Digital Commons Network^™

Rethinking Climate Change Education: Wyoming And New Jersey As Effective Models Of Climate Change In Education Standards, Jamie W. Miller

Pitzer Senior Theses

Education is an essential and oft-overlooked part of the conversation about climate change. As I’ll demonstrate in this thesis, education shapes how the public understands climate change and creates environmental knowledge, attitudes, behaviors, and intentions. Exploring and understanding climate change education allows us to understand how people form perspectives about climate issues. This topic is extremely important, but one we often gloss over when thinking about climate solutions. I analyzed three case studies of educational standards in the United States to understand how political context, writing focuses, and benchmarks impact the efficacy of climate change standards. My research found that …

Geoscience Mathematics Self-Efficacy Scale (Geomses) For Majors-Level Undergraduates: Psychometric Data, Michael Coe, Rory Mcfadden, Beth Pratt-Sitaula, Eric Baer

Science Education Resource Center (SERC)

Self-efficacy is often investigated as a key attitudinal component of academic persistence and performance, and self-efficacy surveys can serve in research models as efficient and non-threatening assessment tools to augment or substitute for achievement or performance measures. The Geoscience Mathematics Self-Efficacy Scale (GeoMSES) builds on prior work in measurement of self-efficacy for mathematics by focusing specifically on students’ capacity to apply mathematical skills to typical problems encountered in majors-level undergraduate geoscience courses or in professional geoscience settings. The scale was developed as part of program evaluation research for a set of learning modules designed to augment existing geoscience curricula. In …

Toward Conditions For Consensus Of Noisy Bounded-Confidence Models, Madeline Reeve

HMC Senior Theses

Models of opinion dynamics aim to describe the spread of opinions over time in a social network. However, many canonical models are deterministic and thus may fail to capture uncertainty present in social interactions. This work investigates the effect of adding noise into bounded-confidence models, a class of opinion dynamics models where agents are more likely to be influenced by opinions close to their own. In particular, we propose a noisy modification of the Deffuant–Weisbuch bounded-confidence model. We prove that in this model all agents eventually adopt the same opinion—that is, our model converges to consensus. In doing so, we …

A Macrocognitive Design Taxonomy For Simulation-Based Training Systems: Bridging Cognitive Theory And Human-Computer Interaction, Jessica M. Johnson

Virginia Digital Maritime Center (VDMC) Faculty Publications

Simulation-based training systems are increasingly deployed to prepare learners for complex, safety-critical, and dynamic work environments. While advances in computing have enabled immersive and data-rich simulations, many systems remain optimized for procedural accuracy and surface-level task performance rather than the macrocognitive processes that underpin adaptive expertise. Macrocognition encompasses higher-order cognitive processes that are essential for performance transfer beyond controlled training conditions. When these processes are insufficiently supported, training systems risk fostering brittle strategies and negative training effects. This paper introduces a macrocognitive design taxonomy for simulation-based training systems derived from a large-scale meta-analysis examining the transfer of macrocognitive skills from …

Computational Clinical Judgment: Predicting Risk With Large Language Models, Hannah Laqueur, Ryan W. Copus

Faculty Works

For seventy years, research has shown actuarial methods outperform clinical judgment. Yet actuarial approaches have limitations: they generally rely on structured data; cannot exploit rare case-specific details; have limited accuracy where outcome data are scarce or incomplete; and cannot offer case-level justifications. Large language models (LLMs) offer a different approach. Like actuarial methods, they aggregate information algorithmically, but like clinicians, they bring general knowledge and can provide case-level justifications. We prompted seven LLMs to assess rearrest risk from 113 parole hearing transcripts and compared their predictions to a machine learning model trained on 4,000 cases with 91 administrative variables. GPT-5 …

Planaria Dugesia Japonica As A Model Organism For Measuring The Toxicity Of Environmental Contaminants Per- And Poly-Fluoroalkyl Substances (Pfas), Caitlyn Rodeo

