Digital Commons Network^™

Exploring Language Through Systemic Functional Linguistics: Importance Of Communicating And Developing Academic Language For Multilingual Learners, Yana Shifrina-Piljovin

Journal of English Learner Education

Systemic Functional Linguistics (SFL) is a comprehensive theory of language that offers a unique perspective on how we use language to communicate and create meaning. SFL provides educators with a powerful theoretical framework for understanding how language functions in various contexts and how this knowledge can be applied to enhance classroom instruction. Developed by linguist Michael Halliday in the 1960s, SFL has become an influential framework for understanding linguistic metafunctions, from everyday conversations to academic discourse. The "systemic" aspect of SFL refers to the idea that language is a network of systems, each offering a set of choices for expressing …

Disentangling (Hybrid) Trustworthiness Of Communicative Generative Ai As Intermediary For Science-Related Information—Results From A Qualitative Interview Study, Evelyn Jonas, Esther Greussing, Monika Taddicken

Human-Machine Communication

The increasing prevalence of communicative Generative AI, such as ChatGPT, highlights their transformative potential for science communication while raising critical questions about users’ trust in these systems conveying science-related information. As perceptual hybrids these agents challenge traditional notions of trustworthiness, and it remains unclear to whom or what users refer to as the object of trust. This qualitative interview study integrates dimensions from human-machine and epistemic trustworthiness within a hybrid framework, complemented by a descriptive source orientation model. It highlights that trustworthiness assessments can extend beyond a chatbot’s interface, emphasizing the perceived salience of its underlying infrastructure, developers, and organizations. …

Generative Artificial Intelligence And Collaboration: Exploring Religious Human-Machine Communication And Tensions In Leadership Practices, Pauline Hope Cheong, Liming Liu

Human-Machine Communication

The adoption of generative artificial intelligence (GAI) applications has bolstered efforts toward human-machine collaboration. Given the lag in research on AI and religion, this study examines how pastors engage GAI to develop religious human-machine communication practices that constitute their leadership. Findings from in-depth interviews with pastors in the U.S. reveal that they view GAI as an idea generator, research assistant, co-author and translator. Clergy enact multiple ways to incorporate GAI communication in religious education and to enhance sermonic performances. Concurrently, pastors perceive tensions between innovation and established rites, as they contend with the authenticity and spiritual depth of GAI content …

Tools Or Teammates? Examining Agency Negotiation In Human-Genai Collaboration In Creative Work, Yuan Sun, Ignacio Fernandez Cruz, Donggyu Kim

Human-Machine Communication

As Generative AI (GenAI) becomes increasingly integrated into creative work, creative professionals face an emerging dilemma: while they can leverage powerful AI capabilities through prompts, the automated process also introduces uncertainties and risks. This study, based on semi-structured interviews with 18 creative professionals, explores their experiences and perceptions of using GenAI tools in creative work. The findings revealed that GenAI’s perceived adaptability, creativity, and scalability enhanced sense of agency in the creative process. Conversely, limitations in customizability, uncertainty, and feedback mechanisms undermined human agency. These perceptions were influenced by users’ conceptualization of GenAI—as either a simple tool or a collaborative …

Investigating The Persuasive Potential Of Communicating With Generative Artificial Intelligence Chatbots For Mental Health: The Roles Of Perceived Message Contingency, Cognitive Elaboration, And Issue Involvement, Hanyoung Kim, Yanyun (Mia) Wang

Human-Machine Communication

With the ever-increasing adoption of generative artificial intelligence (GenAI) chatbots in diverse communication roles, there is a burgeoning need to address how people process and respond to messages from these technologies. This study explores the theoretical mechanisms by which the use of GenAI chatbots influences persuasive outcomes related to mental health, examining perceived message contingency and cognitive elaboration as mediators, and issue involvement as a moderator between the two mediators. Through an experimental setting using ChatGPT, compared to non-conversational online resources, we discovered that GenAI chatbot use led to greater cognitive elaboration through an increased sense of message contingency, leading …

“Made Classes Easier Than A Coloring Sheet”: Student Perceptions And Uses Of Genai, Jessalyn I. Vallade, Renee Kaufmann, Trenton Upchurch

Human-Machine Communication

Student use of GenAI is growing and so are the faculty concerns. With research providing mixed suggestions and approaches, this study sought to understand the student perspective on ethical uses, their own motives and perceived benefits of GenAI use, the risks involved, and their perceptions of susceptibility and severity related to unethical use (i.e., plagiarism/cheating). Results revealed the complexity of student considerations regarding the uses, risks, and benefits of GenAI and its potential for personalized learning enhancement. Students generally view the likelihood of being caught submitting AI-generated work as their own as high and the consequences as severe. The viability …

Human-Machine Communication: Complete Volume. Volume 10

Human-Machine Communication

This is the complete volume of HMC Volume 10.

