Digital Commons Network^™

Sustainable Consumer Behavior Modeling: A Complex-Systems Approach To Neuromarketing, Preethi Nanjundan, Nupoor Sanjay Bhute, Ragini Topre, Lijo Thomas

Northeast Journal of Complex Systems (NEJCS)

This study examines the application of complex-systems modeling to neuromarketing data for gaining deeper insights into the mechanisms underlying sustainable consumer behavior. It investigates how neural and biometric responses, interpreted through a systems-based perspective, can uncover dynamic interactions, feedback mechanisms, and emergent behavioral patterns influencing sustainable purchase decisions. The research explores the impact of sustainability-oriented marketing stimuli on long-term behavioral intentions by emphasizing the interconnected roles of cognitive processing, emotional engagement, implicit associations, and collective consumer dynamics. Through simulation-based modeling and structural analysis, the study demonstrates how subconscious neural responses and affective mechanisms mediate the relationship between marketing interventions, consumer …

Differentiating And Accommodating Ocd And Anxiety In Mathematical Contexts, Madeline F. Gavares

Interdivisional Studies Summer Fellows

Students in mathematics classrooms may experience emotional and cognitive challenges that affect how they engage with coursework and assessments. While math anxiety has been widely documented, less attention has been given to how obsessive-compulsive disorder (OCD), particularly checking behaviors, may influence students’ experiences in math settings. This study explores how students who report math anxiety and those who report OCD symptoms describe their engagement with math tasks and test-taking. Drawing on survey and interview data from students and teachers, this study examines how these experiences are articulated and perceived in academic math contexts, rather than evaluating ability or outcomes. By …

Faith-Informed Instruction In Secondary Mathematics: A Hermeneutic Phenomenological Study Of Lutheran Church–Missouri Synod Teachers, Jonathan Balsman

Doctoral Dissertations and Projects

The purpose of this hermeneutic phenomenological study was to understand the phenomenon of faith-informed instruction as experienced by secondary mathematics teachers in Lutheran Church–Missouri Synod (LCMS) schools in the United States. The theory guiding this study was Vygotsky’s theory of social constructivism, which frames educators’ instructional and theological meaning-making as socially and contextually developed through collaborative, relational learning environments. The central research question guiding this study was: What are the lived experiences of LCMS secondary mathematics teachers as they practice faith-informed instruction? This study used a hermeneutic phenomenological design to interpret teacher meaning-making and reflective practice. Participants were selected using …

Ai-Powered Knowledge Engines As Research Infrastructure For Systematic Knowledge Discovery, Gary Welz

Publications and Research

This paper proposes knowledge engines as a framework for understanding how intelligent systems — both human and artificial — systematically discover, integrate, and generate knowledge. We argue that history’s greatest scientific minds functioned as knowledge engines, processing information through iterative cycles of ingestion, analysis, synthesis, and communication, guided by curiosity and willingness to challenge established beliefs.

We propose a taxonomy of nine integrated capabilities — ingestion, digestion, analysis, calculation, comparison, connection, association, analogy, and multimodal communication — that any serious knowledge engine must combine systematically. The argument is deliberately integrative: achieving ambitious research goals requires orchestrating all nine capabilities within …

Can An Ai System Be Creative? A Critical Perspective From Art And Engineering, Ivan Magrin-Chagnolleau

Presidential Fellows Articles and Research

This paper examines the question of whether artificial intelligence (AI) systems can be creative, approached from the dual perspective of a researcher trained in electrical engineering, pattern recognition, machine learning, and neural networks, who has also spent most of his life engaged in the arts as actor, stage and film director, writer, composer, and visual artist, and in philosophy. Drawing on Margaret Boden’s foundational framework — both her three properties of creativity (novelty, surprise, and value) and her three types of creative processes (combinatorial, exploratory, and transformational) — the paper argues that AI systems are structurally incapable of creativity in …

Continuous 1:1 Sitter Observation Versus Standard Safety Interventions To Reduce Falls In Hospitalized Adults At Risk, Zainab Williams

Student Scholarly Projects

Practice Problem: Patient falls remain a significant patient safety concern among hospitalized adults, particularly those at high risk. Traditional fall-prevention strategies, including continuous 1:1 sitter observation, require evaluation to determine their effectiveness in reducing falls and fall-related injuries.

