Digital Commons Network^™

Understanding Chatbot-Assisted Collaborative Learning Among Female Undergraduate Students, Mohammad Amin Kuhail, Ahmed Shuhaiber, Sinan Salman, Nazik Alturki

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Computer programming can be daunting for beginners due to complex concepts and syntax. Traditional teaching methods, while engaging through gamification and active learning, often lack personalized approaches. Recent advancements in artificial intelligence (AI), particularly large language models (LLMs), present new possibilities for personalized and interactive learning environments. This study introduces a chatbot-assisted collaborative learning environment (CCLE) that leverages an LLM (GPT-4) to enhance collaborative programming education. The CCLE enables real-time guidance and collaboration through natural language interactions, allowing students to work together on programming tasks, edit code collaboratively, and engage with both peers and the educational chatbot. We conducted an …

A Robust Approach For Olive Leaf Disease Detection In Uncontrolled Environments, Rima Grati, Khouloud Boukadi, Emna Ben Abdallah, Ahmed Seffah

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Detecting diseases in olive leaves is crucial for maintaining tree health and ensuring stable olive production. Early signs of infection often appear on the leaves, making them a key indicator for timely disease detection and intervention. Traditionally, farmers rely on visual inspection or laboratory tests to diagnose plant diseases. However, recent advancements in deep learning (DL) have significantly improved the accuracy and efficiency of olive leaf disease diagnosis. Numerous studies in the literature have explored this task using CNN-based architectures and, more recently, Vision Transformers. While these models have shown promising performance on benchmark datasets, they are often trained and …

The Impact Of Generative Ai Training On Teachers’ Curriculum Adaptation Using Reflective Practices, Areej Elsayary

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Generative AI tools offer teachers opportunities to adapt curricula to meet diverse student needs. However, many educators lack the structured training and reflective frameworks necessary for effective and critical use of these tools. Numerous studies have examined the appropriate use of generative AI (GenAI) tools in facilitating differentiation, feedback, and personalized learning. However, teachers need to be trained on the “what” and “how” of integrating GenAI into curriculum adaptation to ensure a positive impact on student learning. This study evaluates the impact of training in-service teachers to use GenAI tools for curriculum adaptation. Specifically, the study investigates three research questions: …

Fig-Gan: Fundus Image Generation Via Deep Learning Based Generative Adversarial Network For Amd Disease Diagnosis, Kailasa Thrishul, Ahed Abugabah, Amina Salhi, Manel Ayadi, Mohamed M. Sithik, D. Jayaprakash, A. Ahilan

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Globally, age-related macular degeneration (AMD) remains a main cause of irreversible vision loss. Recently, deep learning models have primarily focused on classifying fundus images for early detection of AMD progression. However, existing models rarely address the generation of future progression-aware fundus images, particularly when complete real longitudinal follow-up scans are unavailable. This limitation makes it difficult to track retinal changes over time and highlights the need for generative models capable of producing realistic drusen-level structural variations. To address these issues, a novel deep learning-based FIG-GAN model is to generate synthetic future fundus images from baseline inputs. Multi-Attention U-Net (MAU-Net) is …

Temporally Rigorous And Traceable Predictive Maintenance Via Joint Labeler-Model Optimization, Maytha Al-Ali, Ahmad Alharbi

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Predictive maintenance (PdM) is a critical enabler of intelligent asset management in Industry 4.0, yet many existing frameworks remain difficult to operationalize due to methodological fragmentation. Common limitations include sacrificing temporal realism and class granularity for computational expediency, decoupling labeling strategy design from model hyperparameter optimization, and insufficient support for reproducibility and deployment traceability; particularly in rare-failure regimes. To address these challenges, we propose a unified, end-to-end, and fully traceable PdM framework that jointly optimizes labeling and model parameters while enforcing strict temporal fidelity. The proposed pipeline co-optimizes the failure lookahead window () and LightGBM hyperparameters within a single Bayesian …