Creepy, Invasive, And Exploitative Algorithms: A Cpm Analysis Of Users' Privacy Breakdowns And Recalibration Practices With Social Media Algorithms, Matthew J. A. Craig, Jeffrey T. Child

Human-Machine Communication

Social media content filtering algorithms can both provide desired personalized content and ads for users. However, sometimes these recommendations can resemble individual private information. How might users navigate these experiences to best manage their private information? The present exploratory study utilizes the rules- and systems-based framework of communication privacy management (CPM) theory to explore social media users’ experiences of privacy breakdowns with social media algorithms and investigates what users do in response to said breakdowns. These responses were refined using content analysis and divided into different categories of privacy breakdowns and recalibration strategies. Implications for future research surrounding human-machine communication …

The Hai-Io Model: A Framework For Understanding The Human-Ai Communication Process, Rae Francis Quilantang

Human-Machine Communication

The increasing integration of artificial intelligence (AI) into daily life calls for new theoretical frameworks that capture human-AI interaction’s dynamic, feedback-driven nature. Traditional models treat AI as a passive medium, overlooking its adaptive capabilities. This paper proposes the Human-AI Interaction Outcomes (HAI-IO) model, an interdisciplinary framework synthesizing human-machine communication, social exchange theory, dialogue systems, and computational feedback models like cybernetics and reinforcement learning. The HAI-IO model frames interaction as iterative and bidirectional—AI adapts through predictive processing while users adjust based on AI feedback. This mutual adaptation shapes trust, engagement, and system optimization. The model informs AI system design, user education, …

Development And Validation Of The Attitudes Toward Algorithms Scale: A Universal Scale To Measure Individuals Attitudes Toward Algorithmic Decision-Making, Nikolai Bock, Astrid M. Rosenthal-Von Der Pütten

Human-Machine Communication

Algorithmic decision-making (ADM) has become increasingly important across various fields, ranging from personal entertainment to criminal justice. While existing research has predominantly explored evaluative outcomes like individuals’ perceptions and interactions with these systems, there remains a significant gap in understanding the underlying mechanisms that lead to these outcomes. Building on traditional behavioral intention theories, we identified attitudes toward algorithms and ADM as crucial determinants. In response to the lack of an appropriate measure for this construct, we developed and validated the Attitudes Toward Algorithmic Decision-Making Scale (ATAS), a novel instrument designed to assess core beliefs that drive attitude formation toward …

Casa Renovations: Examining Social Responses To An Anthropomorphic Media Representative That Is Separate From The Core Technology Being Represented, Rabindra Ratan, Dayeoun Jang, Taenyun Kim, Kelsey Earle, Gabriel E. Hales, Yiming Skylar Lei, Chaeyun Lim, Andrew Gambino

Human-Machine Communication

To extend our understanding of CASA and account for changes in technological complexity and configuration, this research asks: Do increasing levels of social cues in a media representative that is separate from the core technology it represents lead to increased perceived anthropomorphism of the core technology? And does such perceived anthropomorphism predict positive treatment of the core technology? We conducted two complementary studies observing e-scooter use and treatment, an online experiment focused on responses to video stimuli and a field experiment focused on actual user behavior. Findings suggest that, indeed, social cues in a media representative (i.e., an e-scooter rental …

Transformations And Revelations: The Communicative Constitution Of Trustworthiness And Trust Through Ai Development Practices, Tessa Bruijne, Anouk Mols, Jason Pridmore

Human-Machine Communication

This study explores AI development practices to understand how trustworthiness is built into AI systems, and how this generates trust in AI. Through a multi-sited ethnography based methodology, we analyze observations, interviews, and documentation from AI developers working on trustworthy AI. Our analysis shows two key practices: transformation and revelation. Through transformational AI development practices trustworthiness is (re)constituted, though more or lesser degrees. Through revelation practices, AI developers communicatively engage with others to generate trust. This focus on developers adds to the user-centric perspective and shows the role nontechnical development practices have in shaping trust and trustworthy AI before it …

Socio-Technical Exchange With Machines: Worker Experiences With Complex Work Technologies, Cameron W. Piercy, Reaia Turner-Leatherman