Behavioral Neuroscience Honors Papers

A group of synthetic chemicals, per- and poly-fluoroalkyl substances (PFAS) are ubiquitous in the environment and have significant detrimental effects on physiology and behavior. Planaria have recently increased in popularity as a model for toxicology and regeneration research. These organisms possess a primitive centralized nervous system that is thought to be more similar to the vertebrate brain than to other invertebrate brains in terms of structure and function, and possesses the same neuronal subpopulations and neurotransmitters as the mammalian brain. While other studies have investigated the behavioral effects of perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) on planaria, there is …

Closing The Loop In Sustainable Fashion: Recycling Textile Waste And Its Environmental, Social, And Consumer Impacts, Anthony Amotoe-Bondzie

Sustainability Program Posters and Papers

Fast fashion has intensified textile waste, emissions, and social inequities across global supply chains. This study examines sustainable fashion frameworks and the role of textile recycling in advancing circularity. It employes a qualitative integrative literature review synthesizing interdisciplinary research on waste streams, recycling technologies, policy instruments, and consumer behavior. However, advanced recycling technologies offer environmental benefits but remain limited in scale. Nonetheless, rising consumption offsets efficiency gains, while economic and behavioral barriers hinder systemic change. Technological innovation alone is insufficient; circular design, regulatory enforcement, and reduced overproduction are essential for sustainable transformation.

Do Algorithms Dream Of Electric Muses? Teaching Creative Writing In The Age Of Generative Ai, Anna Leahy

English Faculty Articles and Research

In Philip K. Dick’s novel Do Androids Dream of Electric Sheep? androids are given a psychological test to confirm they are not human before killing them. The story’s end suggests that humans will treat a seemingly harmless android as authentically as a human even when humans are aware the android is not human. Students use tools like ChatGPT, which function as autocomplete on steroids, to produce text using probabilistic relationships among words, and instructors can’t always tell the difference between average student writing and Gen AI text. In creative writing classes, instructors might use thinking for oneself as a central …

Ai In The Workplace: Understanding Role Ambiguity, Employee Motivation, And Learning Engagement, Sheena Leah Metzger

Theses, Dissertations and Capstones

The rapid integration of artificial intelligence (AI) into organizational processes has altered how work is performed and experienced by employees, yet empirical research examining the human implications of AI-driven change remains limited. This study examined the perceived impact of AI implementation on role ambiguity, employee motivation, and training engagement, and investigated the moderating role of perceived organizational support (POS). Grounded in Job Demands–Resources (JD-R) Theory and Organizational Support Theory (OST), the research examined how employees interpreted and responded to AI-related changes in their work environment.

The results offer valuable insights into a shifting perception of how employees experience technology in …

Environmental Sustainability Performance And Efficiency In Thailand’S Rajabhat Universities : A Cross-Regional Analysis Of The Impact Rankings, Konstantinos Balis

Applied Environmental Research

Higher education institutions (HEIs) are expected to increasingly communicate their contributions to the United Nations’ Sustainable Development Goals (SDGs), with the rise of alternative sustainability rankings serving as prominent reporting instruments for institutional transparency. In Thailand, Rajabhat Universities, a network of government HEIs historically associated with their mission of teacher training and local development, have been actively participating in the Times Higher Education (THE) Impact Rankings, presenting a unique case study to explore cross-regional sustainability efforts in relation to global benchmarks. To evaluate trends, regional disparities, and engagement performance across the sustainability pillars, this study uses a descriptive quantitative design …

Investigating The Viability Of Fully Online Asynchronous Physics Instruction In Formal Education, Clifton W. Massey-Noel

Physics Dissertations

In this dissertation we present results from two consecutive investigations into the fully online asynchronous modality in Physics Education. We first discuss the efficacy of a fully online asynchronous section of Modern Physics held in Fall 2024. The asynchronous section is compared with four prior partially-flipped sections of the same class, two of which were held in-person, and two of which were held synchronously online. Results suggest that all three modalities can be made to be about equally as effective. We also discuss the efficacy of a fully online asynchronous section of Calculus-Based Introductory Mechanics held in Fall 2025. The …

