Digital Commons Network^™

A Study Of Artificial Intelligence (Ai) Use Among Entry-Level Occupational Therapy Doctoral Students, Gustavo Reinoso, Rachel Allen-Mchugh, Thomas Decker, Yolanda Griffiths, Stacey Huffman-Main, Leslie Jackson, Ashley Murray, Jamie Rognes, Christine Urish

The Open Journal of Occupational Therapy

Artificial intelligence (AI) is increasingly integrated into higher education, yet little research explores its use among entry-level occupational therapy doctoral (OTD) students. This study developed a scale to assess AI usage and perceptions, examining differences across academic years. Eighty OTD students from a mid-sized urban university completed a 44-item survey refined using a Delphi method with nine faculty experts. Exploratory factor analysis identified three subscales—Efficiency and Adaptability, Academic Integrity Concerns, and the Student-Professor Divide—accounting for 46.04% of the variance (Cronbach’s α = .72–.93). Multivariate analysis of variance revealed significant effects of academic year on subscale scores (Wilks’ Λ = .822, …

Ai’S Role In Searching For Evidence: Friend And Foe, Barbara (Basia) Delawska-Elliott, Brandon Wilkinson

Publications 2026-present

No abstract provided.

A Quality Assurance Framework For Maintaining And Enhancing Academic Standards Of Ai-Infused Higher Education: Insights From Gcc Faculty Perspectives, Nina Abdul Razzak

Higher Learning Research Communications

Objectives: This study addresses the gap in research on maintaining and enhancing the quality of artificial intelligence (AI)–infused higher education in a structured and systematized way by proposing a comprehensive quality assurance (QA) framework fit for that purpose.

Methods: The study employs a qualitative research design approach in the form of a constructivist or interpretive investigation, exploring in depth faculty members’ different perspectives and experiences in relation to AI implementation. The study combines a textual analysis of the international literature on the topic, with insights from four focus groups involving faculty members from various disciplines and colleges across the Gulf …

Does Culture Translate? A Case Study On Artificial Intelligencegenerated Text Concerning Japanese-Style Employment, Kanji Kitamura

Languages, Literatures, and Cultures Faculty Publications

Translation matters to international business when it has a discernible impact on firm performance or critical business processes. Current developments include machine translation, which is evolving in tandem with generative artificial intelligence (AI). On one hand, useful translation apps have become available to help the public communicate internationally. On the other hand, recent research concludes that even machine translation's best output still requires post-editing by a human. This argument implies that a machine-translated, grammatically accurate text may not always make sense to a human audience, possibly because of a semantic-pragmatic issue beyond the lexical level. This paper regards it as …

Advice For Incorporating Ai Tools Into Your Legal Practice, Celia Bigoness, Robert A. Mackenzie, David J. Reiss

Cornell Law Faculty Publications

We have been speaking with many lawyers and law students about using generative artificial intelligence (AI) tools in their legal practice. We are struck by the fact that many of them have not been experimenting much, if at all, with the tools that are available to them - although many acknowledge that their clients are increasingly integrating generative AI into their businesses. We have been integrating a lot of these tools into our own professional lives, and here are some tips to help lawyers and law students get comfortable with AI tools that can help them, in big ways and …

Ai Exposure And The Future Of Work: Tasks, Skill Demand, And Education, Erik Vasilauskas, Michael Horrigan

External Papers and Reports

No abstract provided.

Cognitive Conflict In Iconic Visual Representations: Comparing Conventional And Ai Approaches, Endrayana Putut Laksminto Emanuel, Herfa Maulina Dewi Soewardini, Radhitya Duta Pradana, Sikky El Walida

Jurnal Pendidikan Sains

Background of study: The rapid integration of Artificial Intelligence (AI) in higher education has transformed mathematical problem-solving practices, yet it introduces potential discrepancies in students’ visual understanding, particularly in geometric contexts, leading to commognitive conflicts in visual mediators. Aims and scope of paper: This study aims to analyze and compare the sources of commognitive conflict in iconic visual representations when students solve flat shape problems using conventional methods versus AI-assisted approaches. Methods: A qualitative design was employed involving 20 first-year mathematics education students divided into two groups (AI-assisted and conventional). Data were collected through students’ written work and semi-structured interviews …

Columnas: The Honors Program Newsletter At Bentley University, Amanda Li, Wilson Jan, Michael Raphael, Alexandra Rieckehoff, Karina Wu, Michael Shehata, Nilufar Noorian, Eloise Weintraub

