Digital Commons Network^™

Ai Hallucinations, Academic Integrity, And Learning-Centered Design, Robert K. Mott, Mary Myers

Teaching & Learning with AI

No abstract provided.

Generative Ai Prompt Engineering As A Tool For Multilingual Learner Writing And Teacher Planning In The K-12 Classroom, Angely C. Suarez Dejesus

Teaching & Learning with AI

This presentation explores the use of generative technologies such as Claude.AI and Chat GPT 5 to enhance writing planning and drafting as a tool for highschoolers, focusing on 10th grade pre-IB English.

Designing Equity With Ai: Scaffolding, Offloading, And Translation For Students With Learning And Attention Differences, Oksana Hagerty

Teaching & Learning with AI

This session positions AI tools as a mechanism for supporting students with learning and attention differences grounded in theories of distributed cognition. It distinguishes cognitive barriers arising from peripheral demands from those related to conceptual understanding and higher cognitive tasks. Drawing on scaffolding, cognitive offloading, and translation, the session argues for equity through intentional task design rather than individual exception. It concludes by examining the pedagogical trade-offs between AI-supported cognition and the pursuit of tool-independent mastery.

Avoiding Libel (And Possible Defamation Consequences) In The Age Of Ai Detection: Lesson From Journalism For Higher Education, Thomas A. Pear

Teaching & Learning with AI

This presentation argues that educators should not rely solely on AI‑detection tools when accusing students of AI‑assisted plagiarism. Instead, it proposes using detector scores only as “pedagogic probable cause,” a term developed by the author that signals when a submission warrants closer review, not a basis for disciplinary action. The presentation opens by outlining the limitations of current AI detectors, including high false‑positive rates and documented bias against non‑native English writers.

The presentation then reframes the issue through two complementary lenses: investigative journalism and defamation law. Drawing on the Woodward‑and‑Bernstein “two‑source rule,” it contends that a single detector score …

The Regional Ai Ecosystem: Faculty Fellows, Elearning Execution, And Community Partnerships Powering Workforce-Aligned Ai, Christopher Prokes

Teaching & Learning with AI

No abstract provided.

The Multimodal Video Evaluator (Mve): Codifying Decades Of Empirical Research Into A Systematic Multimedia Design & Evaluation Framework, Koichi Sato

Teaching & Learning with AI

Online higher education relies heavily on instructional videos, yet many faculty-produced media assets inadvertently induce high extraneous cognitive load. Instructional designers frequently face an “expert bottleneck,” lacking the operational bandwidth required to conduct manual, frame-by-frame pedagogical audits across expanding institutional media catalogs. To bridge this research-practice gap, this paper presents an operational blueprint for the Multimodal Video Evaluator (MVE), an open-access, AI-driven workflow designed to automate multimedia quality assurance. Built on a native multimodal artificial intelligence architecture, the MVE concurrently processes visual, auditory, and textual streams to evaluate media assets against 127 research-derived design guidelines rooted in the Cognitive Theory …

Physics-Informed Neural Network Solution Of The 2d Helmholtz Equation With A Gaussian Source, Theodoros Panagiotakopoulos, Chris Velissaris, Aristotelis Nikolaos Rapsomanikis

Faculty Scholarship and Creative Works

We present a physics-informed neural network (PINN) framework for solving the complex-valued two-dimensional Helmholtz equation with a localized Gaussian source and spatially varying permittivity. Starting from Maxwell’s equations, the frequency-domain scalar Helmholtz formulation under transverse electric (TE) polarization is derived and enforced directly within the neural network loss function. The model employs a sinusoidal representation network (SIREN) architecture to capture the oscillatory nature of wave solutions and incorporates the Sommerfeld radiation condition to impose open boundary conditions. Training is performed using a hybrid collocation strategy combined with a two-stage optimization procedure consisting of Adam followed by L-BFGS. Numerical experiments in …

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.

