Digital Commons Network^™

Leveraging Artificial Intelligence For Transformative Education: Challenges And Recommendations, Papia Bawa

Journal of Research Initiatives

The sheer force with which GPT models are inundating business, education and economic fields speaks to its ability to not only transform the ways in which we interact and act but also disrupt these ways. This systematic literature review applies the PSALSAR method to synthesize findings from 72 articles on AI applications in education, emphasizing its transformative potential across various domains. AI is transforming personalized learning by customizing content and feedback to individual needs, addressing challenges like data privacy and ethical concerns. It enhances administrative efficiency through automation and data-driven decision-making, improving institutional performance while managing biases and maintaining human …

Early Childhood Pre-Service Teacher Interns’ Experiences In Building Relationships With Students’ Families, Fungayi Madzonga

Walden Dissertations and Doctoral Studies

Strong relationships between educators and students’ families are essential for fostering learning environments to meet the needs of early childhood students. The problem that was addressed through this study is that many early childhood preservice teacher interns (ECPTIs) experience challenges in building relationships with students’ families during the internship phase of teacher preparation in Alberta. Framed by ecological systems and self determination theories, the purpose of this basic qualitative study was to explore ECPTIs’ experiences building relationships with students’ families and to understand the resources needed to strengthen those relationships in Alberta. Semi structured interviews were conducted with 12 ECPTIs …

Building A Bridge To African American Student Success: A Quantitative Study At A Community College In Central Kentucky, Kauai R. Thurman

Morehead State Theses and Dissertations

A capstone submitted in partial fulfillment of the requirements for the degree of Doctor of Education in the Ernst and Sara Lane Volgenau College of Education at Morehead State University by Kauai R. Thurman on April 2, 2026.

The Effect Of Cerebral Somatosensory Network Priming On Language Function In Chronic L-Mca Ischemic Stroke: A Companion Case Study, Mandelin E. Wollesen

College of Education and Human Sciences: Dissertations, Theses, and Student Research

Chronic aphasia following a left middle cerebral artery (L-MCA) stroke is often associated with limited recovery beyond the acute phase, necessitating interventions that target neuroplastic mechanisms. This study examined the effects of somatosensory pneumotactile stimulation paired with cognitive-linguistic tasks on functional language performance in an individual with chronic aphasia. Using a single-subject pre-post design, the participant completed a 10-week intervention protocol involving repeated pneumotactile stimulation via the GALILEO system combined with language and motor tasks. Outcomes were assessed using standardized measures, discourse-based language samples, oral reading, repetition, and phonemic verbal fluency. Discourse was analyzed using Correct Information Units (CIUs), words …

Ais26s: Genai And Llms For Cybersecurity, Political Sciences, Transportation Security, And Resiliency, Latifur Khan

Paul English Applied Artificial Intelligence (AI) Institute Publications

This presentation examines the role of generative artificial intelligence (GenAI) and large language models (LLMs) in addressing complex challenges across cybersecurity, political science, and transportation security. Dr. Latifur Khan discusses how advanced AI methods can be applied to threat detection, data analysis, and decision-making in high-risk and data-intensive environments. The talk highlights interdisciplinary applications of LLMs, emphasizing their ability to extract insights from large-scale data, improve system resilience, and support intelligent infrastructure. Emerging research directions and practical implications for real-world deployment are also discussed.

Preschool Special Educators' Perceptions On Using Role-Play To Improve Language Development For Preschoolers With Autism, Ini Udosen

Walden Dissertations and Doctoral Studies

The problem that was addressed through this study is that preschool special educators are not consistently integrating role-play strategies when teaching language development to children with autism spectrum disorder (ASD) at ABC district (a pseudonym), a district in the southeastern United States. Grounded in Vygotsky’s social learning construct, the purpose of this study was to explore the perceptions of preschool special educators on using role-playing exercises to model proper communication behaviors and to improve learning skills as well as other advantages of role-play activities for children with ASD at ABC district. For this basic qualitative study, semistructured interviews were conducted …

A Qualitatively Driven Approach Integrated With Quantitative Analysis Applied To Decision Making In Institutional Administration Of Higher Education, Cristo Leon Ph.D., James Lipuma Ph.D., Michelle Kudelka

STEM for Success Resources

A qualitatively driven mixed methods study on decision-making in higher education administration. The article integrates Constructivist Grounded Theory, thematic analysis, participatory design, and quantitative dashboard analytics to examine interdisciplinary collaboration, institutional research management, and user-centered data visualization. It offers a practical framework for designing accessible and context-sensitive academic dashboards that support evidence-informed governance, resource allocation, and research strategy in universities

Historical Facts And Constitutional Law: New Challenges For Lawyers, Judges, And Scholars, Joseph Blocher, Brandon L. Garrett, H. Timothy Lovelace Jr.

