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On The Benefits Of Directness In Virtual Characters For Motivational Interviews, Michael O'Mahony, Cathy Ennis, Robert Ross

Conference papers

Understanding the factors influencing successful engagement with Embodied Conversational Agents (ECAs) remains a significant challenge. This understanding could be used to personalise agents to users to improve interactions. Some studies have shown that simulating personalities in healthcare agents can improve effectiveness and engagement. However, it is not yet well understood how variations of agent personality can be leveraged to improve user engagement with Motivational Interviewing (MI) ECAs. Specifically how the balance between agent warmth and directness can be controlled in an MI agent to improve likeability and engagement. We conducted an online Wizard-of-Oz (WoZ) mediated study of two variants of …

Methods In Environmental Studies, Erika Dunagan, Maya Mendoza, Posey Graber, Alex Cullins, Emma Mcginnis, Ally Nepomuceno, Isabella Buchan

Featured Student Work

This publication is a collection of undergraduate research conducted in the Methods in Environmental Studies course at the University of San Francisco in Fall 2024. The student-led projects explore the intersections of place, policy, ecology, and cultural identity through applied environmental research methodologies. Topics include a decolonial examination of the Forest Park Mound Group and Indigenous resilience in St. Louis; a comparative study of Navajo cosmology and ecological justice; a social and environmental impact assessment of Costa Rica’s National Decarbonization Plan; a psychogeographical analysis of Golden Gate Park and its impact on the psyche, emotions, behaviour, and health of urban …

Software Implementations And Analyses Of The Emotional Impact Of Various Binaural Beat Classifications Layered Into Music., Neil Azimi

Student Scholar Symposium Abstracts and Posters

This study explores the psychoacoustic effects of binaural beats, which are produced when sinusoidal waves of slightly differing frequencies are played into each ear, leading to brainwave entrainment. Binaural beats are categorized by frequency bands (e.g., Beta: 14–30 Hz for energy, Theta: 4–8 Hz for relaxation), each associated with different psychological effects. This research contributes to the field by empirically analyzing whether binaural beats alter the emotional impact of music. Past studies have investigated the potential benefits of binaural beats in relaxation and energy stimulation. However, their effects, when combined with music, especially regarding a song's perceived emotional quality or …

Investigating The Efficacy Of Prompt Engineering Techniques For Research Survey Paper Generation Using Large Language Models, Innocent Obed Awidi

Theses and Dissertations

The recent advancements in large language models (LLMs), such as ChatGPT, offer promising potential for automating academic writing tasks. This study investigates the efficacy of prompt engineering techniques in guiding LLMs to generate high-quality research survey papers, specifically exploring their application in the fields of artificial intelligence (AI) in drug development and large language model customization for classification. Using a mixed-methods approach, this research assessed the impact of prompt engineering on the coherence, relevance, and overall quality of generated content through quantitative and qualitative analyses. Techniques including prompt refinement, contextual prompting, and iterative prompting were systematically applied to enhance the …

Mathematics In Amusement Parks, Kacey Laumann

Honors Projects

This project focuses specifically on the Walt Disney World Park, Magic Kingdom. I started by collecting data through the MyDisneyExperience app. By recording the data, I was then able to create polynomial functions to the fifth the degree. Each attraction received a function which allowed me to predict the wait times for that attraction. Then, by graphing the functions and analyzing the graph using calculus the “best time” and “worst time” to go to the attraction were found. After the analysis the information is used to build a unique schedule for a guest. Then the guest receives this schedule after …

Does A Name Make A Difference? Teaching Random Selection In The Classroom, Venessa Singhroy, Rommel Robertson, Kostas Stroumbakis

Numeracy

In Statistics education, it is crucial to emphasize the foundational significance of random selection, which underpins statistical methodologies and ensures unbiased representation of populations in samples. However, students often struggle to grasp the concept’s complexities, leading to challenges in applying random selection methods effectively. This paper examines the gap between students’ theoretical understanding of randomness and their practical application of this concept. Using an Explanatory Sequential Design, this study presents an instructional activity aimed at teaching the concept of randomness in the selection process and proposes modifications to enhance student comprehension. The activity, implemented in undergraduate Statistics and Psychology courses, …

The Impact Of Student Engagement Activities On Future Climate Change Adaptation: The Case Of Student Simulation Models, Bassel Mostafa Elkalaf