Honors Program

INSIDE THE MODERN WORLD

Page 2: Stepping Out by Amanda Li

Page 3: Inside the Corporate Slop Bowl by Wilson Jan

Page 4: The Silencing: An Evaluation of the Global Attacks on the Right to Protest by Michael Raphael

THE SOUND OF CHANGE

Page 5: The Social, Cultural, and Economic Impact of Bad Bunny by Alexandra Rieckehoff

Page 6: Streaming Changed Music, But Is It Fair to Artists? by Karina Wu

Page 7: Feeling the Music: How Haptic Wearables Are Changing the Way We Experience Sound by Michael Shehata

SHIFTING SYSTEMS

Page 8: The Story Behind Davos, One of the …

Statistical Investigation Project, Ahmad Almomani Ph.D.

School of Arts & Sciences

The assignment was developed by SUNY Geneseo Professor Ahmad Almomani for the course, MATH 242: Elements of Probability and Statistics in the spring 2026 semester.

The objective for this assignment is that students will apply statistical methods to analyze real-world data and communicate meaningful conclusions.

Navigating The Ai Classroom: Integrating Ai In Education For Enhanced Learning And Career Readiness, Katryna M. Johnson

Journal of Applied Marketing Theory

This study employs an innovative approach by integrating AI and human endeavors in the research process. The examination provides a literature review and theoretical frameworks for integrating AI in education, focusing on three key stakeholder groups: students, faculty, and institutions. The analysis explores the benefits and challenges of AI in the classroom from each group’s perspective. The paper emphasizes hands-on AI experience for marketing students to remain competitive. The paper provides practical tips and suggestions for using AI in marketing classes and creating an institutional environment to support long-term AI growth. Additionally, the study presents widely used AI tools in …

Grading Machines: Can Ai Exam-Grading Replace Law Professors?, Kevin L. Cope, Jen Frankenreiter, Scott Hirst, Eric A. Posner, Daniel Schwarcz, Dane Thorley

Faculty Scholarship

In the past few years, large language models (LLMs) have achieved significant technical advances, such that legal-advocacy organizations are increasingly adopting them as complements to—or substitutes for—lawyers and other human experts. Several studies have examined LLMs' performance in taking law school exams, finding mixed results. Yet there have been no published studies systematically analyzing LLMs' competence at one of law professors' chief responsibilities: grading law school exams. This paper presents results of an analysis of how LLMs perform in evaluating student responses to legal analysis questions of the kind typically administered in law school exams. The underlying data come from …

Advanced Artificial Intelligence Vs Simpler Models For 1-Year Death Prediction Among Patients Receiving Hemodialysis, Karthikeyan K, Jennifer E Flythe, Patrick H Pun, Wolfgang C Winkelmayer, David Carlson

Faculty, Staff and Students Publications

Objectives: We evaluated the data requirement for modern AI tools to outperform simpler models in predicting short-term mortality in over 500 000 patients with hemodialysis-dependent kidney failure.

Materials and methods: We compared logistic regression, boosting, and transformers using increasingly complex feature sets (from last-visit data to full trajectories). Performance was measured using the area under the ROC curve (AUC-ROC) and the Precision-Recall curve (AUC-PR) across training data sizes ranging from 500 to 490 197 samples.

Results: Using features with temporal information is beneficial across all models. On the full dataset, Transformers (AUC-ROC = 0.8568) and boosting (AUC-ROC = 0.8598) perform …

Artificial Intelligence And Music Creativity: The Human Element And An Exploration Of Possibilities, Benjamin J. Guerrero, Raffaella Borasi, David Miller, Blaire Koerner, Zenon Borys, Yu Jung Han, Rachel Roberts

Journal of the Association for Technology in Music Instruction

Artificial Intelligence (AI) is widely recognized as a potential game-changer for music-making. However, the direction of these changes and the extent of their impact on the music field will depend on how musicians use AI, which partly hinges on their perceptions of AI and their willingness to engage with it. Debates are ongoing about AI’s impact on creative fields, and we anticipate that musicians’ views on these matters will significantly influence their readiness to incorporate AI into their work. We interviewed 43 participants who use technology in various roles across different music genres to gain insight into their experiences with …

Chatgpt Versus Uptodate In Preclinical Medical Education: Cross-Sectional Analysis Using Term Frequency-Inverse Document Frequency Cosine Similarity, Shankar S. Thiru, Nicholas E. Aksu, Matthew Chiang, Daniel O. Gallagher, Mary Furlong, Elizabeth R. Prevou, Akhil Jay Khanna

Rothman Institute Papers

BACKGROUND: Generative artificial intelligence tools such as ChatGPT are increasingly used by medical students for self-directed learning. Although these models demonstrate linguistic fluency, their reliability as supplementary resources for preclinical education remains uncertain. In particular, comparisons with evidence-based references such as UpToDate are lacking.