Engineering Sulfur Concrete Mixes: A Data-Driven Approach To Aggregate Packing And Binder Efficiency, Vasilia Al Khaldi, Abdel Hamid I. Mourad, Maisa El Gamal

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Processing window (mass loss < 3%). A first-order, order-of-magnitude carbon-footprint estimate—presented with explicit caveats rather than as a full life-cycle assessment—indicates that replacing Portland cement with by-product sulfur is the dominant contributor to a substantial reduction in embodied CO₂ per cubic metre relative to equivalent-strength Portland cement concrete. The valorization of steelmaking by-products aligns with circular economy principles, enabling high-performance, recyclable, and low-carbon construction materials without chemical binder modification.

Towards Promoting Innovation In Inclusive Education: Behavioural Intention Of Teachers Towards Adopting Ai To Teach Students With Learning Disabilities In The Uae, Fatima Zraydi, Maxwell Peprah Opoku, Bernadette M. Guirguis, Laurent Gabriel Ndijuye, Ebenezer Mensah Gyimah

All Works

The integration of artificial intelligence (AI) in education offers significant potential for identifying and supporting all students, including those with learning difficulties. Although discussions on the potential of AI to advance the learning of students are ongoing, AI usage among teachers to leverage it in the teaching of students with learning disabilities in nonwestern contexts, such as the United Arab Emirates, is unresearched. The study was guided by a unified theory of acceptance and use of technology to examine teachers’ intentions toward adopting AI tools to enhance educational outcomes for students with learning disabilities in the UAE. Using a quantitative …

Image And Metadata-Driven Personality Inference For Career Recommendation: A Social Media-Based Ai Framework For Adolescents, Heba Ismail, Maryam Alhefeiti, Ashraf Khalil

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This study presents a novel AI-based framework that leverages Instagram image and metadata analysis to infer Big Five personality traits and deliver personalized career recommendations for high school students in the UAE. Addressing the limitations of traditional recommender systems that rely on self-reported questionnaires or text, the proposed approach uses multimodal visual features—including profile metrics, HSV color patterns, semantic image labels, and texture analysis—to enable a non-intrusive, scalable personalization method. A pilot study involving data from 30 student accounts served as a proof of concept. Correlation analysis identified profile and HSV features as the most predictive, and four machine learning …

An Advanced Healthcare System With An Automated Vit Model For Dermoscopic Skin Cancer Identification, Ahed Abugabah, Prashant Kumar Shukla, Suchi Mishra, Abhishek Dwivedi

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Early and reliable diagnosis of skin cancer from dermoscopic images remains challenging due to class imbalance, subtle inter-class variations, lesion boundary ambiguity, and illumination inconsistency, which can degrade the robustness of conventional convolutional neural networks (CNNs). To address these limitations, this study proposes an automated smart healthcare framework for dermoscopic skin cancer diagnosis using an Enhanced Vision Transformer (E-ViT) that improves global-context modeling through self-attention while strengthening fine-grained lesion representation learning. Unlike standard ViT configurations, the proposed architecture integrates multi-scale patch embedding and attention refinement to better capture border irregularities and color–texture heterogeneity that are critical for melanoma discrimination. Furthermore, …

Fair And Explainable Educational Recommendations With A Hybrid Graph-Gru Framework, Edmund Evangelista, Syed M.Salman Bukhari

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Artificial Intelligence (AI) recommender systems are increasingly used in education to personalize learning and help students navigate large collections of digital learning resources. However, many existing approaches emphasize predictive accuracy over fairness, robustness, diversity, and transparency. This creates an important educational challenge. The students with limited participation histories may receive less reliable support, while highly popular resources may dominate recommendation lists and limit access to other useful learning materials. To address this challenge, this study aims to develop and evaluate a responsible educational recommender framework that supports personalized learning resource navigation while making recommendation behavior more fair, stable, diverse, and …

Reimagining Sustainable Sulfur Concrete: A Systematic Review Of Sulfur, Waste Integration, And Durability, Vasilia Al Khaldi, Abdel Hamid I. Mourad, Maisa Elgamal