Duke Law Journal

No abstract provided.

Unwanted Histories, Christen Hammock Jones, Karen M. Tani

Duke Law Journal

The Supreme Court’s turn to history as a method of constitutional decisionmaking has both intrigued and alarmed professional historians, for reasons now well-rehearsed in the literature. This Article takes as a given that history is now part of judges’ work. It then invites judges to think more expansively about the type of history they could—and perhaps should—be producing. This task, in turn, means engaging with some of the central questions about methodology and sources that preoccupy professional historians.

This Article focuses on a source base that historians routinely rely upon but that courts have shied away from: personal accounts of …

Falsifying Tradition, Darrell A. H. Miller

Duke Law Journal

From cases spanning gun rights, reproductive freedom, religious liberty, and personal jurisdiction; to separation of powers and other structural features of the Constitution, courts increasingly rely on tradition to guide their decisions. Often, judges appeal to tradition in a vaguely empirical way, as “facts to study, not convictions to demonstrate about,” in the words of Justice Antonin Scalia. Yet, for a claim that purports to be factual, there’s very little agreement, or even analysis, about what renders this factual assertion—tradition—true or false. This Article tackles that basic issue.

Part I surveys the ways in which courts use tradition in different …

A Hybrid System For Multi-Stage Generation Of Contextual Translation Variants, Leonid Kuligin, Thomas Zettl

Defensive Publications Series

Some automated translation systems may be limited by producing a single, high-probability output, which can lack the linguistic diversity beneficial for certain applications. A hybrid, multi-stage workflow can generate multiple contextual translation variants by utilizing a probabilistic generative model, such as a large language model, to produce an initial set of translation candidates based on specified constraints. These candidates may then be programmatically refined, rated for quality, and deduplicated using deterministic and semantic techniques. By producing a curated list of distinct translation options instead of one output, this process can provide broader linguistic coverage to improve the performance of dependent …

Energy, Computation, And The Nuclear Renaissance: Material Foundations Of The Data Economy, Apolo Fernandez

Helms School of Government Spring Public Policy Conference

No abstract provided.

Multimodal Speech-Based Dementia Detection Using Wav2vec2 And Demographic Features, Carlos Blanco, Prajwal Shetty, Tyler Hood

Artificial Super Intelligence (ASI) Conference

Early detection of dementia is essential for timely clinical intervention, yet existing diagnostic procedures remain costly and resource-intensive. Speech-based analysis has emerged as a promising non-invasive alternative due to its sensitivity to cognitive decline. In this work, we propose a multimodal framework that integrates self-supervised speech representations from wav2vec2 with demographic metadata, including age, gender, and ethnicity. We evaluate our approach against a strong audio-only baseline under a controlled experimental setup. Results demonstrate a +12.5% improvement in validation accuracy and consistent gains in macro F1-score. These findings indicate that demographic information provides complementary predictive signals beyond acoustic features alone, highlighting …

Voice As A Bio-Marker Of Surgical Recovery: Classifying Post-Operative Ent Patients Using Vowel Acoustics, Habeeb Kotun Jr., Shumit Saha

Artificial Super Intelligence (ASI) Conference

Voice has garnered significant interest as a biomarker for diagnosing and managing neurological, respiratory, and cardiovascular diseases. However, upper airway surgeries such as septoplasty, tonsillectomy, and functional endoscopic sinus surgery (FESS) can substantially alter vocal tract anatomy, thereby changing vocal acoustics and potentially confounding voice-based diagnostic systems. This study investigates whether acoustic features from sustained vowels can differentiate between these procedures and a control group. Audio was collected from 105 Spanish-speaking participants 15 days pre surgery and 15 days post surgery. For each vowel, 121 chroma, cepstral, spectral, and temporal features were extracted and then reduced to 90 longitudinally responsive …

Manipulation Behind The Pro-Choice Movement, Madeline S. Schlautman

Helms School of Government Spring Public Policy Conference

No abstract provided.

Ccp Political Warfare Campaigns Against The U.S., Naomi Park, Rael Worrhen, Hannah Worthen

Helms School of Government Spring Public Policy Conference

No abstract provided.