PICOT: In hospitalized adult patients at high risk for falls (P), does continuous 1:1 sitter observation (I), compared to standard safety interventions (C), reduce fall rates (O) as measured by reported falls per 1,000 patient days during hospitalization over 12 weeks (T)?

Evidence: Current evidence supports multifactorial fall-prevention programs that combine patient assessment, staff engagement, and proactive nursing interventions through intentional rounding. …

Llm-Enabled Open-Source Systems In The Wild: An Empirical Study Of Vulnerabilities In Github Security Advisories, Fariha Tanjim Shifat, Hariswar Baburaj, Ce Zhou, Jaydeb Sarker, Mia Mohammad Imran

Computer Science Faculty Research & Creative Works

Large language models (LLMs) are increasingly embedded in open-source software (OSS) ecosystems, creating complex interactions among natural language prompts, probabilistic model outputs, and execution-capable components. However, it remains unclear whether traditional vulnerability disclosure frameworks adequately capture these model-mediated risks. To investigate this, we analyze 295 GitHub Security Advisories published between January 2025 and January 2026 that reference LLM-related components, and we manually annotate a sample of 100 advisories using the OWASP Top 10 for LLM Applications 2025.We find no evidence of new implementation-level weakness classes specific to LLM systems. Most advisories map to established CWEs, particularly injection and deserialization weaknesses. …

Improving Cancer Diagnosis And Patient Outcomes With Deep Learning Models, Mariana Arriz-Jorquiera

USF Tampa Graduate Theses and Dissertations

Cancer care depends on timely and reliable decisions, from detection and diagnosis to treatment planning and patient monitoring. These decisions are often made under uncertainty because medical images and healthcare data may be noisy, incomplete, or difficult to interpret. In breast cancer imaging, ultrasound is widely used because it is safe, accessible, and complementary to other imaging modalities. However, variations in image quality, acquisition conditions, and noise can obscure lesion boundaries and texture, affecting human interpretation and artificial intelligence reliability. This dissertation develops deep learning, image-analysis, and optimization methods to improve healthcare decisions under imperfect information. Its primary focus is …

Determinants Of Home Composting Behavior In Supporting Sustainable Agriculture Among Smallholder Farmers: A Case Study In The Thai Nguyen Province Of Vietnam, Bac Ho Van, Hien Vu Thi, Xinh Ho Luong

Journal of Environmental Science and Sustainable Development

Home composting is a practical and sustainable approach for the management of organic waste generated in the home and agricultural production that contributes to both organic waste management and soil fertility enhancement. In the northern mountainous regions of Vietnam, smallholder farmers face limited adoption of sustainable waste management practices due to behavioral constraints, limited technical knowledge, and resource constraints affecting agricultural productivity.  This study applies and extends the Theory of Planned Behavior (TPB) by integrating behavioral and contextual determinants to examine home composting adoption among smallholder farmers in rural Vietnam. Principal Component Analysis (PCA) was used to reduce and structure …

Quantitative Methods In Education: A Practical Introduction To Statistics, Yukiko Maeda, John Gipson, Sheila Hurt, Katie H. Dufault

Purdue University Press Books

Educational research often involves understanding complex patterns in student achievement, teacher effectiveness, and institutional performance. Quantitative Methods in Education: A Practical Introduction to Statistics is designed to equip current and future educators and researchers with a basic comprehension of the statistical tools necessary to effectively analyze and interpret educational data. In today’s data-driven world, the ability to leverage statistical techniques is essential for making informed decisions that can enhance learning outcomes and maximize learner potential. This book provides a systematic approach to exploring these trends using both descriptive and inferential statistics, providing readers with the knowledge to conduct rigorous analyses …

