F1 score across a comprehensive dataset from 2013–14 to 2021–22, which includes variables such as age, ethnicity, gender, Pell Grant eligibility, and academic performance metrics. The research highlights the RF model's capability to handle large datasets with varying data types and demonstrates its superiority over traditional regression models in predictive accuracy. Through an iterative process, the study refines the RF model to …

Ethical Imperatives And Challenges: Review Of The Use Of Machine Learning For Predictive Analytics In Higher Education, Emily Barnes, James Hutson, Karriem Perry

Faculty Scholarship

The escalating integration of machine learning (ML) in higher education necessitates a critical examination of its ethical implications. This article conducts a comprehensive review of the application of ML for predictive analytics within higher education institutions (HEIs), emphasizing the technology's potential to enhance student outcomes and operational efficiency. The study identifies significant ethical concerns, such as data privacy, informed consent, transparency, and accountability, that arise from the use of ML. Through a detailed analysis of current practices, this review underscores the need for HEIs to develop robust ethical frameworks and technological infrastructures to navigate these challenges effectively. The findings reveal …

The Perennial Eclipse: Race, Immigration, And How Latinx Count In American Politics, Rachel F. Moran

Faculty Scholarship

In 2016, the U.S. Supreme Court decided Evenwel v. Abbott, a case challenging the use of total population in state legislative apportionment as a violation of the Equal Protection Clause. The plaintiffs sued Texas, alleging that the State impermissibly diluted their voting power because they lived in areas with a high proportion of voting-age citizens. When total population was used to draw district lines, the plaintiffs had to compete with more voters to get their desired electoral outcomes than was true for voters in districts with low proportions of voting-age citizens. The Court rejected the argument, finding that states enjoy …

Persistent Identifiers And The Next Generation Of Legal Scholarship, Aaron Retteen, Malikah Hall-Retteen

Faculty Scholarship

This article discusses the importance of the most common persistent identifiers in scholarly communications—the digital object identifier and the ORCID identifier—to legal scholarship. Persistent identifiers help preserve and disseminate academic content and data-driven services that leverage this information standard are now integrated into the publication process. Because legal publishers have not widely adopted persistent identifiers, the legal discipline cannot enjoy the benefits offered by this system. This article looks at barriers to implementing persistent identifiers among legal publishers and provides an anecdotal example of creating a sustainable workflow between the law library and student-run law journals.

The Submerged Administrative State, Gabriel Scheffler, Daniel E. Walters

Faculty Scholarship

The United States government is experiencing a reputation crisis: after decades of declining public trust, many Americans have lost confidence in the government’s capacity to perform its basic functions. While various explanations have been offered for this worrying trend, these existing accounts overlook a key factor: people are unfamiliar with the institutions that actually do most of the governing—administrative agencies—and they devalue what they cannot easily observe. The “submerged” nature of the administrative state is, we argue, a central reason for declining trust in government.

This Article shows that the administrative state is systematically submerged in two ways. First, administrative …

The Efficacy Of High-Fidelity Simulation On Knowledge And Performance In Undergraduate Nursing Students: An Umbrella Review Of Systematic Reviews And Meta-Analysis, Celeste Marie Alfes

Faculty Scholarship

Objectives: This umbrella review aimed to consolidate the evidence base on the impact of high-fidelity simulation on knowledge and performance among undergraduate nursing students. Design: Umbrella review with meta-analyses of pooled effect sizes, followed by an additional meta-analysis of primary studies from the included systematic reviews, excluding overlapping results. Data sources: Systematic searches were performed up to August 2023 in PubMed, Embase, and Cochrane Library. We included reviews that compared high-fidelity simulation against other learning strategies. Review methods: The risk of bias was assessed for each included systematic review (ROBIS tool) and primary study (RoB 2 or ROBINS-I as appropriate). …

Bridging The Digital Divide: Innovative Uses Of Qr Codes And Nfc In The Artistic Realm, Piper Hutson, James Hutson