Human-Machine Communication

Machines are now commonplace work partners and Human-Machine Communication (HMC) is part of modern work. Guided by the machine heuristic and Social Exchange Theory (SET) this paper uses interviews with 22 workers to explore the socio-technical relationships between humans and machines at work. Participants worked with complex machines across a wide variety of industries and roles and findings reveal participants see machines as part of the work ecosystem, develop everyday machine heuristics to guide repeated interactions with machines, and that elements of human uniqueness persist in evaluations of humans and machines. Discussion points emphasize situated and developing human-machine interaction scripts, …

Prompted By Me. Generated By Chatgpt, David J. Gunkel

Human-Machine Communication

This essay—which is not only about human-machine collaboration but is a performance in human-machine collaboration—interrogates the shifting terrain of authorship and creativity in the age of generative artificial intelligence (GAI). Challenging both the instrumentalist view of technology and the romantic myth of the singular genius, it argues for a reconceptualization of creative production as distributed, dialogical, and co-constituted. Drawing on both theoretical innovations in poststructuralism and the practices of pre- and post-modern content creators, the essay repositions the algorithm not as a mere tool but as an active participant in the generation of meaning. In doing so, it exposes and …

Being And Becoming In Human-Machine Communication: Core Commitments And Conceptual Foundations Of A Trans-Ontological Field, Autumn P. Edwards, Katrin Etzrodt

Human-Machine Communication

This introduction traces the emergence of Human-Machine Communication (HMC) as a distinct field centered on communication across ontological boundaries. Arguing that HMC is not merely about interacting with machines but about how communicative presence and legitimacy are constituted, the authors introduce the Act–Mean–Relate (AMR) paradigm to conceptualize how machines’ capacity for action, signification, and relation enable communication. HMC challenges human exceptionalism by shifting focus from internal states and categorical differences to symbolic and relational dynamics. It addresses the interpretive labor involved in making machine others intelligible and emphasizes communication as the co-construction of social reality. The article highlights tensions between …

Pilot Fatigue And Required Rest Period For Korean Air Force Pilots Flying High-Performance Aircraft, Mijin Hong

Graduate Thesis and Dissertation post-2024

Over the years, significant advancements have been made in aircraft technology and in understanding the detrimental effects of fatigue on flight performance. However, integrating these advancements into crew rest regulations, particularly for the Republic of Korea Air Force (ROKAF) operating high-performance jets, requires further review. This study employs a systematic review with thematic analysis to assess whether ROKAF’s current rest regulations are sufficient. Relevant studies were identified from English-language databases (e.g., FAA, ICAO, Google Scholar) and Korean-language databases (e.g., RISS, KCI). Titles and abstracts were initially reviewed, followed by full-text assessments based on inclusion and exclusion criteria focusing on military …

Machine Learning-Enhanced Optimization For The Real-Time, Secure, And Efficient Operation Of The Energy-Water-Hydrogen Nexus, Mostafa Goodarzi

Graduate Thesis and Dissertation post-2024

Given the escalating urgency of climate change, our research addresses the imperative need to curb carbon emissions, particularly from the electricity sector, which accounts for a quarter of total emissions in the U.S. We propose integrated systems, such as the energy-water nexus (EWN) and an innovative concept known as the energy-water-hydrogen (EWH) nexus, which integrates renewable energy sources (RESs) with green hydrogen production through water electrolysis. These concepts align seamlessly with the nation’s commitment to global climate agreements, including the Paris Agreement. Furthermore, green hydrogen—a clean and efficient energy source produced via water electrolysis powered by renewable energy—emerges as a …

Pedestrian Monitoring And Crossing Intention Prediction At Intersections Using Computer Vision And Deep Learning, Ahmed Abdelrahman

Graduate Thesis and Dissertation post-2024

Ensuring the safety of Vulnerable Road Users (VRUs), including pedestrians, bicyclists, and E-scooter riders, at intersections is crucial for sustainable and efficient urban mobility. Despite recent advancements in transportation technologies, accurately understanding and predicting human behavior at intersections remains challenging, resulting in unsafe interactions, crossing violations, and diminished trust in traffic systems. This dissertation presents an integrated approach comprising three novel frameworks: VRUCrossSafe, VRU-CIPI, and the Video-to-Text Pedestrian Monitoring (VTPM) system, collectively addressing critical gaps in intersection safety, VRU behavior prediction, and privacy-preserving traffic monitoring. First, VRUCrossSafe introduces a real-time intersection safety solution utilizing computer vision and ensemble machine learning …

Tail-Imbalance Diffusion Equalizer For Class-Balanced Generation, Chinmay Dhanraj Nehate