OBJECTIVE: This study evaluated the similarity between responses generated by ChatGPT (with GPT-4o mini) and those from UpToDate to preclinical medical education questions to assess ChatGPT's potential as an adjunctive learning tool.

METHODS: We conducted a cross-sectional comparison study using 150 first-order questions derived from a preclinical question bank at a single allopathic institution under the …

Why General Ai Inherited The Body: A Structural Account Of Embodied Modulation Under Monolithic Imitation, Griselda Poe

Publications and Research

General AI has pursued the replication of human-level intelligence without first decomposing human cognition into structurally distinct components. Human cognition, however, is shaped by embodied constraints such as mortality, survival pressures, finite lifespan, and physiological states. This paper argues that when cognition is treated as a single undifferentiated whole, embodied modulation is not accidentally introduced into AI systems but structurally entailed. Any attempt to imitate “human intelligence” under a monolithic model necessarily incorporates variability shaped by mortal embodiment. The tensions observed in contemporary AI systems are better understood as consequences of copying an undecomposed target rather than isolated implementation errors. …

Defining A Multi-Omic, Ai-Enabled Stool Screening Paradigm For Colorectal Cancer: A Consensus Framework For Clinical Translation, Arturo Loaiza-Bonilla, Yan Leyfman, Viviana Cortiana, Rhys Crawford, Shivani Modi

Einstein Health Papers

Colorectal cancer (CRC) develops through both conventional adenoma-carcinoma and serrated neoplasia pathways, yet noninvasive screening still under-detects the advanced precursor lesions that enable true cancer prevention. Stool-based screening reduces CRC mortality, but its preventive impact remains constrained by limited detection of advanced precancerous lesions (APLs), including advanced adenomas and sessile serrated lesions. Next-generation multitarget stool DNA assays (mt-sDNA; e.g., Cologuard Plus) have established high sensitivity for CRC and specificity approaching 94%, leaving improved APL detection as the principal opportunity for innovation. This review presents a consensus framework for a multi-omic stool screening paradigm that integrates host epigenetic markers (DNA methylation) …

Examining The Effect Of Enhanced Retrieval Practice With Or Without Artificial Intelligence On Task Value And Self-Efficacy Of College Students: A Quasi-Experimental Study, Duane N. Stutzman

Doctoral Dissertations and Projects

The purpose of this quantitative quasi-experimental study was to determine if a significant difference exists in college students perceived task value and self-efficacy when using different forms of retrieval practice enhanced with or without artificial intelligence. This study is important because task value and self-efficacy may have an impact on student motivation and engagement; therefore, the study adds to the literature demonstrating that retrieval practice can help improve active, rather than passive learning. The sample was composed of 140 undergraduate students enrolled in a hybrid health science course at a large university in the Midwest. After participants completed their assigned …

Applications Of Artificial Intelligence In Nanotechnology, Shahad Eabd Alrida, Ola Obed, Elaf Taha, Thamer Abdullah, Mustafa Hathal, Viola Somogyi

Engineering and Technology Journal

Artificial intelligence (AI) is emerging as a prominent technological advancement. It is the act of replicating human intelligence for many purposes. In contrast to conventional methodologies, artificial intelligence (AI) is undergoing tremendous advancements. The present state of artificial intelligence (AI) technology enables them to effectively address numerous intricate difficulties with proficiency comparable to a human's. The significance of advancements in AI is particularly evident in machine learning, where the techniques and algorithms are effectively applied to address many problems, including those in nanotechnology. In contemporary nanotechnology, it is crucial to expedite the search for the most favorable synthesis parameters while …

Human-Ai Collaboration In Marketing Brainstorming: A Meta-Analytic Investigation Of Implementation Approaches And Creative Outcomes, Michael Michaels

USF Tampa Graduate Theses and Dissertations

Marketing organizations face intensifying pressure to sustain creative output while managing constrained resources and accelerating digital content cycles. The integration of artificial intelligence into marketing brainstorming processes presents a promising response to this challenge; however, prior to this investigation, no comprehensive quantitative synthesis had established the overall effectiveness of human-AI collaboration in marketing creativity contexts or identified optimal implementation strategies.