Arriving With The Five Senses: Resilient Whole Being In The Classroom, Mitra Emad

Teaching Online Pedagogical Repository

Using a simple sensory arrival exercise to welcome and orient students to the learning environment encourages a whole being wellbeing approach to learning. Moving through each of the five senses as a way to fully arrive “in class” promotes self-regulation and engagement. In online environments, this exercise gives students an opportunity to settle into a familiar space, as well as to engage with that familiarity in ways that “render the familiar strange,” enhancing curiosity and opening up engagement with the course materials and learning experiences that follow.

Boarding By Biometrics: How Smart Technology Is Reshaping Passenger Experience, Xiaoting Chi, Frank Badu-Baiden, Seongseop (Sam) Kim, Junwei Cao, Elena-Nicoleta Untaru, Heekyoung Jung, Heesup Han

Rosen Research Review

The research by Chi, Badu-Baiden, Kim, Cao, Untaru, Jung, and Han explores how biometric boarding transforms airline travel. Using technology acceptance, agenda setting, and behavioral reasoning theories, the study reveals how ease of use, usefulness, media exposure, and attitudes shape adoption. Findings stress convenience, engagement, and targeted communication, with age and gender influencing responses. For airport managers and designers, the research offers practical strategies for secure, efficient, and passenger-centered boarding systems.

The Pleasure Principle: Why Enjoyment May Be The Missing Link In Ai Adoption, Arthur Huang, Ahmet Bulent Ozturk, Tingting Zhang, Efren De La Mora Velasco, Adam Haney

Rosen Research Review

The research by Huang, Ozturk, Zhang, de la Mora Velasco, and Haney reveals a compelling insight: enjoyment—not just efficiency—is a key driver of whether guests will continue using AI in hospitality and tourism. By expanding the expectation-confirmation model, the study shows that perceived enjoyment, alongside performance and satisfaction, plays a pivotal role in shaping future use intentions. This shift toward hedonic value reframes how hoteliers and tourism professionals should design and promote AI services. The findings suggest that delight, fun, and emotional resonance are just as important as functionality when it comes to long-term engagement with AI-powered experiences.

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 …

Evaluating Regularized Logistic Regression And K-Nn On Mnist Under Increasing Random Missingness, Daniel Markwei

Data Science and Data Mining

This paper investigates the effect of random missingness on the performance of regularized multinomial logistic regression and the k-nearest neighbors (k-NN) classifier for handwritten digit recognition on the MNIST dataset. In particular, we study L1-regularized (LASSO) logistic regression and L2-regularized (Ridge) logistic regression alongside k-NN. Varying percentages of random missingness were introduced into the original dataset, and each model was evaluated in terms of its classification performance. The results show that random missingness degrades the performance of all three classifiers. Overall, k-NN consistently achieves higher accuracy than both L1- and L2-regularized logistic regression across all missingness levels; however, its performance …

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 …

Creating A Flipped-Classroom With Universal Instructional Design In A Hybrid Stem Course To Facilitate Active Learning, Lori L. Dunlop-Pyle

Teaching Online Pedagogical Repository

The strategy describes using Universal Instructional Design (UID) principles to create a hybrid STEM course to facilitate active learning exercises in class for a diverse group of learners.

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.

Rethinking The Mindfulness And Mindlessness In Media Evocation Of Human-Machine Communication: A Case Study On The In-Car Robot “Nomi”, Bing Wang, Longxiang Luo, Weizi Liu

Human-Machine Communication

The commonly used Media Equation framework in human-machine communication research exhibits limitations when explaining human-machine relationships in the AI era, giving rise to the Media Evocation paradigm. Based on the Media Evocation framework, this study employs in-depth interviews to investigate whether interactions between humans and the in-car robot Nomi are mindful or mindless, while also examining whether these interactions prompt reflections on the machine’s ontology. The findings indicate that most participants perceive Nomi as a human-like actor and interact with it mindfully. Highquality social cues, such as voice and facial expressions, can trigger mindful anthropomorphic responses in human-machine interaction, eliciting …

Human-Machine Communication: Complete Volume. Volume 12

Human-Machine Communication

This is the complete volume of HMC Volume 12.