Future Journal of Social Science

This paper explores the critical role of student engagement in addressing the growing challenges of climate change, with a focus on the Model United Nations (MUN) as a case study. As climate-related security threats increase globally, educational platforms that prepare youth for effective leadership in climate politics are more essential than ever. MUN, a widely practiced student activity simulating global policy-making, provides a valuable opportunity for students to deepen their understanding of the interconnectedness between climate change, peace, and security. By participating in MUN simulations, students engage in debates, develop innovative solutions, and practice diplomatic skills, all while exploring the …

Ethics And Environmental Impact Of Video Games, Anushka Chokshi

ART 108: Introduction to Games Studies

As video games grow in popularity, concerns regarding their ethical and environmental implications are brought up. While once, topics like their impact on child development or harm to Earth might have been considered minor or irrelevant, these concerns are now voiced in numerous articles across the internet, amplifying the urgency to develop games in an ethical context before matters are blown out of proportion. For the purposes of exploring both past and present views, this work draws from older and newer sources surrounding many topics on the idea of game development in the video game industry. Essentially, video game development …

Toward An Insider Threat Education Platform: A Theoretical Literature Review, Haywood Gelman, John D. Hastings, David Kenley, Eleanor Loiacono

Research & Publications

Insider threats (InTs) within organizations are small in number but have a disproportionate ability to damage systems, information, and infrastructure. Existing InT research studies the problem from psychological, technical, and educational perspectives. Proposed theories include research on psychological indicators, machine learning, user behavioral log analysis, and educational methods to teach employees recognition and mitigation techniques. Because InTs are a human problem, training methods that address InT detection from a behavioral perspective are critical. While numerous technological and psychological theories exist on detection, prevention, and mitigation, few training methods prioritize psychological indicators. This literature review studied peer-reviewed, InT research organized by …

Everyone Brings Something To The Table: A Culturally Sustaining Analysis Of Teacher Candidates’ Mixed Reality Teaching Simulations, Erin Scott

Faculty Publications

Discussions of HBCU students’ content knowledge have centered around developing high impact, asset-based approaches to learning (Williams et al, 2022). So, HBCU teacher preparation providers (TPPs) can also focus efforts on culturally sustaining approaches to developing candidates’ content knowledge and researching how high impact practices, like teaching simulations, can help prepare candidates for classrooms. This exploratory case study uses critical cases (n=2); findings suggest candidates have a developing understanding of content, which forms a solid basis for increasing their knowledge. MRTSs are addressed as a potential high impact, culturally sustaining practice for building candidates’ content knowledge. Further, HBCU TPPs can …

The Effects Of Negative Feedback On Cognitive And Behavior Performance Related To Self-Efficacy, Elizabeth Ann Godfrey, Karly Kammann, Mattie Harvey, Rayna Cruickshanks

Science University Research Symposium (SURS)

Feedback is information or guidance in response to a behavior, action, or result. Feedback is a method for improvement and is a tool commonly used by professors, coaches, and bosses. Existing literature suggests that feedback can elicit emotional responses affecting attitudes and behaviors across contexts. Negative feedback specifically is understudied with variable findings; some literature suggests negative feedback is dismissed while other studies suggest that it may enhance performance. Similar inconclusive findings exist when examining ability-based and effort-based feedback. One factor that may play a role in the response to feedback is self-efficacy. Self-efficacy contributes to emotional reactions and thoughts …

Real-Time Motion Augmentation And Synthesis For Animating The Hands And Eyes Of Virtual Humans And Avatars, Ryan Canales

All Dissertations

Virtual Reality (VR) enables users to interact within virtual worlds via an embodied virtual representation of themselves called an “avatar”. Because avatars are essential for immersive experiences, it is important to consider how altering or augmenting avatar motion affects virtual experiences. This dissertation aims to improve virtual experiences by addressing some of the many challenges in animating avatars and virtual humans.

In our first study, we addressed the lack of tactile feedback during virtual grasping by using visual feedback techniques. We augmented the avatar’s hand motion to remain outside virtual objects (“outer hand”) even when the user’s hand penetrated them. …

About The Mcnair Scholars Program, The Mcnair Team

McNair Scholars Research Journal

No abstract provided.

Investing The Therapeutic Possibilities Of Glassblowing, Isabella Posca

McNair Scholars Research Journal

No abstract provided.

