Digital Commons Network^™

Simulation-Based School Safety Leadership: Practicing Early Warning Sign Recognition And Response, Daniel W. Eadens

Teaching Online Pedagogical Repository

This entry describes the effectiveness of a simulation involving safety.

Ai-Resilient Assessment Audit, Christopher Longo

Teaching Online Pedagogical Repository

The AI Resilient Assessment Audit is a quality assurance workflow where instructors use Generative AI to stress test their discussion prompts for vulnerabilities to academic dishonesty. Vulnerable prompts are remediated using a Personal Synthesis Protocol. This protocol requires students to anchor concepts to verifiable episodic memories and engage in structured peer review. This approach shifts assessments from simple recall to self-determined learning and fosters deeper student engagement.

Paws And Persuasion: How Dog Influencers Shape Hotel Booking Decisions, Wei Wei, Lu Zhang, Tianyu Ying, Yanyan Zheng

Rosen Research Review

The research by Wei, Zhang, Ying, and Zheng explores how pet influencers—specifically dog influencers on Instagram—impact hotel booking intentions. Through two experiments, the study reveals that message appeal (rational vs. emotional) interacts with audience characteristics like prior experience and perceived attractiveness of the pet influencer. Rational messages are more persuasive for less experienced travelers and when the pet influencer is perceived as less attractive. Emotional messages, while engaging, are less effective in these contexts. This research uncovers the nuanced power of pet influencer marketing and offers practical strategies for hospitality marketers seeking to tap into the booming “cute economy” of …

Rethinking Textbook Reading Checks: Designing Reflective Assignments With Ai, Sue A. Bauer, Ezekiel Walker Dr.

Teaching Online Pedagogical Repository

This strategy uses AI as a planning partner to help instructors design reading-based assignments that move beyond traditional quizzes by emphasizing analysis, interpretation, and reflection on textbook chapters. By providing AI with key themes and learning objectives, instructors can quickly generate structured prompts and rubrics that assess insight, use of evidence, and clarity of reasoning. The approach encourages deeper student engagement with readings while allowing instructors to customize and maintain oversight of the assignment and evaluation process.

Pennies In The Bank: Building Background Knowledge, Brooke Lee Webster

Journal of English Learner Education

Abstract

Across the United States, teachers are met with stringent time requirements that may not align with the needs of the students inside the classroom. This paper explores the efforts of condensing and prioritizing in a diverse classroom. Through a reflective narrative of teaching comprehension to emerging bilingual students, this paper presents a structure that leverages morning meetings and discussion as prongs for maximizing the benefit of students within limited instructional minutes. Tasks that build competence, confidence, and connection cycle to foster the environment that students need to thrive. Additionally, this paper investigates the role of building background knowledge in …

A Quasi-Experimental Study On The Effectiveness Of Achieve3000 On The Reading Comprehension Scores Of Ells With Ld, Paula P. Fields

Journal of English Learner Education

The purpose of this quasi-experimental pretest-posttest study was to determine if a significant difference existed in the comprehension scores of secondary English Language Learners with learning disabilities after treatment. The problem addressed is that a significant correlation exists between English language learners and learning-disabled students’ low reading proficiency scores and student achievement, leading to decreased graduation rates. Schema theory served as the theoretical foundation of this research because when the appropriate schema is activated, it helps increase comprehension. The research question guiding this study was: Is there a significant difference between the reading comprehension scores of high school English language …

Ai-Powered Pathways To Open Education: Enhancing Practice And Expanding Discovery, Rebecca Mcnulty, Lily Dubach

Faculty Scholarship and Creative Works

Generative AI is changing how we teach and learn, and this session will show practical ways it can support open education. We will look at two everyday challenges: finding aligned open materials and spotting places in a course where open practices could enhance opportunities for collaborative learning. An instructional designer will demonstrate how custom GPTs can review a syllabus and suggest places where open pedagogy could involve students in co-creating and sharing knowledge. A librarian will show how large language models can help locate courses and syllabi that already use open practices, making it easier for faculty to discover and …