This dissertation presents a systematic meta-analytic investigation of AI-enhanced brainstorming effectiveness in marketing contexts. Following PRISMA guidelines, 42 independent empirical studies (N = 2,166 participants) published between 2018 and 2025 were identified across four primary academic databases, coded for implementation …

Opportunities, Challenges, And Conspicuous Absences: An Integrative Review Of The Social Work Literature On Artificial Intelligence, Michael J. Massey, Ian G. Williams, Grace C. Polistina, Eathan A. Breaux

Publications and Research

INTRODUCTION: Social work discourse regarding artificial intelligence (AI) in practice, research, and education has proliferated over the last 5 years, reflecting both excitement over its potential and ambivalence about its ethical challenges. However, the extent to which social work is fully engaging with the structure of AI and its enormous impacts on the environment, labour, and distribution of power remains unclear.

METHODS: An integrative review of social work literature from 2020–2024 was conducted to address two research questions: 1) What is the nature of the social work discourse related to AI? 2) To what extent is the discourse …

Do Emotions Matter In Ai? The Mediating Role Of Emotional Response Between Perceived Risk And Trust, Areej Babiker, Mohamed Basel Almourad, Sameha Alshakhsi, Magnus Liebherr, Raian Ali

All Works

Research shows that trust in AI is influenced by socio-ethical considerations, technical features of AI systems, and user characteristics. Yet, the mediating role of emotional response between perceived risk and trust remains underexplored, particularly across different AI contexts. This cross-sectional vignette experiment design aims to explore the relationship between users' perceived potential risk, emotional response, and trust in AI, and examine how these relationships vary across different levels of automation and criticality. An online survey included a total of 639 participants including 316 from the UK and 323 from Arab Gulf Cooperation Council (GCC) countries. Participants rated their perceived risk, …

Markets, Agency, And Trust: Ai Agents And The Knowledge Problem, Brennan Mcdavid, Lynne Kiesling, David Chassin

Philosophy Faculty Articles and Research

Artificial intelligence (AI) is transforming market participation, raising key epistemological questions: Do AI agents enhance or diminish the aggregation of local, private, and tacit knowledge Hayek saw as essential to market processes? How does trust in both markets and AI shape willingness to engage in AI-mediated exchange? This paper examines these issues through market epistemology, agency relationships, and trust epistemology, analyzing how agentic AI reshapes the knowledge problem and principal-agent dynamics. Applying this framework to transactive energy markets, we show that AI shifts decision-making from human cognition to algorithmic processes that require user trust despite epistemic opacity, although it is …

An Ai Approach To Differentiating Lung Squamous Cell Carcinoma From Metastases Of Other Origins, Mark G Evans, Jennifer Ribeiro, Todd Maney, Anthony Helmstetter, Jennifer Johnson, Anthony Karnezis, Casey Bales, George Sledge, David Spetzler, Ari Vanderwalde, Matthew Oberley, Balazs Halmos, Hossein Borghaei, Farah Abdulla, David Bryant, Fred Hirsch, Hassan Ghani

Department of Medical Oncology Faculty Papers

IMPORTANCE: Distinguishing primary lung squamous cell carcinoma (SCC) from squamous metastases to the lung is a clinical challenge due to histopathologic similarities. Accurate diagnosis is essential to guide treatment decisions.

OBJECTIVE: To assess the utility of an artificial intelligence (AI) approach that includes evaluation of key orthogonal evidence in distinguishing primary lung SCCs from metastatic tumors of other tissue origins.

DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study used GPSai, a tissue-of-origin AI model run automatically on each sample submitted for molecular profiling, to flag potential misdiagnoses among research-eligible cases submitted as lung SCC. Molecularly profiled cases within the Caris Life …

Neurosymbolic Counterpoint Generation, Paul D. Jarski

Master's Theses

Recent advancements in generative artificial intelligence have revolutionized music generation, yet research has predominantly focused on raw audio synthesis over music in symbolic form, i.e. a score. This thesis presents the first neurosymbolic model designed to generate imitative Renaissance counterpoint in symbolic (MIDI) format. By leveraging an autoregressive Transformer architecture, this research explores the capacity of deep learning models to manage independent voices and strict stylistic constraints.