Cnkg: Harnessing Large Language Models For Cognitive Neuroscience Knowledge Graph Construction, Ali Sarabadani, Kheirollah Rahsepar Fard, Hamid Dalvand

Turkish Journal of Electrical Engineering and Computer Sciences

Textual resources are among the most valuable sources of information in cognitive neuroscience (CN) for understanding and investigating brain activity and cognitive processes. Extracting and constructing knowledge graphs (KGs) from these texts can facilitate medical research by providing deeper insights into neurological diseases and brain function. In recent years, the use of large language models (LLMs) in natural language processing (NLP) has become increasingly widespread, significantly enhancing the extraction of meaningful information from large volumes of text. This study proposes a novel approach for constructing and evaluating a specialized knowledge graph, termed the cognitive neuroscience knowledge graph (CNKG), from scientific …

Building The Next Cybersecurity Workforce: A Grades 7–12 Curriculum To Close The Cyber Talent Gap, Mohammed A. Salam, Iqbal Shareef, Rich P. Manprisio

Journal of Cybersecurity Education, Research and Practice

In today’s rapidly evolving technological landscape, cyberattacks pose increasing threats, yet a global shortage of cybersecurity and digital forensics professionals leaves industries vulnerable, similar to having too few law enforcement officers in a densely populated city. The judicial system faces rising digital crimes and fraud cases, further strained by the lack of experts to analyze and extract digital evidence. Despite high demand, millions of positions remain unfilled. This paper identifies the root causes of the cybersecurity workforce shortage and proposes a targeted solution: a curriculum for Grades 7–12 designed to foster cybersecurity awareness and interest. The methodology included a comprehensive …

Human-Driven, Autonomous, Or Hybrid? The Optimal Fleet Configurations For Ride-Hailing Platforms, Wenjing Li, Yali Zhang, Jun Sun, Zhaojun Yang

Information Systems Faculty Publications

The growing commercialization of autonomous vehicles (AVs) is reshaping consumer service preferences and prompting ride-hailing platforms to redesign fleet structures that accommodate the coexistence of human-driven vehicles (HVs) and AVs. This article develops a queueing game framework that incorporates vehicle heterogeneity and consumer preference differences to systematically compare three fleet configuration strategies: the pure HV (PHV) strategy (HVs only), the pure AV (PAV) strategy (AVs only), and the hybrid strategy (both HVs and AVs). The analysis highlights how consumer mismatch losses, AV operating costs, and service rates jointly shape equilibrium outcomes. Results show that when consumer mismatch losses are moderate, …

Learning Programming In Informal Spaces: Using Emotion As A Lens To Understand Novice Struggles On R/Learnprogramming, Alif Al Hasan, Subarna Saha, Mia Mohammad Imran

Computer Science Faculty Research & Creative Works

Novice programmers experience emotional difficulties in informal online learning environments, where Confusion and Frustration can hinder motivation and learning outcomes. This study investigates novice programmers' emotional experiences in informal settings, identifies causes of emotional struggle, and explores design opportunities for affect-aware support systems. We manually annotated 1,500 posts from r/learnprogramming using the Learning-Centered Emotions framework, applying clustering, and axial coding. Confusion, Curiosity, and Frustration dominated emotional experiences, sometimes co-occurring and linked to early learning stages. Positive emotions were infrequent. The primary emotional triggers included ambiguous errors, unclear learning pathways, and misaligned resources. We identify five key areas where novice programmers …

Signal And Substance: Why Methodological Sophistication Fails To Guarantee Inference, Aamir Rashid, Rizwana Rasheed

Publications and Research

Despite increasing analytical sophistication, empirical research in organization studies continues to suffer from fragile inference, uneven theoretical accumulation, and contested credibility. This paper seeks to explain why these problems persist by shifting attention from authors’ methodological choices to the evaluative dynamics of peer review. Adopting a conceptual and theory-analytic approach, the paper theorizes peer review as an inferential gatekeeping system. Drawing on research design, theory evaluation, and philosophy-of-science literatures, this study develops an analytical framework to examine how evaluative routines shape what constitutes empirical rigor during the review process. The analysis identifies five recurring reviewer blind spots: inferential scope inflation, …