Video-Based, Small Group, Synchronous Discussions (Vssd), Jeff Renfrow

Teaching Online Pedagogical Repository

The VSSD is a research-supported online discussion model that can produce significant increases in student perceptions of social presence, learning, and satisfaction as compared to the traditional text-based, asynchronous, whole-group discussion model. In the VSSD, students lead the discussion experience by scheduling a synchronous, remote video meeting with their small group, they engage in the discussion topic for 30 to 45 minutes, then individually record a privte reflection video that is submitted to the instructor for evaluation and feedback.

Ai-Generated Musical Educational Videos: A Creative Learning Strategy For Any Discipline, Gulfem I. Yucelen

Teaching Repository of AI-Infused Learning

In this activity, students transform course concepts into original songs by writing lyrics, refining them with AI, and generating music and video content. Generative AI tools support the creative process, while students provide oversight to ensure accuracy and clarity. The final product is a musical educational video that deepens understanding and can also be shared with peers or younger learners.

Human-Machine Communication: Complete Volume. Volume 12

Human-Machine Communication

This is the complete volume of HMC Volume 12.

Normalizing Ai: The Evanishing Effect And Rethinking The Machine Heuristic, Bumju Jung, Cameron W. Piercy, Patric R. Spence

Human-Machine Communication

This study examines how people evaluate factual claims attributed to human journalists versus artificial intelligence (AI) news bots, and how these evaluations are shaped by individual endorsement of the machine heuristic. An online experiment (N = 233) used a 2 (Agent: human vs. AI) × 2 (Information Veracity: accurate vs. inaccurate) design in which participants viewed a short tweet embedded in either a human or AI profile and then rated perceptions of source credibility, objectivity, bias, and accuracy. Endorsement of an AI-focused machine heuristic was significantly associated with higher source credibility, perceived objectivity, and perceived accuracy, and lower perceived bias, …

Ai Humanizers, Pragmatists, Skeptics: A Cluster Analysis Of Normative Attitudes For Ai’S Capabilities And Roles, Kate K. Mays, Ekaterina Novozhilova

Human-Machine Communication

This study explores people’s attitudes about artificial intelligence’s (AI) capabilities through a normative lens. Drawing from literature on phenomenological, ontological, and heuristic judgments about machines, we aim to better understand what capabilities people think AI should be able to have and how that relates to enthusiasm about having AI take certain roles in their lives. Survey participants (N = 601) were grouped via two-step clustering based on their attitudes, revealing three clusters: AI humanizers, who expect empathy and social interaction from AI; AI pragmatists, who expect cognitive capabilities; and AI skeptics, who prefer AI with limited human-like traits and emphasize …

Explain. Write. Edit. Summarise: An Exploratory Study On Agency Negotiations In Student-Chatbot Conversations, Árni Már Einarsson Mr, Ekaterina Pashevich

Human-Machine Communication

LLM-based chatbots such as ChatGPT have given technologies that traditionally operated on the back end a user-friendly, conversational interface. Their rapid adoption among students has prompted universities worldwide to issue guidelines and re-examine existing practices. Supplementing prior research based on discourse analysis and self-reported measures (e.g., surveys and interviews), we propose an approach for analyzing naturally occurring student–chatbot interactions, rooted in conversation analysis of chats (n = 503) donated by eight current Danish university students. The analysis identifies conversational patterns across three main types of activities and examines how agency is negotiated across the structural dimensions of signification, domination, and …

The Epistemic Power Of Human-Machine Communication, Katrin Etzrodt, Autumn P. Edwards