A Data-Driven Framework For Automation Readiness In Minnesota State University, Mankato Course Scheduling, Prisca Bongu Payanzo Maba

All Graduate Theses, Dissertations, and Other Capstone Projects

University course scheduling is one of the most complex optimization problems in higher education institutions. With universities growing in size and offering a broad spectrum of majors and disciplines, the number of possible course scheduling combinations increases exponentially, rendering traditional ways of scheduling ineffective.

Although operations research has extensively studied automated scheduling algorithms, there has been limited investigations into the organization readiness of academic departments to implement such systems. This paper offers a hybrid data science framework that assesses departmental readiness for scheduling automation.

The study combines qualitative Zoom interview data from 19 academic departments with institutional scheduling rules from …

Fluid Agency In Ai Systems: A Case For Functional Equivalence In Copyright, Patent, And Tort, Anirban Mukherjee, Hannah H. Chang

Research Collection Lee Kong Chian School Of Business

Modern Artificial Intelligence (AI) systems exhibit fluid agency in multi-step workflows: lacking human-like consciousness or culpability, yet they display behavior that is (i) stochastic (probabilistic and path‑dependent), (ii) dynamic (co‑evolving with user interaction), and (iii) adaptive (able to reorient across contexts). These properties generate valuable outputs but collapse attribution, irreducibly entangling human and machine inputs. Doctrines that assume traceable provenance—authorship, inventorship, and liability—fracture under this unmappability, yielding ownership gaps and moral “crumple zones.”This Article argues that only functional equivalence stabilizes doctrine under unmappability: Where provenance is indeterminate, legal frameworks should treat human and AI contributions as equivalent for allocating rights …

Designing An Approach To Developing Students' Symbol Sense For The Derivative In Calculus, Laura E. Weinstein

Theses, Dissertations and Culminating Projects

Students often struggle to connect the conceptual meaning of the derivative with the symbolic structures of Leibniz (dy/dx) notation. Although symbol sense has been described as the coordination of mathematical concepts, signs, and objects, little is known about how instruction can purposefully support students in developing symbol sense for the derivative. This study addresses this gap by designing and examining a learning approach aimed at helping students construct the relational structures underlying derivative notation. Using design research methodology, the study engaged intact algebra, precalculus and calculus classes in a suburban New Jersey high school across iterative cycles of design, implementation, …

Operationalizing Cyber-Routine Activities Theory For Senior Cybercrime Prevention: An Evaluation Of The Shield Training-The-Trainer Program, Kyung-Shick Choi, Insun Park, Mijin Kim, Ji Yae Bong

International Journal of Cybersecurity Intelligence & Cybercrime

Older adults face growing risks of cyber-enabled fraud, yet scalable, evidence-based prevention programs remain limited. Guided by Cyber-Routine Activities Theory (Cyber-RAT), this study evaluates the pilot implementation of the Seniors Harnessing Internet Education for Lasting Defense (SHIELD) Training-the-Trainer program, designed to prepare law enforcement officers and community leaders to deliver cybercrime prevention education to older adults. A key innovation of SHIELD is its integration of interactive game-based simulations, which allow participants to practice verification, refusal, and reporting behaviors in realistic cybercrime scenarios. Following the December 2025 pilot session in Boston, semi-structured interviews were conducted with 12 participants from law enforcement, …

Serum Biomarker Trajectory Clusters Predict Functional Outcome And Quality Of Life For Traumatic Brain Injury, Thanh Son Do, Chantal Carnes, Zhihui Yang, Firas Kobeissy, Hamad Yadikar, Gayla R. Olbricht, Olli Tenovuo, Jussi P. Posti, Ewout W. Steyerberg, Lindsay Wilson, Nicole Von Steinbüchel, Endre Czeiter, Andras Buki, David K. Menon