A Machine Learning Approach To Multifactorial Modeling Of Episodic Memory Performance, Evan Fletcher, Marianne Chanti-Ketterl, Emily Hokett, Yi Lor, Umesh Venkatesan, Paola Gilsanz, Rachel Whitmer, Ruijia Chen, Kristen George, Zvinka Zlatar

Moss-Magee Rehabilitation Papers

BACKGROUND: Neurocognitive health is influenced by multiple modifiable and non-modifiable lifestyle factors. Machine learning tools offer a promising approach to better understand complex models of cognitive function. We used extreme gradient boosting (XG Boost), an algorithm of decision-tree modeling, to analyze the association between 15 late-life lifestyle and demographic factors with episodic memory performance. METHOD: Our dataset consisted of 2247 participants from the KHANDLE and STAR cohorts. Participants included 841 men and 1406 women, an ethnoracial diversity of 413 Asian, 987 Black, 349 Latinx, and 496 White adults with age range 54-90 (mean = 74). XG Boost models of continuous …

Reducing Token Redundancy In Video-Language Models Via Memory Consolidation Algorithm, Matt Couts

Electrical Engineering and Computer Science Undergraduate Honors Theses

Video Question Answering (VideoQA) focuses on developing mod- els capable of engaging in natural language conversations about video con- tent. Current state-of-the-art typically analyze videos frame-by-frame, a process that is both computationally and memory-intensive. Integrating the Atkinson-Shiffrin memory model with Video Language Models has demon- strated potential for enhancing video understanding capabilities. Reducing the number of frames processed by the model is a crucial operation in this approach, which is achieved by a memory consolidation algorithm. This al- gorithm condenses a video sequence into a small set of representative frames which capture the essence of the video content. However, due …

Resting-State Brain Activity And Its Relationship To Mental Health In Epilepsy Using Fmri, Florian Gobellan Rodriguez

McNair Scholars Research Journal

No abstract provided.

Letter From The Vice President For Research And Innovation, The Mcnair Team

McNair Scholars Research Journal

No abstract provided.

The Algorithm Of Fear: Unpacking Prejudice Against Ai And The Mistrust Of Technology, James Hutson, Daniel Plate

Faculty Scholarship

The mistrust of AI seen in the media, industry and education reflects deep-seated cultural anxieties, often comparable to societal prejudices like racism and sexism. Throughout history, literature and media have portrayed machines as antagonists, amplifying fears of technological obsolescence and identity loss. Despite the recent remarkable advancements in AI—particularly in creative and decision-making capacities—human resistance to its adoption persists, rooted in a combination of technophobia, algorithm aversion, and cultural narratives of dystopia. This review investigates the origins of this prejudice, focusing on the parallels between current attitudes toward AI and historical resistance to new technologies. Drawing on examples from popular …

Concert Tickets, Party Matching, Sleeping Barbers, And Single Lane Bridges: Characterizing Student Reasoning About Concurrency, Aubrey Lawson

All Dissertations

Programming with concurrency is challenging both to learn and to teach. A concurrent program has multiple computations happening “at the same time” either simultaneously or in an interleaved manner. It is non-deterministic, imposing only a partial ordering on its decomposed parts. Advantages of concurrency include the potential for increased program throughput, high responsiveness and reduced complexity of program structure. But a concurrent program can be more complex to reason about than a sequential program, in part because the conditions of correctness must hold for all possible execution sequences and also because programmers must implement and reason about synchronization constructs that …

Full Issue, The Mcnair Team

McNair Scholars Research Journal

No abstract provided.

Constructing Qur’An Recitation Classification Using Alexnet Algorithm, Harits Ar Rosyid, Dzulkifli Abdullah, Mohammed S. Alqahtani

Knowledge Engineering and Data Science

The growing demands for accurate and efficient methods in the Qur'an recitation classification highlight the limitations of existing models, particularly in assisting the memorization process. This study aims to address these challenges by implementing the AlexNet Convolutional Neural Network architecture, widely recognized for its effectiveness in image classification, to classify the Qur'an recitations using the Mel Frequency Cepstral Coefficient (MFCC) as the feature extraction method. The research involves several stages, including data collection, preprocessing (audio segmentation by verse), data augmentation, feature extraction, and classification using the AlexNet architecture, followed by performance evaluation. Key results demonstrate that the combination of MFCC …

User Acceptance Of Advice By Ai Agents: Expectation-System Fit Perspective, Jingyuan Cai, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

Algorithms have increasing influence on our daily decisions, especially when the recommendations are presented by human-like AI agents. This study applies the Theory of Effective Use to investigate how the fit between the user’s role expectation for an AI agent and the agent’s interaction style impacts AI advice adoption. We proposed a new concept termed Perceived Expectation-System Fit (PESF) and empirically examined its impact on user perceptions and advice acceptance. We found that low PESF reduces advice acceptance by diminishing cognitive and affective trust in the AI agent. Furthermore, increased algorithm transparency increases PESF's impact on decision-making. Our findings provide …