Human-Machine Communication

This editorial introduces Volume 12 of Human–Machine Communication by positioning communicative machines as epistemic provocateurs that unsettle inherited distinctions among agency, meaning, and relation. Rather than treating these disruptions as anomalies to be resolved, the editorial argues that Human–Machine Communication (HMC) is distinctively equipped to register, analyze, and sustain such epistemological tensions. Drawing on philosophical traditions from Aristotle to Marx and Heidegger, the authors show how contemporary communicative machines simultaneously strain multiple historical settlements that once stabilized human–machine boundaries. The volume frames HMC as a “seismograph” for and as a “practice of” epistemological change, tracing how agency and meaning are …

Interpretable Linear Models For Heart Disease Prediction: A Comparative Study, Dipok Deb, Emran Hossain

Data Science and Data Mining

Heart disease remains a leading cause of mortality worldwide, underscoring the importance of accurate and transparent methods for early diagnosis. While many machine learning and artificial intelligence models have demonstrated strong predictive performance, their limited interpretability poses challenges for clinical adoption. In this study, we evaluate three interpretable linear classification models—Generalized Linear Model (GLM) logistic regression, L1-regularized (Lasso) logistic regression, and Linear Discriminant Analysis (LDA)—for heart disease prediction using the Cleveland Heart Disease dataset. Following comprehensive data preprocessing, the models are assessed on a held-out test set using standard evaluation metrics, including accuracy, precision, recall, F1-score, and the area under …

Predicting Male Flowering Time In Maize Using Machine Learning Technique, Dipok Deb

Data Science and Data Mining

This study compares three machine learning approaches—Elastic Net, Principal Component Regression (PCR), and Partial Least Squares (PLS)—for variable selection and prediction within a high-dimensional Maize-GWAS framework. The goal was to accurately predict the complex polygenic trait of time to male flowering while managing the challenges of numerous, highly correlated genetic markers. The ENET model, which combines l1 and l2 penalties, delivered the highest predictive accuracy and successfully identified a select subset of the most influential genetic variants. In contrast, PCR and PLS, both utilizing dimension reduction, offered a significant advantage in computational speed and model stability. The findings confirm that …

Data-Driven Prediction Of Superconducting Critical Temperature: A Linear And Regularized Linear Modeling Approach, Dipok Deb

Data Science and Data Mining

This study adopts a data-driven approach to estimate the critical temperature of superconducting materials using linear machine learning models. A comprehensive dataset derived from material physico-chemical properties was analyzed after systematic preprocessing and standardization. Three linear modeling strategies—Linear Regression, Ridge Regression, and Linear Regression with Subset Selection—were developed and evaluated using standard regression performance metrics. The findings demonstrate that both basic and regularized linear models can effectively capture the relationship between material features and superconducting behavior, offering robust and interpretable predictions. While feature selection enhances model transparency, it comes with a modest reduction in predictive capability. Overall, this work emphasizes …

Digital Redlining In The Smart City: Artificial Intelligence, Housing Law, And Structural Urban Inequality, Spurthi Nrusimhadevara

Undergraduate Scholarship and Creative Works

Artificial intelligence is increasingly used in urban housing systems, where it shapes decisions about tenant screening, rent pricing, lending, zoning, and neighborhood investment. Although these tools are often promoted as efficient and impartial, they frequently rely on historical data that reflect racial, economic, and spatial inequality. As a result, AI systems can reproduce discriminatory outcomes even when protected characteristics are not directly used. This paper examines digital redlining in the smart city and argues that algorithmic housing tools mirror long standing structural inequities that raise significant concerns under fair housing and civil rights law. It evaluates how automated screening, predictive …

Show Your Work: Assessment In The Age Of Ai, Kevin Yee, Laurie Uttich, Elizabeth Giltner, Anastasia Bojanowski

UCF Created OER Works

The fourth book from a team of college instructors who have been in the trenches of AI and higher education since the beginning, Show Your Work: Assessment in the Age of AI is a practical, discipline-spanning guide for educators who are ready to redesign their assignments for a world where AI is a given. Organized around three approaches—co-creating with AI, writing without it, and finding alternative AI-resistant assessments—this book offers more than 50 concrete strategies that faculty can mix, match, and adapt to their own courses and contexts. Whether you want to integrate AI as a learning tool, build assignments …

University Of Central Florida Graduate Catalog, 2025-2026, University Of Central Florida

UCF Catalogs

No abstract provided.