Faculty Scholarship

In the rapidly evolving digital age, artists and creatives are increasingly leveraging QR codes and Near Field Communication (NFC) technologies to redefine the boundaries between the physical and digital worlds. This article explores the diverse and inventive applications of QR codes and NFC in art installations, augmented reality experiences, interactive storytelling, performance art, and marketing campaigns. By incorporating these technologies, artists may create interactive, immersive, and personalized experiences which engage audiences in novel ways. Additionally, the article delves into the technological advancements enabling these innovative applications, including location-based personalization, machine learning, augmented reality, and the seamless interactions facilitated by NFC …

Develop An Interactive Python Dashboard For Analyzing Ezproxy Logs, Andy Huff, Matthew Roth, Weiling Liu

Faculty Scholarship

This paper describes the development of an interactive dashboard in Python with EZproxy log data. Hopefully, this dashboard will help improve the evidence-based decision-making process in electronic resources management and explore the impact of library use.

Common Questions And Misconceptions About Protein Supplementation: What Does The Scientific Evidence Really Show?, Jose Antonio, Cassandra Evans, Arny A. Ferrando, Jeffrey R. Stout, Brandi Antonio, Harry P. Cintineo, Patrick Harty, Shwn M. Arent, Darren G. Candow, Scott C. Forbes, Chad M. Kerksick, Flavia Pereira, Drew Gonzalez, Richard B. Kreider

Faculty Scholarship

Protein supplementation often refers to increasing the intake of this particular macronutrient through dietary supplements in the form of powders, ready-to-drink shakes, and bars. The primary purpose of protein supplementation is to augment dietary protein intake, aiding individuals in meeting their protein requirements, especially when it may be challenging to do so through regular food (i.e. chicken, beef, fish, pork, etc.) sources alone. A large body of evidence shows that protein has an important role in exercising and sedentary individuals. A PubMed search of “protein and exercise performance” reveals thousands of publications. Despite the considerable volume of evidence, it is …

Teaching "Is This Case Rightly Decided?", Steven Arrigg Koh

Faculty Scholarship

“Is this case rightly decided?” From the first week of law school, every law student must grapple with this classroom question. This Essay argues that this vital question is problematically under-specified, creating imprecision in thinking about law. This Essay thus advocates that law professors should present students with a three-part framework: whether a case is rightly decided legally, morally, or sociologically.

Additionally, this Essay argues that disaggregating the question exposes deeper deficiencies in legal education. Many law professors do not provide students with serious grounding to engage in rigorous thinking about the relationship between law, morality, and justice, not to …

Parenting And The Academic Library: Experiences, Challenges, And Opportunities, Courtney Stine, Sarah Frankel, Anita Hall

Faculty Scholarship

Academic Library Workers in Conversation is a C&RL News series focused on elevating the everyday conversations of library professionals. The wisdom of the watercooler has long been heralded, but this series hopes to go further by minimizing barriers to traditional publishing with an accessible format. Each of the topics in the series were proposed by the authors and they were given space to explore. This issue’s conversation revolves around parenting and how academic libraries must do more. The insights from the authors apply beyond parenting and are a great reminder that people make our academic libraries work.— Dustin Fife, series …

Rethinking Plagiarism In The Era Of Generative Ai, James Hutson

Faculty Scholarship

The emergence of generative artificial intelligence (AI) technologies, such as large language models (LLMs) like ChatGPT, has precipitated a paradigm shift in the realms of academic writing, plagiarism, and intellectual property. This article explores the evolving landscape of English composition courses, traditionally designed to develop critical thinking through writing. As AI becomes increasingly integrated into the academic sphere, it necessitates a reevaluation of originality in writing, the purpose of learning research and writing, and the frameworks governing intellectual property (IP) and plagiarism. The paper commences with a statistical analysis contrasting the actual use of LLMs in academic dishonesty with educator …