Enhancing Password Security And Memorability Using Machine Learning And Linguistic Patterns, Jared Wise

LSU New Orleans Theses and Dissertations

In the digital age, text-based passwords remain a primary method for securing online accounts. Yet, users frequently face a dilemma between creating passwords that are easy to remember and sufficiently secure against cyberattacks. This research introduces an approach to password generation that bridges this gap by utilizing linguistic patterns, particularly song lyrics, to develop highly secure and naturally memorable passwords. Using large lyric datasets gained from web scrapes from popular song lyric websites (AZ Lyrics, Genius), features are extracted from a corpus of over 5 million lyrics using sentence structure and natural language processing in a novel way. In using …

Where And How Are Undergraduate Students Developing Dispositions Needed For The Geoscience Workforce?, Kaelyn Lagerwall

Boise State University Theses and Dissertations

Dispositions, such as the desire to learn, work ethic, initiative, and organization, are defined as internal attributes, attitudes, or values that stimulate action. Rather than being intrinsic traits, dispositions can be learned and are considered a dynamic and evolving arrangement of interconnected components. Dispositions are highly desired and valuable to the workforce, playing a critical role in gaining and maintaining employment; they are frequently mentioned in job advertisements for bachelor-level geoscientists. Therefore, it is important to understand where and how geoscience students are developing these dispositions as part of their degree programs. We surveyed faculty in geoscience departments at two …

Front Matter

The Synapse: Intercollegiate science magazine

No abstract provided.

Leveraging Ai Tools In University Writing Instruction: Enhancing Student Success While Upholding Academic Integrity, Daisuke Akiba, Rebecca Garte

Publications and Research

The emergence of AI-powered Large Language Models (LLMs), such as ChatGPT and Google Gemini, presents both opportunities and challenges for higher education, particularly regarding academic integrity in writing instruction. This exploratory study examines a novel pedagogical approach that integrates LLMs as required feedback tools in a university-level psychology writing assignment. The exclusive online approach emphasizes improvement through revision, requiring students to obtain AI-generated feedback on ungraded initial drafts based on an instructor-provided rubric, with final assessment focused on the quality of subsequent revisions. Analysis of survey data from 39 undergraduate students, incorporating both quantitative measures and qualitative responses, revealed several …

A Community-Driven Framework To Evaluate Factors Influencing Nft Buyers, Yi Meng Lau, Ping Fan Ke

Research Collection School Of Computing and Information Systems

This study examines the pivotal role of community-driven social dynamics in shaping non-fungible tokens (NFT) buyers’ purchasing intentions and the increasing social significance of digital assets. Building on prior research in online word-of-mouth, we propose a comprehensive framework that integrates technological, personal, social, economic, and political factors influencing NFT purchases. The framework emphasizes the importance of service providers, personalization, perceived value, and associated risks, while also providing insights into how online word-of-mouth and community dynamics impact these aspects. As a preliminary exploration, this research lays the foundation for future empirical studies to validate the framework and assess its applicability across …

A Strategic Insight Into The Market For Carbon Management Capacity, Mahelet G. Fikru, Ting Shen, Jennifer Brodmann, Hongyan Ma

Economics Faculty Research & Creative Works

This study presents the market for carbon management capacity via carbon capture, utilization, and storage technologies, identifying demand and supply forces, as well as clarifying the potential impact of market and non-market-based shocks on technology developers versus adopters. The paper addresses a prevailing gap in market analysis, introducing a microeconomic framework and unique dataset to identify key players, market forces, and policy incentives shaping the carbon capture, utilization, and storage landscape. The analysis equips industry stakeholders, policymakers, and investors with valuable insights regarding (1) leaders in the design, development, and manufacture of carbon capture, utilization, and storage technologies (supply), (2) …

Community Co-Production Of The Meaning Of Local Climate Resilience And Action: A Case Study, Michele Romolini, Mary Hillemeier, Dustin L. Herrmann

Center for Urban Resilience Scholarship

In the face of a rapidly urbanizing and warming planet, there is urgency for local governments to develop community resilience strategies. Successful climate change adaptation will likely require the inclusion of local knowledge, especially from historically marginalized communities. One pathway for this is through research projects and government planning activities that employ processes of co-production to generate actionable knowledge relevant to the community. This paper describes the approach, results, and reflections of a multi-sectoral partnership organized to engage residents of a small municipality to co-produce the meaning of community climate resilience, through methods including individual interviews, cognitive mapping, and a …