Social Media, Fitness, Gender, And Rhetoric, Emily M. Potts

High Impact Practices Student Showcase Spring 2026

The goal for this study was to find how TikTok uses rhetoric to argue about effective workout routines for males versus females and what values or ideologies does this rhetoric help to promote. People tend to take health and fitness advice from social media although it is not the most creditable place. Understanding how people on TikTok use rhetoric to argue about effective workouts for males versus females and what values and ideologies this rhetoric helps to promote is a gap, although it affects a significant amount of people in today's society.

To discover how rhetoric is used in this …

Battling Human Trafficking: How Social Media Advertising Influences Awareness, Cami Dobson, Addyson Jones, Giovanni Gioia, Alexandra Boveil

High Impact Practices Student Showcase Spring 2026

In our Principles of Advertising class, our group analyzed an anti-human trafficking non-profit organization, The Lifeboat Project, to create an ad campaign. Specifically, we focused on how to utilize social media in order to reach a target demographic. The Lifeboat Project aims to raise awareness on human trafficking, while also supporting victims through their resources. The purpose of our project was to promote the organization's goal of visibility and prevention tools.

First, we developed our target audience, and created a target persona. We conducted research on the organization and competitors. Using this information, we constructed survey questions, and distributed them …

Non-Invasive Detection Of Intracranial Pressure, Andrei V. Nesterenko

Honors Undergraduate Theses

Intracranial pressure is a critical metric used when managing tumors, strokes, TBIs, hydrocephalus, and other operative conditions. Traditional methods for continuous ICP monitoring, intraparenchymal catheters, epidural transducers etc., are invasive and carry a high risk of infection. Previous attempts to create accurate, easy to use, and non-invasive ICP monitoring techniques have been unsuccessful. In this study, we investigated the utility of supraorbital and posterior auricular photoplethysmography to monitor changes in ICP during orthostatic tilt and hyperventilation, which increase and decrease ICP respectively.

Through a continuous 5-minute recording on a tilt-table we characterized SOA and PAA waveforms in 12 participants (ages …

Experimental And Numerical Study On The Stability Limits Of Ammonia And Ammonia/Hydrogen Flames Inside A Toroidal Jet-Stirred Reactor, Guillermo Alberto Barrios Cadenas

Graduate Studies Theses and Dissertations 2026

Ammonia’s (NH₃) properties as a carbon-free hydrogen carrier, its phase characteristics, and its wide global infrastructure present a solid case as a potential surrogate for carbon-based aviation fuels. Delivering a zero-emission NH₃-based engine requires careful integration and optimization of the combustor and thermal management systems, a process that requires high-fidelity chemical reacting models experimentally validated through the use of simplified combustors. This study investigates NH₃ fundamental combustion characteristics at conditions relevant to aviation gas turbines using a newly constructed toroidal jet-stirred reactor (TJSR) facility. Lean blow-off (LBO) experiments were carried out for NH₃ blends …

Ecological And Evolutionary Divergence Of A Shared Sympatric Color Polymorphism In Paracirrhites Hawkfish, Samuel Greaves

Graduate Studies Theses and Dissertations 2026

Color polymorphism provides a tractable window into how selection, gene flow, and ecology interact to maintain phenotypic diversity and initiate divergence. I investigate the ecological and genomic basis of sympatric light and melanistic morphs in two reef hawkfishes, Paracirrhites arcatus and P. hemistictus, across Guam and Hawai‘i. This study aims to determine whether the color morphs of these hawkfishes are a stable polymorphism or have begun the process of ecological speciation. For P. arcatus revealed substantially lower density on Guam (0.086 ind/m²) than reported for Hawai‘i (0.292 ind/m²) and a strong skew away from the melanistic morph on Guam …