Graduate Thesis and Dissertation post-2024

Real-world image corpora are often imbalanced. On long-tailed datasets, the head class can outnumber the tail by a large margin, and a vanilla diffusion probabilistic model (DPM) consequently loses fidelity and diversity on rare categories, undermining controllable generation. To address this gap, we present Tail Imbalance Diffusion Equalizer (TIDE), a training framework that restores class balance without discarding data or adding extra training stages. Our contribution is threefold: (i) score field rebalancing, where we embed class-prior knowledge into a mixing matrix that routes gradients toward minority classes, with this class-prior knowledge consisting of the empirical label frequencies in the training …

A Variable Resistance Suit (Vars) And An Extendable Prosthetic Arm (Expa) For Physical Rehabilitation And Assistance, Ibrahim F. Kadhim

Graduate Thesis and Dissertation post-2024

This dissertation presents the design, development, and evaluation of two novel wearable assistive technologies – Variable Resistance Suit (VARS) and the Extendable Prosthetic Arm (EXPA) – to improve rehabilitation outcomes and functional independence of individuals with musculoskeletal impairment. VARS is a modular, lightweight, and wearable resistance training system that applies bidirectional, speed-dependent, and variable mechanical resistance to the elbow and knee joints. It addresses the limitations of traditional resistance equipment by offering a portable, safer, and more accessible alternative. Importantly, VARS enables targeted engagement of specific muscle groups during training, minimizing the risk of overloading adjacent or compensatory muscles. VARS …

The Path Of Peace: Non-Violent Methods Of Play In Indie Video Game History, Ryu R. Yamamoto

Graduate Thesis and Dissertation post-2024

This research project investigates the cultural and historical significance of independently published Japanese bullet-hell/danmaku games from the 2000s and 2010s. This project highlights gaps in current game histories, particularly surrounding the influence of these games on heralded contemporary titles like Undertale (2015). The significance of independently published “doujin” Japanese digital media, notably the Touhou Project series, is often overlooked in American game studies contexts. Examining these underexplored games aims to enrich the understanding of cultural-historical games research, particularly in positioning lesser-known and lower-budget games, and contribute to the broader discourse on cross-cultural interactions within the gaming community. Comparative analyses of …

Limitations Support Learning: A Design Based Study Of Ethically Scaffolded Generative Ai Tools For Long Form Argumentation And Metacognition, Lindsay Konradt

Graduate Thesis and Dissertation post-2024

This design‑based research study implemented and refined an instructional model that used generative AI (GAI) tools within a nine‑week AP Capstone Seminar argumentation unit. The model combined teacher feedback and modeling, structured reflection tasks (including AI‑assisted reflection), AI assisted editing, AI-assisted literature searches, and counterargument support using restricted chatbots. During the nine week period, responsibility for feedback moved from teacher and AI supported scaffolding to student driven writing practice and revision. Data collection focus on four advanced high school students at a Florida public high school, including multiple drafts, GAI input and output logs, reflections, and pre‑ and post‑unit semi‑structured …

Fit Index Criteria For Multisample Analysis In Sem With Ordinal Data: A Monte Carlo Simulation Study, Suat Babayigit

Graduate Thesis and Dissertation post-2024

Measurement invariance is crucial for valid group comparisons in structural equation modeling (SEM), yet testing invariance becomes challenging when using ordinal data. This dissertation evaluates the adequacy of widely used fit index difference criteria (ΔCFI, ΔRMSEA, ΔSRMR) for multisample invariance testing with ordinal indicators. Traditional Δ fit cutoff thresholds were established based on continuous, normally distributed data, but ordinal measures can distort invariance conclusions. Monte Carlo simulations address this issue by manipulating a comprehensive set of conditions: sample sizes (200, 400, 1000), group size ratios (equal vs. unequal), model complexity (low vs. high), underlying distributions (normal vs. nonnormal), Likert scale …

Integrating Education For Sustainable Development Into Elementary Curriculum Through Transdisciplinary Learning: A Case Study Of Teachers At Designated Green Schools, Amanda Ferguson

Graduate Thesis and Dissertation post-2024

The rising number of sustainability-focused jobs in the United States has underscored the need for greater exposure to Education for Sustainable Development in early education. While higher education and secondary schools offer courses on sustainability and the environment, elementary students have limited opportunities to engage with these topics. This embedded multiple-case study examined the role of Education for Sustainable Development in elementary classrooms, specifically through transdisciplinary lessons. The research was guided by the question: How do elementary teachers in county-designated Green Schools in a Florida district use transdisciplinary lessons to teach sustainability within their existing curriculum?