Mathematics and Statistics Faculty Research & Creative Works

Serum brain-enriched biomarkers are increasingly employed in the clinical evaluation of traumatic brain injury (TBI) to assist with triage, neuroimaging decisions, and prognostication. However, the potential of temporal biomarker trajectories to inform disease monitoring and long-term outcomes remains underexplored. We aim to identify distinct biomarker trajectory (TRAJ) profiles in traumatic brain injury patients and to examine their associations with long-term clinical outcomes. The study included 373, CT-positive Intensive Care Unit (ICU) traumatic brain injury patients (256 with initial Glasgow Coma Scale 3–12) from the Collaborative European Neurotrauma Effectiveness Research in TBI (CENTER-TBI) core study who had at least two serum …

Beyond Fixed Thresholds: Per-Label Calibration For Fine-Grained Emotion Detection On The Goemotions Dataset, Sai Puneet Naga Venkata Subramanyam Patchipulusu

Selected Full-Text Master Theses 2021-

This study investigates the effectiveness of five community fine-tuned transformer models for fine-grained emotion detection on the GoEmotions dataset: SamLowe/roberta- base-go_emotions (RoBERTa-base), cirimus/modernbert-base-go-emotions (ModernBERT), mrm8488/deberta-v3-base-goemotions (DeBERTa-v3-base), bhadresh-savani/bert-base-go- emotion (BERT-base-cased),and tasinhoque/distilbert-go-emotions (DistilBERT) . While the original GoEmotions research by Demszky et al. (2020) established a BERT-base baseline with a macro-F1 of 0.46, this thesis extends that work through independent empirical evaluation of five derivative models, systematic per-label threshold optimization, and comparative analysis of architectural trade-offs across the full transformer model family. Using the GoEmotions simplified test split (5,427 examples across 28 categories), all five models were evaluated at a fixed 0.5 …

Creating A University-Based Accessible Makerspace For Use By Local Community Members Through Participatory Design Workshops, Erin Higgins, John J. Magee Iv, Foad Hamidi

Computer Science

While Do-It-Yourself Assistive Technology (DIY-AT) has been shown to provide needed AT for individuals who might not otherwise have access, the makerspaces utilized to create these technologies have proven to be inaccessible. A promising direction for creating accessible makerspaces is to utilize participatory methods to develop new spaces for use by a diverse community of individuals. We explored these possibilities through participatory design workshops focused on building a new accessible community makerspace situated within a university campus setting. Through these workshops, we found that there are unique physical, technical, and human supports needed to create an accessible space for the …

Investigating Ui Based And Ai Based Interactions In Vr Environments For Human Anatomy Education, Siddharth Sondhi

Master's Projects

Traditional approaches to learning and simulation often struggle to convey the complexity of three dimensional structures. In anatomy education, methods such as textbooks, lectures, and cadaver based learning are used, but can make it difficult to understand the complex structure of organs within the human body. Virtual Reality (VR) offers a promising alternative by providing immersive and interactive 3D environments that allow users to explore and manipulate anatomical structures more intuitively. These environments can be further enhanced by integrating large language models (LLMs) as intelligent agents capable of guiding users through natural language interaction. This project presents a Unity-based VR …

Emotional Patterns In Conversational Social Media Using Graph-Based Context, Sai Sanjay Yerunkar

Master's Projects

Most social media datasets for emotion detection have not been constructed to account for conversational structure‚ so we investigate whether it carries signal for emotion prediction. Using Sentiment140 and GoEmotions Reddit threads‚ we construct their thread-based conversation graphs and compute the aggregated features of neighbors as well as the transformer and TF-IDF representations of comments. Connected comments are 4.5× more similar in emotions than expected by chance. Pairwise emotional similarity decays exponentially with geodesic distance (e.g.‚ after 2 hops). Pairs separated by a 30s timestamp difference have the highest emotional similarity. These results suggest that emotion is structured locally and …