The Vagabond Way: A Qualitative Study Of Intentional Non-Participation In Structured Society, Lorena E. Black

Honors Undergraduate Theses

This study analyzes intentional vagabondage as both a philosophical position and a lived critique of structured society. Using qualitative fieldwork conducted at Fairlawn Family Church in Fort Pierce, Florida—including ten semi-structured interviews, participant observation, and grounded theory analysis—the study examines how individuals who voluntarily disengage from formal systems of housing, labor, and legality construct meaning, identity, and stability beyond institutional boundaries. The analysis identifies three central themes: rhythm, referring to the patterned routines that sustain mobility; reciprocity, which characterizes social exchange and support networks; and refusal, expressed as a deliberate rejection of societal expectations. While many participants describe their paths …

Laser Beam Shaping Using A Neural Network, Azeem A. Hakim

Honors Undergraduate Theses

Multiphoton lithography (MPL) is a method of laser-based 3D-printing for fabricating micron-scale structures point-by-point in a photopolymerizable medium. MPL’s high-resolution capabilities have made it a powerful method for the fabrication of many devices, such as microelectromechanical systems (MEMS) and tissue scaffolds.  The throughput of MPL processes can be increased by using spatially shaped laser beams that expose large areas or volumes simultaneously. A laser beam can be reshaped by passing it through a spatial light modulator (SLM) displaying a pre-designed phase mask. One type of laser beam profile used for this purpose is the Bessel beam, a type of structured …

Participatory Barriers And Single-Member Districts In Planning For Latino Demographics: A Spatial Analysis Of Osceola County, Florida, Amy Garcia Paniagua

Honors Undergraduate Theses

This mixed-methods case study on Osceola County, Florida examines how participatory barriers shape planning outcomes for Latino communities within single member district systems. Demographic transformation has shaped Osceola into one of three Hispanic/Latino majority counties. For Latinos, unique barriers to civic access exist, with the potential for exclusion in planning processes. The research bridges participatory planning theory with theories supporting single-member district electoral representation by evaluating whether district-level governance mitigates inequities where civic engagement is constrained. Methods integrate GIS-based spatial analysis with an institutional review of district-level actions to assess relationships between Hispanic civic accessibility and planning equity. Two composite …

Comparative Analysis Of Serum-Free Culture Conditions On Cell Proliferation And Extracellular Vesicle Production By Adipose-Derived Stem Cells, Ayna Ghulldu

Honors Undergraduate Theses

Adipose-derived stem cells (ADSCs) are promising candidates in regenerative medicine due to their proliferative capacity, self-renewal, and secretion of extracellular vesicles (EVs) that mediate intercellular communication. Serum-free media has been increasingly explored for MSC culture as it eliminates xenogeneic components, improving human therapeutic suitability. However, comparative evaluation of distinct serum-free formulations on ADSC proliferation and EV output simultaneously remains limited. This study compares a serum-containing medium to three proprietary serum-free media prototypes differing in composition, including the presence or absence of extracellular matrix proteins, to inform the optimization of culture conditions for clinical use. Proliferation, EV characteristics, and gene expression …

Are Courts Developing A Consistent Standard For Sanctioning Attorneys Who Misuse Genai In Legal Filings?, Natalia Borges

Honors Undergraduate Theses

This thesis examines whether Florida courts are developing an emerging statewide standard governing attorney use of generative artificial intelligence in litigation and whether this trend supports the need for formal statewide codification. This study addresses growing concerns about fabricated citations, unverified legal research, attorney sanctions, and inconsistent disclosure practices as generative artificial intelligence becomes integrated into legal drafting and research. This research reviews the Florida Rules regulating the Florida Bar, ethics guidance on generative AI, Florida procedural certification requirements, disciplinary actions, and administrative orders from Florida judicial circuits that require disclosure and verification of artificial intelligence use in court filings. …