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 …

Two Years To Madness: A 30-Month Journal Of Human–Machine Communication And Second-Hand Reality, Andrew Prahl

Human-Machine Communication

Drawing on a 30-month analytic-autoethnography of the first author’s journal as an earlyaccess OpenAI user, this study examines how sustained communication with generative AI affects everyday lived experience and identity. Inductive content analysis of 166 entries by independent coders is followed by theory-driven coding with the extended-mind and sensemaking frameworks. Three interlocking themes emerge. Enabled and Degraded captures the tension between new capabilities and efficiency versus creeping skill atrophy. Scary New World charts rising anxiety as productivity gains erode competitive and relational distinctiveness. The findings also show a growing, pervasive doubt about the human authorship of texts, images, and other …

The Material Condition: A Practice Theory-Oriented Infrastructural Turn To The Ethics Of Human-Ai Communication, Anne Mollen, Sigrid Kannengießer

Human-Machine Communication

This paper calls for an infrastructural turn in human–AI communication, centered on the materiality of generative AI. We argue that a nuanced understanding of ethical implications of generative AI necessitates examining the socio-technical infrastructures that constitute these systems. These infrastructures encompass not only technological artifacts but also human actors (developers, users, data subjects, etc.) and their practices as well as social contexts in designing, developing, implementing, and maintaining AI. Therefore, we propose to adopt a practice theory approach, to analyze how ethical concerns materialize within these infrastructures. This perspective reveals how infrastructures are contested spaces in global production chains, highlighting …

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 …

Whole Earth Machines: Human-Machine Communication For A Green Transition, Klaus Bruhn Jensen

Human-Machine Communication

The climate crisis of the 21st century represents an existential risk to humanity and biodiversity, posing essential questions of how communication may serve to coordinate mitigation of and adaptation to climate change. One recent response has been massive investments by governments and corporations in systems providing feedback on the state of Earth— Whole Earth Machines (WEMs). For human-machine communication (HMC) studies, WEMs invite sustained engagement with communication infrastructures as a key constituent of research agendas, beyond the interface encounters at the center of many HMC studies to date. The article presents a conceptualization and operationalization of WEMs as critical infrastructures …

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 …

Covid-19 Infection And Hypertension In Correlation With Race, Elizabeth Durkin

The Pegasus Review: UCF Undergraduate Research Journal

Healthcare disparities exist in the U.S. between different races. This study investigated the frequency of COVID-19 infections and hypertension cases among five different racial groups (White, Black, Asian, Native American, and Native Hawaiian). The study also examined the correlation between COVID-19 infections and hypertension with the hypothesis that because of disease predisposition and socioeconomic barriers, Black populations would have the highest rates of COVID-19 infections and hypertension. We used data from the Kaiser Family Foundation regarding COVID-19 cases and race in conjunction with Census population data to determine whether COVID-19 case frequency means differed by race. Data on hypertension and …

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 …

Variability In Parainfluenza Virus Derived From Persistently Infected Lung Epithelial Cells, Cassidy R. Conte

Honors Undergraduate Theses

An acute infection (AI) with RNA virus can progress to a persistent infection (PI) where infected cells continue to grow and replicate while producing progeny virions. PIs with respiratory viruses are clinically important, as they can lead to prolonged shedding of viruses and generation of mutant viruses that are altered in pathogenesis and/or immune responses. Parainfluenza type 5 (PIV5) is a prototypic RNA virus shown to cause PIs in cell culture. Plaques in tissue culture from an acute infection with parental PIV5 were homogeneous in size and shape. By contrast, plaques from PIV5 persistently infected cells were heterogeneous, having a …

The Role Of The Amygdala In Huntington Disease-Associated Aggression, Luis Torres

Honors Undergraduate Theses

Huntington disease (HD) is a fatal neurodegenerative disorder caused by a trinucleotide CAG expansion in the huntingtin gene (HTT). HD is characterized by motor, cognitive, and psychiatric symptoms that significantly impact patient and caregiver quality of life. Psychiatric symptoms, including depression, anxiety, and irritability, are common manifestations of HD and can emerge years before the onset is clinically diagnosed. Aggression is a common and challenging psychiatric symptom in HD, often misunderstood and associated with caregiver stress, early institutionalization, and reduced quality of life. Despite its clinical impact, aggression in HD lacks effective, targeted treatment options. Similar to HD …

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 …