Reinforce Trustworthiness In Multimodal Emotional Support System, Huy M. Le, Dat Tien Nguyen, Ngan T. T. Vo, Tuan D. Q. Nguyen, Nguyen Le Binh, Duy Minh Ho Nguyen, Daniel Sonntag, Lizi Liao, Binh T. Nguyen

Research Collection School Of Computing and Information Systems

In today's world, emotional support is increasingly essential, yet it remains challenging for both those seeking help and those offering it. Multimodal approaches to emotional support show great promise by integrating diverse data sources to provide empathetic, contextually relevant responses, fostering more effective interactions. However, current methods have notable limitations, often relying solely on text or converting other data types into text, or providing emotion recognition only, thus overlooking the full potential of multimodal inputs. Moreover, many studies prioritize response generation without accurately identifying critical emotional support elements or ensuring the reliability of outputs. To overcome these issues, we introduce …

Artem: Enhancing Large Language Model Agents With Spatial-Temporal Episodic Memory, Cassandra Hui Ming Tan, Budhitama Subagdja, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Current large language models (LLMs) exhibit significant deficiencies in episodic memory tasks including encoding, storing, and retrieving specific information from temporally dependent events over a long period of time. Recent approaches to handle memory tasks in LLMs, such as in-context learning, retrieval-augmented generation (RAG), and fine-tuning, may resolve the long-term retention issues, but are still inadequate to handle tasks requiring chronological awareness of the stored information. We introduce Agentic Retrieval with Temporal-Episodic Memory (ARTEM), a hybrid LLM-based agent architecture integrating LLMs with a self-organizing neural network named Spatial-Temporal Episodic Memory (STEM), designed to handle episodic memory tasks. Our approach employs …

Predicting Criminal Behavior In Major Us Cities, Madison A. Price

SPARK Symposium Presentations

In recent years, especially post pandemic, there has been a decrease in crime in the United States. Unfortunately, the country’s violent crime rates are still significantly higher compared to similar high-income countries, so what predicts crime in major American cities? There is tons of research to support the idea that demographics can offer some insight into predicting crime. There are countless online resources that seek to identify major crime centrals in the United States (Petrino, 2025). In the late 1990s, researchers noticed that crime rates in cities had a downward slope due to an important contributor: demographic change (Fox & …

Students' Perception Of Generative Ai-Assisted Collaborative Argumentation, Jinhee Kim, Seongryeong Yu, Rita Detrick, Liangjie Fan, Na Li

STEMPS Faculty Publications

The rapid scaling of generative artificial intelligence (GenAI) technology presents opportunities for personalised learning experiences and facilitates collaborative learning, including collaborative argumentation (CA). However, empirical research examining students' perceptions of GenAI-assisted CA within classroom contexts remains limited. This study explored university students' experiences with GenAI-assisted CA through in-depth interviews with 36 students following a CA activity using a ChatGPT4-embedded argumentation platform developed by the research team. Findings indicate that students viewed GenAI as serving multiple roles, including tool, facilitator, teaching assistant and machine buddy. Students perceived that GenAI-assisted CA could empower task performance and create a collaborative learning environment. Meanwhile, …

Artificial Intelligence And Consumer Well-Being: A Cross Domain Systemic Review, Setar Lytle, Mahesh Gopinath

Marketing Faculty Publications

Artificial intelligence (AI) is increasingly embedded in everyday consumption, yet evidence on its longer-term implications for consumer eudaimonic well-being remains dispersed across disciplines and application contexts. This review integrates that literature to clarify the domains, theoretical explanations, and conditions through which AI shapes consumer well-being. Following PRISMA and SPAR-4-SLR procedures, we reviewed research published from January 2010 to January 2026. From 6058 records, 480 studies across psychology, business, and human-technology interaction met the inclusion criteria. The evidence is organised through psychological, social, and technological perspectives and identifies six interconnected domains: mental health, cognitive development, physical health, personal growth, autonomy and …