Using the theoretical framework …

Preserving Florida History In 3d: A Digital Public History Project Preserving Paleo-Native American Artifacts And Jack West Architecture From Warm Mineral Springs, Florida, Trevor D. Colaneri

Graduate Thesis and Dissertation post-2024

This thesis project examines low-cost photogrammetry and 3D walkthrough tours to preserve a collection of artifacts and buildings from Warm Mineral Springs, Florida. The documented objects and structures consist of a small collection of artifacts from Warm Mineral Springs currently held by Florida’s Bureau of Archaeological Research and three buildings designed by noted architect Jack West, a Sarasota School of Architecture member, which suffered extensive damage from a category five hurricane in 2022. Warm Mineral Springs is an archaeologically significant site and is one of the few sites in Florida that demonstrate significant paleo-Native American cultural remains that has also …

Emojis As Text Technology: Between Visual Paradigm And Cultural Revolution, Hanan Hafiz

Graduate Thesis and Dissertation post-2024

Emojis, as a broader communication phenomenon, have gained widespread usage, significant adaptation, and considerable academic attention due to their role in providing semiotic cues and online gestures within computer-mediated communication. This study aims to trace their development and evolution using the text technologies framework. This approach examines the systematic use of emojis, with particular emphasis on their extensive evolution by historically contextualizing their usage, trends, and cultural interactions. Anchored in this conceptual approach, the study draws on the taxonomy of text technology developed by Treharne and Willan, analyzing the evolution of emojis through four key dimensions: intentionality, materiality, functionality, and …

It's Been Here All Along: Increasing Discomfort In Immersive Horror Puzzle Experiences Without Jump Scares, Brittany R. Porthouse

Graduate Thesis and Dissertation post-2024

This thesis seeks to utilize horror themes in a puzzle-based themed experience without the usage of jump scares. By alerting the body’s startle response once a puzzle is completed with a sudden loud noise or visuals, many horror-themed escape rooms utilize the jump scare tactic to heighten their guests’ adrenaline. While this technique is often effective in eliciting a reaction from participants, the effects are temporary– and sometimes hinder participants’ desire to fully interact with the environment. By primarily using the experience’s narrative and environment to illicit a fear response in guests, as opposed to using the consequences of their …

Supervised Topic Modeling For Scientific Texts: Bayesian Shrinkage Methods And Domain-Specific Applications In Forensics And Online Aggression Sciences, Amir Alipour Yengejeh

Graduate Thesis and Dissertation post-2024

Topic modeling has become a powerful tool for analyzing large-scale textual corpora across scientific domains. However, traditional unsupervised approaches like Latent Dirichlet Allocation (LDA) often produce redundant or weakly informative topics, limiting their interpretability and predictive utility. This dissertation presents a dual-track study that advances the field of interpretable topic modeling and domain-specific text analysis by (1) quantitatively analyzing research trends in Cyber Aggression and Abuse (CAA), and (2) developing a supervised topic selection framework for forensic science literature.

In the first part, we apply LDA to a corpus of 2,309 journal abstracts on CAA sourced from the Web of …

Numerical Evaluation Of A Novel Transpiration Cooling Scheme For Use In Dynamic Control Of Atmospheric Entry System, Caroline J. Anderson

Graduate Thesis and Dissertation post-2024

Future space exploration missions require sustainable, efficient thermal protection systems for atmospheric entry, instead of disposable ablative shields. Transpiration cooling has interest as a long studied method but never used for missions to date, prompting further study to address concerns of flow transition downstream. In consideration of additional need for aerodynamic maneuvering for greater landing accuracy, a novel asymmetric scheme of transpiration cooling is presented as a method of using onboard coolant to meet entry trajectory maneuvering requirements. This numerical study creates a coupled model of vehicle-scale flow domain and material-scale thermal response to converge on accurate vehicle surface values.

Morphology, Evolution And Host-Driven Convergence In Ichneumonidae (Hymenoptera, Ichneumonoidea), Davide Dal Pos

Graduate Thesis and Dissertation post-2024

Understanding the functional and evolutionary significance of morphology is fundamental to interpreting the tree of life. In recent years, emerging tools have enabled broad-scale analysis of discrete morphological data and facilitated the study of entire phenomes, helping to re-establish morphology as a central component of evolutionary research. These advances allow us not only to examine individual traits in detail but also to compare them across taxa and explore their evolutionary trajectories. This approach is particularly critical when studying hyperdiverse groups that exhibit both high levels of morphological convergence and complex life cycles intricately tied to host use. A prime example …