Voice-Controlled Unmanned Aerial System Using A Fine-Tuned Small Language Model For Real-Time Command Parsing, Owais Ahmed, Joseph Stanziano, Ram Sudharsanan, Raj Kondragunta, Adeel Khalid

Artificial Super Intelligence (ASI) Conference

This paper presents the concept and architectural design of a voice-controlled Unmanned Aerial System (UAS) that leverages a fine-tuned Small Language Model (SLM) to convert natural language voice commands into structured MAVLink flight instructions in real time. A custom quadcopter platform has been designed and assembled with a Pixhawk flight controller, and a web-based interface has been developed to integrate browser-based speech recognition with on-device SLM inference. We describe a systematic evaluation methodology for five candidate SLMs spanning encoder-decoder and decoder-only architectures, a custom dataset of 5,450 labeled drone command samples covering 11 operational command types and an unknown rejection …

Xagentmaint: Explainable Agentic Systems For Predictive Maintenance In Industrial Digital Twin Environments, Shikhar Patel, Sankeerth Adisha

Artificial Super Intelligence (ASI) Conference

Predictive maintenance in manufacturing demands more than accurate failure forecasting. Maintenance engineers require transparent and auditable decision rationale to act confidently. Industrial digital twin environments produce rich and continuous streams of sensor data. Existing AI models typically surface only numerical anomaly scores without contextual explanation. This paper presents XAgentMaint, an explainable agentic AI framework for predictive maintenance. The system integrates a Retrieval-Augmented Generation knowledge base with a ReAct reasoning agent. An XGBoost failure classifier serves as the core prediction component throughout the pipeline. All three components are evaluated on the NASA CMAPSS turbofan degradation dataset across all four sub-datasets (FD001-FD004), …

Restorative Literacy: Designing Human-Centered Learning In Technological Times, Camille O'Quin

Research Days

As educational environments increasingly integrate artificial intelligence and automated instructional tools, important questions emerge about what must remain distinctly human in teaching and learning. This presentation introduces Beyond the Margins (BTM): Restorative Literacy for Rising Voices, an interdisciplinary initiative that reimagines literacy instruction through relational, justice-centered practice in technological times.   Grounded in the Restorative Literacy framework, BTM integrates structured literacy instruction, narrative identity development, restorative dialogue, and interdisciplinary collaboration across speech-language pathology, social work, counseling, psychology, and special education. Implemented with justice-involved adolescents, the model positions reading and writing not only as academic skills but as pathways to voice, belonging, …

Filming Modernity And Islam In Colonial Egypt, Eid Mohamed

Journal of Religion & Film

This is a book review of Heba Arafa Abdelfattah, Filming Modernity and Islam in Colonial Egypt (Edinburgh: Edinburgh University Press, 2023).

Qbiasnet: Quantum-Enhanced Variational Classifiers For Ethical Bias Detection In Multimodal Ai Models, Nikunj Doshi, Kavach Shah, Shikhar Patel

Artificial Super Intelligence (ASI) Conference

Bias in multimodal AI systems that jointly process image and text inputs creates measurable risks in sensitive deployment contexts including public health, financial services, and automated hiring. Classical detection approaches face a fundamental architectural limitation in that they cannot efficiently model intersectional bias. Intersectional bias emerges from the nonlinear interaction of multiple protected attributes simultaneously across visual and linguistic modalities. This paper introduces QBiasNet, a hybrid quantum-classical system that encodes cross-modal CLIP embeddings into an 8-qubit Variational Quantum Circuit (VQC) implemented in PennyLane. By exploiting quantum entanglement, the VQC learns high-order feature correlations that linear probes and shallow neural networks …

Agripestdatabase-V1.0: A Structured Insect Dataset For Training Agricultural Large Language Model, Yagizhan Bilal Durak, Ashley Morgan-Olvera, Ahsan Ul Islam, Iftekhar Ibne Basith, Shahidul Islam, Syed Hasib Akhter Faruqui

Artificial Super Intelligence (ASI) Conference

Agricultural pest management increasingly relies on timely and accurate access to expert knowledge, yet high quality labeled data and continuous expert support remain limited, particularly for farmers operating in rural regions with unstable or no internet connectivity. At the same time, the rapid growth of artificial intelligence (AI) and large language models (LLMs) has created new opportunities to deliver practical decision support tools directly to end users in agriculture through compact and deployable systems. This work addresses (i) generating a structured insect information dataset to be used for LLM training, and (ii) adapting a lightweight LLM model (<= 7B) by fine tuning it for possible future edge device uses in agricultural pest management. The textual data collection was done by reviewing and collecting information from available pest databases and published manuscripts on nine selected pest species. These structured reports were then reviewed and validated by a domain expert. From these reports, we constructed question-answer (Q/A) pairs to support model training and evaluation. A LoRA-based fine-tuning approach was applied to multiple lightweight LLMs and evaluated. Initial evaluation shows that Mistral 7B achieves an 88.9% pass rate on the domain-specific Q/A task, substantially outperforming Qwen 2.5 7B (63.9%), and LLaMA 3.1 8B (58.7%). Notably, Mistral demonstrates higher semantic alignment (embedding similarity: 0.865) despite lower lexical overlap (BLEU: 0.097), indicating that semantic understanding and robust reasoning are more predictive of task success than surface-level conformity to reference text in specialized domains. By combining expert organized data, well structured Q/A pairs, semantic quality control, and efficient model adaptation, this work contributes towards providing support for farmer facing agricultural decision support tools and demonstrates the feasibility of deploying compact, high-performing language models for practical field-level pest management guidance.