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Sulfur concrete (SC) - a thermoplastic, waterless composite in which molten sulfur-based binder replaces Portland cement - is attracting growing research attention as a sustainable construction alternative capable of superior performance in chemically aggressive environments. This systematic literature review synthesises evidence from 127 sources (2000–2025), examining three interlinked dimensions: (i) the role of waste and industrial by-product materials as aggregate and filler substitutes; (ii) the influence of aggregate type, morphology, and grading on mechanical and microstructural performance; and (iii) durability under acid, saline, and freeze-thaw exposures. A transparent, PRISMA-aligned screening and classification protocol - here used as a structured review …

Does Self-Efficacy Of Teachers Toward Inclusive Education Differ Between Primary And Secondary School? A Cross-Cultural Study Of Ghana And The United Arab Emirates, Ahmed Mohamed, Maxwell Peprah Opoku, Bernadette M. Guirguis, Ebenezer Mensah Gyimah, Maya Al Yafi, Shouq Alqahtani, Safa Alharthi, Mahra Aldhanhani, Al Zahra Aljaberi

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There are ongoing debates on the level of education that students with special educational needs could participate in and enjoy as part of their fundamental right to education. There is a notion that students with special educational needs could be more easily included in primary schools than in secondary schools. However, teachers were excluded from such discussions. The current study aims to invigorate such discussion by exploring primary and secondary school teachers' self-efficacy across Ghana and the United Arab Emirates (UAE). a total of 897 teachers were recruited from Ghana and the UAE to rate their self-efficacy via the Teacher …

The Role Of Corporate Sustainability Goals In Shaping Organizational Intentions And Adoption Of Green Technologies In Small- And Medium-Sized Enterprises, Syed Zamberi Ahmad, Abdul Rahim Abu Bakar, Imane Belyamani, Manar Fawzi Bani Mfarrej

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This study investigates green technology adoption (GTA) among small and medium-sized enterprises (SMEs) in the United Arab Emirates (UAE), focusing on the influence of corporate sustainability goals (CSG) and sustainability motivation (SM). Utilizing institutional theory, the theory of planned behavior (TPB), and resource-based view (RBV), the research highlights how SMEs integrate environmental, social, governance (ESG) and economic considerations into their CSG to enhance GTA. Addressing a gap in prior research that has largely emphasized external drivers of adoption while underexploring internal organizational mechanisms, the study conceptualizes CSG as strategic intent and models SM as a second-order construct . Based on …

A Performance-Optimized V2v Task Offloading Framework For Real-Time Vehicular Communication, Tariq Qayyum, Asadullah Tariq, Ikbal Taleb, Mohamed Adel Serhani, Zouheir Trabelsi

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As vehicular applications become increasingly complex, their computational demands often exceed the capabilities of individual vehicles. Vehicular Edge Computing (VEC) alleviates this limitation by enabling task delegation to nearby edge resources; however, high mobility, dynamic topology, and fluctuating vehicle density make real-time offloading decisions challenging. To address these issues, we propose a performance-optimized Vehicle-to-Vehicle (V2V) task offloading framework for dense and dynamic Vehicular Ad-hoc Networks (VANETs). The framework follows a two-stage design: (i) context-aware edge-node selection based on live topology capture via periodic beaconing, and (ii) cumulative score-based dynamic priority queuing at the selected edge node. The priority score jointly …

Transient Phenomenology Of Third Landscape In The United Arab Emirates, Luca Donner, Francesca Sorcinelli

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The Third Landscape, theorized by Gilles Clément, represents a residual territorial area, abandoned or not yet used, in which nature reclaims anthropized places. It is a paradigm based on the idea of a marginal, neglected context, but characterized by great intrinsic biodiversity. Starting from this theoretical assumption and supported by a photographic investigation, this study aims to identify some phenomenological characteristics of the Third Landscape in the United Arab Emirates. The scientific contribution will make use, in its dialectical and descriptive development, of reflections by authors such as, among others, Clément, Bauman, Lovelock, D’Angelo, Burkhardt, Augé, and Lynch. Starting from …