How Can Accessibility In Computing Education Be Improved Through Hci Research?, Dr David Santandreu Calonge, Linda Smail, Firuz Kamalov, Dima Yousef, Melody Sylvain

All Works

Accessibility - accommodation of diverse sensory, motor, cognitive, and linguistic needs - remains critically underrepresented in computing education despite broad societal acknowledgment of its importance. This position paper argues that systemic inequities and persistent barriers to integrating accessibility and inclusion - ranging from curricular inertia to limited faculty capacity - require new methodological approaches drawn from Human-Computer Interaction (HCI) research. HCI provides tested frameworks that pair participatory design with inclusive pedagogy, guided by empirical evaluation to drive systemic change. We identify three key areas where HCI can advance accessibility education: (1) embedding accessibility within core curricula through design-based pedagogies, (2) …

Mental Health Self-Perceptions And Resource Utilization In Undergraduate Students At Binghamton University, Nicole J. Dreznin, Sarah Marcus

Binghamton University Undergraduate Journal

Undergraduate students face increasing rates of mental health challenges, however discrepancies in mental health literacy and utilization of resources may exist across student populations. This study examined the perceptions of mental health in undergraduate students at Binghamton University and if they differed among STEM vs non-STEM, man vs. women, and first-generation vs. continuing generation undergraduate students. A 20-question survey, containing 5 demographic questions and 15 mental health related questions was distributed through Qualtrics to 9 undergraduate classes. The available response choices were based on the Likert scale. A total of 1266 students participated.  Chi square tests of independence were done …

A Differential Equation–Based Epidemiological Model Of Post-Operative Chronic Pain In Scoliosis Patients With Data-Driven Analysis, Paige Zhu, Padmanabhan Seshaiyer

CODEE Journal

Chronic post-surgical pain (CPSP) is a common and often overlooked complication following surgical correction of idiopathic scoliosis, impacting long-term patient wellbeing despite improvements in surgical outcomes. This project introduces a novel epidemiological framework to model the progression of CPSP using a compartmental structure. By applying a coupled system of nonlinear differential equations, we simulate pain trajectories over time and assess the effectiveness of surgical interventions. The model is implemented for a single-cohort population and extended to a two-cohort design to compare outcomes between Posterior Spinal Fusion (PSIF) and Vertebral Body Tethering (VBT) procedures. Further stratification by patient age enables us …

Perspectives Of Scholars, Families, And Advisors On 360-Degree Video Technology In Graduate Education, Oluwatobi A. Mogbojuri, Bridget A. Walsh, Matthew Aguirre

Journal of Human Sciences and Extension

This study explored the experiences of scholars in creating and sharing 360-degree videos, as well as the perspectives of families and advisors who viewed the videos. Focus groups and individual interviews were conducted online using a videoconferencing platform. Perspectives from 20 participants (15 scholars, three advisors, and two family members) were analyzed using thematic analysis. Three primary themes were identified: (1) barriers to 360-degree video use, (2) perspective shifts and limited change, and (3) storytelling and scholar visibility. Findings suggest that 360-degree video technology may be an innovative tool for enhancing recruitment and retention, especially for historically marginalized groups, through …

Insurgent Until Proven Innocent: Land, Power, And The Right To Defend Rights, Kelsey Jost-Creegan

Michigan Journal of International Law

As the climate crisis intensifies, advocates worldwide have stood up to defend their communities, territories, and environment. In response, they have faced violent retaliation. This repression persists despite evolving international, regional, and national-level legal frameworks around the “right to defend rights” and the “right to protection.” This article begins by providing a comprehensive overview of this evolving legal landscape. Against this backdrop, the article examines the tactics and architectures of violence used to repress land and environmental defenders through the lens of counterinsurgency theory.