Ideational Behavior And Occupational Identity Achievement: A Study Of Emerging Adult College Students Preceding Entry Into The Fouth Industrial Revolution Workforce, Carrington M. Faulk, Michael F. Kosloski, Philip Reed

Marketing Faculty Publications

As emerging adults transition into the Fourth Industrial Revolution (4IR) workforce, it is essential to understand the factors that predict successful occupational identity achievement, as automation will impact human occupational identity crises. This descriptive cross-sectional study employed a correlational design to determine the degree to which ideational behavior predicts occupational identity achievement prior to entry into the 4IR workforce. Using a sample of 166 emerging adult college students from a Mid-Atlantic, diverse, four-year university, data were collected using Runco's Ideational Behavior Scale (RIBS) and Melgosa's Occupational Identity Achievement subscale (OIA). Results showed that ideational behavior significantly predicted occupational identity achievement …

Math Anxiety, Math Self-Concept And Math Self-Efficacy: A Study Of The Jingle-Jangle Fallacies, Marsha Natasha Durrant-Walker

Dissertations

Problem

The overlap and lack of clear distinction among the constructs of math anxiety, math self-concept, and math self-efficacy presents issues for research and practice. The literature reveals that math anxiety is closely linked to math self-concept (Klee et al., 2022). Additionally, math self-concept and math self-efficacy often overlap and are not easily distinguishable (Kranzler & Pajares, 1997; Pajares & Miller, 1994; Pajares & Urdan, 1996). Each of these constructs has been shown to play a critical role in student math achievement (Timmerman et al., 2016). -- When constructs are not defined or measured distinctly, inconsistencies may emerge in research …

How Candidates Campaign To Sway Minority Voter Bases, Katelyn Karwick

Senior Honors Theses and Projects

Religious groups in the United States are making large partisan switches–decades-long Democrats are questioning their support and often change their vote to another party. This phenomenon contributed to Michigan’s flip to Republican in the 2024 presidential election, as well as divided Jewish support for New York City mayoral candidate Zohran Mamdani. Past research has linked a positive correlation between religious participation and political mobilization, though the tactics used by campaigners to create this connection have gone under research. Looking at Donald Trump’s victory in Dearborn, Michigan in 2024 and Zohran Mamdani’s extensive New York City mayoral campaign, this study focuses …

Using Provided Guided Notes In Coordinated Introductory First-Year Mathematics Courses, Jennifer L. Huber

Mathematics Dissertations

The goal of this study is to investigate how standardized guided notes shape instructional practices and student engagement in coordinated introductory first-year college mathematics courses at a large public university. The researcher explored three multi-section introductory mathematics courses with overlapping learning objectives. Each course required students to purchase a student workbook as part of the instructional materials for the class. The instructors taught primarily from the workbook containing guided notes created by a former coordinator of the course. The researcher used a mixed-methods approach. Instructors and students participated in surveys, class observations and provided class meeting notes. Instructors shared additional …

Simulating Social Attitudes With Llms: Accuracy, Demographic Effects, And Refusal Behavior In The Sensitive Domain Of Suicide Prevention, Cristina J. Perez, Michael P. Vasquez Jr., Philippe J. Giabbanelli, Patrick Y. Wu

VMASC Publications

Large language models (LLMs) are increasingly used to simulate public opinion, yet their validity in sensitive policy domains remains underexplored. We evaluate whether LLMs can reproduce attitudes toward suicide prevention policies using 32 questions drawn from seven nationally representative U.S. surveys (2023-2025). We systematically vary demographic conditioning (race/ethnicity, gender, age, education, income, party), prompt framing (direct elicitation, respondent embodiment, specialist embodiment), and model architecture (GPT-5 Nano, DeepSeek V3.2, Meta Llama 3.1 8B, Mistral Small 24B). Across 811,560 prompts, the mean absolute error—the average gap between predicted and human response distributions—is 23 percentage points. We also find that LLM responses to …