We compare multiple data representation strategies with distinct tokenization methods. The proposed model incorporates a symbolic component that enforces fundamental contrapuntal rules. Additionally, this thesis contributes a preprocessed dataset of Renaissance polyphony, in …

Using Large Language Models To Analyze Political Texts Through Natural Language Understanding, Kenneth Benoit, Scott De Marchi, Conor Laver, Michael Laver, Jinshuai Ma

Research Collection School of Social Sciences

Large language models (LLMs) offer scalable alternatives to human experts when analyzing political texts for meaning, using natural language understanding (NLU). Qualitative NLU methods relying on human experts are severely limited by cost and scalability. Statistical text-as-data methods are scalable but rely on strong and often unrealistic assumptions. We propose a systematic, scalable, and replicable method that can extend existing qualitative and quantitative approaches by using LLMs to interpret texts meaningfully rather than as mere data. Our ensemble means of LLM-generated estimates of party positions on six key issue dimensions correlate highly with equivalent mean ratings by country specialists. When …

A Free Speech Dilemma: Ai Outputs And The Constitution, Mbilike M. Mwafulirwa

Akron Law Review

In the beginning was a word—then over time, a whole civilization was built on words. Speaking, thinking, and writing have always been inherent aspects of the human experience. Until now. Artificial intelligence machines have hi-jacked words. Through focused training on our words and knowledge, they too can now write, create, and express themselves just like we do. This, then, presents a profound constitutional question flagged by Justice Barrett in Moody v. NetChoice: if the U.S. Constitution protects human expression, does it also protect AI outputs?

This article addresses that question through the derivative principle: If you squeeze an orange into …

The Role Of Artificial Intelligence In Macroeconomic Forecasting: A Systematic Literature Review, Thura J. Mohammed, Xinying Chew, Khai Wah Khaw

AUIQ Humanities and Social Sciences

Macroeconomic forecasting remains difficult because aggregate dynamics are nonlinear, regime-dependent, and increasingly informed by high-dimensional, mixed-frequency data, conditions under which traditional econometric models often lose accuracy, especially around turning points. This study systematically reviews how artificial intelligence (AI) is being used to address these challenges and what reliable evidence exists on its forecasting value. Using a PRISMA-aligned protocol, we searched Web of Science, Scopus, and ScienceDirect, identifying 1,627 records; after de-duplication and multi-stage screening, 178 studies were retained for qualitative synthesis. The review develops an evidence-based taxonomy of AI model families in macroeconomic forecasting and synthesizes their motivations, performance patterns, …

A Possible Renaissance For Christian Higher Education, Derek Schuurman

University Faculty Publications and Creative Works

The early Greeks saw the essence of education as Paideia: the process of forming a whole person into an ideal citizen. They emphasized the formation of virtues like prudence, justice, fortitude and temperance in preparation for active citizenship. Later, in the Medieval era, the Christian tradition saw education as formation for the glory of God, adding Christian virtues of faith, hope and love along with character traits like humility, gratitude, generosity and chastity. But something shifted after the Enlightenment and Industrial Revolution. Knowledge became increasingly instrumental, valued for its practical application primarily as information needed to “get a job.” …

Exploring K–12 Teacher Motivation To Engage With Ai In Education, Ethel Tshukudu, Katharine Childs, Gaokgakala Alogeng, Emma R. Dodoo, Douglas R. Case, Tebogo Videlmah Molebatsi

Faculty Research, Scholarly, and Creative Activity

While global interest in K–12 AI and ML education grows, many African education systems lack foundational computing education beyond basic computer literacy. This creates unique challenges for AI integration in countries where computer science isn’t part of the K–12 curriculum. Teachers are central to this effort, but little is known about what motivates them to engage with these technologies or how they use them. This study examined what motivates K–12 teachers to engage with AI and ML in Botswana. Using a mixed-methods approach, we surveyed 59 teachers using an adapted version of the Motivation to Teach Computer Science (MTCS) scale …

Artificial Intelligence In Nuclear Cardiology: Technical Perspectives, Strategic Directions, And Recommendations From An Iaea Expert Working Group, Christiane Wiefels, Luis Eduardo Juárez-Orozco, Pietro Selemo Craviolatti, Oleksandr Diahiliev, Amir Eskander, Raffaele Giubbini, Weihua Zhou, Et Al.

Michigan Tech Publications

Artificial intelligence (AI) is increasingly permeating nuclear cardiology and offers the possibility to enhance diagnostic accuracy, prognostic stratification, and operational efficiency. AI is demonstrating applicability across the imaging workflow—from individualized patient selection and adaptive image reconstruction to denoising of low-dose datasets, automated attenuation and motion correction, calcium scoring, and the integration of imaging with clinical and functional variables for enhanced diagnosis and comprehensive risk assessment. But the translational trajectory of AI in nuclear cardiology is challenged by the lag in fundamental AI knowledge among researchers and clinicians, the quality of the target data regarding heterogeneity in acquisition protocols, scanner platforms, …