The article proposes a typology of counterinsurgent violence including: surveillance; stigmatization; criminalization; arbitrary detention; infiltration; cooptation; …

Item Response Theory Evaluation Of Mental Health Sentiment Scales, Muhammad Amzad Hossain

Graduate Theses and Dissertations

Mental health is an essential part of overall well-being. Accurate measurement of constructs such as loneliness, anxiety, depression, and life satisfaction is extremely important in research and practice. Traditional approaches based on Classical Test Theory (CTT) are limited. They rely on total test scores and assume constant measurement error across individuals. They may not reflect true variability in measurement precision (Zein & Akhtar, 2025; Marvianto, 2023). In contrast, Item Response Theory (IRT) provides an advanced approach by examining item-level performance. It models the relationship between latent traits and responses (Zein & Akhtar, 2025 ). To address these limitations, this study …

Influence Of Stormwater Flooding Events On The Mobile County School District Student Population, Kadence Kali Johnston

Honors Theses

Mobile County, Alabama, receives among the highest annual rainfall totals in the United States resulting in frequent stormwater flooding that intersects with existing socioeconomic vulnerabilities. Within the Mobile County Public School System (MCPSS), 77% of students are economically disadvantaged and over 10% experience homelessness, creating heightened risk for educational disruption during flood events. This study investigates how stormwater flooding influences school attendance, closures, and academic performance across MCPSS, providing insight into how climate-driven hazards exacerbate educational inequities. The research integrates flood frequency, school performance metrics, and GIS flood-zone mapping and teacher perceptions to understand how flooding affects student learning opportunities. …

Spatiotemporal Sycophancy: Negation-Based Gaslighting In Video Large Language Models, Ziyao Tang, Pengkun Jiao, Bin Zhu, Huiyan Qi, Jingjing Chen, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

Video Large Language Models (Vid-LLMs) have demonstrated remarkable performance in video understanding tasks, yet their robustness under conversational interaction remains largely underexplored. In this paper, we identify spatiotemporal sycophancy, a failure mode in which Vid-LLMs retract initially correct, visually grounded judgments and conform to misleading user feedback under negation-based gaslighting. Rather than merely changing their answers, the models often fabricate unsupported temporal or spatial explanations to justify incorrect revisions. To systematically investigate this phenomenon, we propose a negation-based gaslighting evaluation framework and introduce GasVideo-1000, a curated benchmark designed to probe spatiotemporal sycophancy with clear visual grounding and temporal reasoning requirements. …

Improving Urban Search And Rescue Team Coordination Through Adaptive Context Awareness, Daniel Reyes Duran

Doctoral Dissertations and Master's Theses

Modern multi-agent Urban Search and Rescue (USAR) operations heavily rely on mobile geospatial Common Operating Pictures (COPs) to maintain team coordination and Situational Awareness (SA). However, the proliferation of high-frequency sensor telemetry at the tactical edge has introduced a data saturation paradox challenge: while information theoretically drives informed decision-making, unmanaged data surges induce increased operator cognitive overload and alert fatigue on mobile End-User Devices (EUDs), while downstream data-broadcasting models inherently strain edge processing and viewport environments.

To resolve these constraints, this dissertation presents a context-aware Value of Information (VoI) data-management framework integrated directly with a custom, event-driven Android Team Awareness …

Operational Agency: A Permeable Legal Fiction For Tracing Culpability In Ai Systems, Anirban Mukherjee, Hannah H. Chang

Research Collection Lee Kong Chian School Of Business

Modern artificial intelligence (AI) systems act with a high degree of independence yet lack legal personhood—a paradox that fractures doctrines grounded in human-centric notions of mens rea and actus reus. This Article introduces Operational Agency (OA)—a permeable legal fiction structured as an ex post evidentiary framework—and Operational Agency Graph (OAG)—a tool for mapping causal interactions among human actors, organizations, and AI systems. OA evaluates an AI’s observable operational characteristics: its goal-directedness (as a proxy for intent), predictive processing (as a proxy for foresight), and safety architecture (as a proxy for standard of care). OAG operationalizes that analysis by embedding these …