Subaltern Women, State Neglect, And Climate Precarity: Rethinking Forest Landscape Governance In Indonesia, Titiek Kartika Hendrastiti, Siti Kusujiarti

The Indonesian Journal of Socio-Legal Studies

This article examines the social positioning and struggles of subaltern women in East Java, Indonesia, within the intersecting conditions of state neglect and climate precarity in Forest Landscape Governance (FLG). Drawing on field research conducted between 2022 and 2023, it employs Postcolonial Feminist Political Ecology (PFPE) and Postcolonial Feminist Participatory Action Research (PFPAR) to analyze how governance regimes simultaneously depend upon yet marginalize women’s ecological labor. Based on field conversations, storytelling, focus group discussions, participatory drawing, and community dialogues in Banyuwangi and Trenggalek, the study shows that subaltern women remain largely invisible within formal governance frameworks, despite their central role …

April 2026, Robert Kelly

Robert Kelly Manuscripts

No abstract provided.

“I Ignored Western Media And Went Down The Rabbithole No One Warns You About”: An Exoticization Genre On Youtube, Dixon D. Dayton

CISLA Senior Integrative Projects

No abstract provided.

Culturally Responsive Care For Jewish Patients And Colleagues In Speech-Language Pathology, Irene Brettman, Victoria Littman

Bridgewater Review

Speech-Language Pathology (SLP) is an ever evolving profession in the healthcare and educational landscape. Typically, individuals who have not required SLP services may be unaware of the practice’s specific scope. In a medical setting, among other urgent communication needs, an SLP often provides critical care for patients who are at risk for dysphagia. Dysphagia is a medical condition that interrupts normal swallow function when eating, drinking, and/or taking medication, and can result in negative consequences such as weight loss, malnutrition, eating disorders, and respiratory decompensation. Food is deeply personal and embedded across worldwide culture. For many people, eating and drinking …

Kenyon Alumni Magazine - Spring/Summer 2026

Kenyon College Alumni Bulletin

No abstract provided.

Unnoticed Witnesses Of History: First-Hand Accounts Of Ukrainian Women In South Carolina During Russia's Invasion Of Ukraine, Madeline R. Fyock

Senior Theses

Language and other cultural symbols have become widely contested in post-Soviet Ukraine, especially after Russian President Vladimir Putin’s full-scale invasion in February 2022. The conflict prompted many in Ukraine and its diaspora to re-negotiate and affirm Ukrainian national identity through language, traditions, and culture. The ways in which national identity is signaled in Ukraine has been widely studied in the wake of 2022, but less research has investigated how similar trends are occurring in migratory contexts, where conflict and displacement play crucial roles in identity construction. This study examines the ways that Ukrainian immigrant women in South Carolina signal their …

Evaluating The Impact Of Social Determinants Of Health On Outcomes Of Type Ii Diabetes In South Carolina, Alexander G. Downs

Senior Theses

Type II diabetes mellitus (T2DM) represents a significant public health burden in South Carolina, where 13.5% of adults are affected, surpassing the national rate of 12%. This integrative literature review examines the social determinants of health most strongly associated with T2DM morbidity and mortality in South Carolina, including race and ethnicity, socioeconomic status, rural or urban residence, educational attainment, healthcare access, and food insecurity. Evidence drawn from peer-reviewed studies, epidemiological reports, and state health data reveals that African American, rural, and low-income populations bear a disproportionate share of the diabetes burden in the state. These disparities arise through multilevel mechanisms …

The Middle-Class Rip-Off'? Subsiding Culture In Contemporary Ireland, Connell Vaughan Dr

Irish Communication Review

In the last few years (roughly since the start of the Covid-19 pandemic) there has been a noted increase in state-led cultural funding in Ireland. Key examples include the raise in the financial allocation to the Arts Council, the introduction of the Basic Income for the Arts scheme, and increased sports capital funding. With reference to the official communication documents of these cases (so-called ‘grey literature’) and deploying the classic 1982 episode of the British sitcom Yes, Minister, ‘The Middle-Class Rip-Off,’ which pitches sports funding against support for the arts, as a satirical lens, this paper reflects on the contemporary …