Knowledge-State Generative Agents For Pre-Assessment Question Evaluation, Ping Fan Ke, Yi Meng Lau, Siaw Ling Lo

Research Collection School Of Computing and Information Systems

This paper introduces a Knowledge‑State Generative Agent framework for evaluating the quality of pre‑assessment questions. The framework employs large language model (LLM)–based agents prompted to adopt a teacher persona to simulate the responses of students with and without mastery of targeted knowledge components. A preliminary empirical study using archival data from 424 students enrolled in an Information Systems Management course indicates that the proposed approach yields interpretable metrics under Classical Test Theory. Results further show that agents instantiated with the relevant mastered knowledge components exhibit systematically higher performance than agents lacking such mastery. In addition, the study suggests that teacher-persona …

Towards Understanding Users' Theory Of Recommender Systems, Mohammed Muheeb Faizan Ghori

Theses and Dissertations from DePaul University

Recommender systems have become deeply embedded in digital platforms such as streaming services, social media, and e-commerce applications, shaping how users discover information, consume content, and interact with online environments. Despite their widespread adoption, these systems are frequently perceived as opaque ‘black boxes’, leaving users uncertain about how recommendations are generated, why certain content is prioritized, and whether their interactions meaningfully influence recommendation outcomes. Existing research at the intersection of recommender systems and human–computer interaction has largely focused on improving transparency, explainability, and recommendation quality from a system-centered perspective. However, limited research has examined how users conceptualize recommender systems and …

Comparing The Effects Of Project-Based Learning, Inquiry Learning, And Conventional Instruction On Students' Learning Motivation In Biology, Yeyen Angraini, Irwandi Irwandi, Jayanti Syahfitri

Jurnal Pendidikan Sains

Learning motivation is an important factor influencing students’ engagement, persistence, and success in Biology learning. However, classroom instruction at the senior high school level is often dominated by teacher-centered approaches, which may limit students’ active participation and motivational development. This study aimed to compare students’ learning motivation across Project-Based Learning (PjBL), Inquiry Learning, and conventional instructional approaches in Biology learning. The study employed a quantitative quasi-experimental design with a pretest–posttest approach involving three groups. Participants consisted of 85 Grade XI students from SMA Negeri 1 Talang Padang, South Sumatra, distributed across three classes: PjBL (n = 28), Inquiry (n = …

The Effect Of Emotional Intelligence And Logical-Mathematical Intelligence On Students’ Mathematical Problem-Solving Ability, Zulkyfli Siduppa, Sutji Rochaminah, Muh Hasbi, Dasa Ismaimuza

Jurnal Pendidikan Sains

Mathematical problem-solving ability is an essential competency in mathematics education because it supports students’ reasoning, critical thinking, and decision-making skills. This study aimed to examine the influence of emotional intelligence and logical-mathematical intelligence on the mathematical problem-solving ability of Grade XII students at SMA Negeri 1 Tolitoli. The study employed a quantitative survey design involving 143 students from the Mathematics and Natural Sciences (MIPA) program during the 2023/2024 academic year. Data were collected using an emotional intelligence questionnaire, a logical-mathematical intelligence questionnaire, and a mathematical problem-solving test on algebraic function limits. All instruments were validated and demonstrated satisfactory reliability, with …

Teachers’ Awareness Of Family Engagement In Multilingual Education, Sedighe Zamani Roodsari

Journal of Multicultural Affairs

This study investigated public school teachers’ awareness of family engagement as a linguistic and cultural resource for multilingual students. Multilinguals are typically described as individuals who can communicate in more than one language, with English not being their native language, and their linguistic choices are influenced by societal norms and systems (Šifrar Kalan et al., 2024; Wei, 2008). Preparing pre-service teachers to enhance opportunities for multilingual students remains a critical need in teacher education programs, as they strive to move beyond monolingual ideologies in their teaching practices (Cárdenas Curiel et al., 2024; Kim & Choi, 2020; Williams & Ewing, 2019). …