Large Language Models In Nlp: Evolution, Architectural Trends, And Open Challenges, Haseeb Javed, Babar Shah, Farman Ali, Daehan Kwak

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The rise of Large Language Models (LLMs) has transformed how Natural Language Processing (NLP) and its subdomains are approached. Recent technological advancements have driven this transformation. This study offers researchers a detailed overview of LLMs, comparing them with traditional rule-based systems, statistical techniques, machine learning, neural networks, and the rise of transformer-based architectures. From a wider perspective, language models such as GPT, BERT, T5, PaLM, and LLaMA have facilitated the transformation of entire sectors, including healthcare and business, due to their highly scalable nature. Despite their wide range of applications, LLMs face numerous challenges, such as output biases, limited interpretability, …

Anticipatory Governance And Leadership For Ai Implementation In Higher Education: A Scoping Review, Sandra Baroudi

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As the education sector attempts to address rapid changes caused by Artificial Intelligence (AI), it becomes crucial to examine approaches to leadership at the organizational and system levels. This scoping review explores how anticipatory models of governance are conceptualised and operationalised globally within higher education settings in the context of AI-related transformations. Using a scoping review design, academic and grey literature published between 2020 and 2025 was searched across Scopus, EBSCOhost, ERIC, Google Scholar, and ProQuest. Nineteen sources were selected based on clear inclusion and exclusion criteria and analysed thematically. Findings revealed that while AI offers promising opportunities to transform …

Extending Geometric Acoustic Ray Tracing To Multi-Room Environments: A Case Study On Gunshot Sound Transmission Between Adjacent Rooms, Tyler Ton

Theses and Dissertations

Accurate localization of gunshots in multi-room building environments remains a challenging problem in acoustic forensics and public safety applications. Existing approaches model sound propagation within a single room, neglecting the transmission of acoustic energy through walls and other building materials. This thesis presents a study on modeling multi-room gunshot acoustic transmission, combining geometric ray tracing with structural acoustic transmission-loss modeling to generate impulse responses for two horizontally adjacent rooms separated by a shared wall, providing a foundation for future inter-room gunshot localization work. The proposed system uses GSound-SIR, a geometric acoustics engine, to simulate sound propagation in both of the …

Representing The Brand: A Study To Examine The Best Practices For Structuring And Operating Communications Teams In Higher Education Institutions, Margaret L. Reisser

Masters Theses and Doctoral Dissertations

As higher education institutions increasingly compete for students, faculty, funding, and recognition, academic leaders are recognizing the essential role communications and public relations professionals play in maintaining and promoting the value of their institutional brands. Much has been written about the value of communications professionals in brand management in the corporate arena. However, it appears less attention has been paid to their role in higher education. This mixed-methods study was undertaken to examine the best practices for structuring and operating communications and public relations organizations for optimal success in promoting the higher education institutions they represent. Communications and public relations …

Weathering The Divide: Social Determinants, Neighborhood Context, And Systemic Lupus Erythematosus Among African American Women, Vanessa Cl Morman

Electronic Theses and Dissertations

Background: Systemic lupus erythematosus (SLE) disproportionately affects African American women and contributes to racial health disparities in the United States. Although genetic susceptibility influences disease risk, growing evidence suggests that social determinants of health (SDOH), including neighborhood conditions, structural racism, and socioeconomic disadvantage, contribute to disease development and progression. Epigenetic mechanisms may provide a biological pathway linking adverse social conditions to chronic disease disparities. This dissertation examined the influence of SDOH on SLE disparities through evidence synthesis and empirical investigation to inform public health practice and policy.

Methods: This integrated learning experience consisted of three complementary manuscripts. Aim 1 was …

An Assessment Of Accessibility And Affordability Of Inpatient Psychiatric Care In Tennessee, Kailee Havrda

Electronic Theses and Dissertations

Introduction: Access to mental health has seen changes over the past decade, but little research and attention have been given to access to inpatient psychiatric facilities. Inpatient psychiatric care is crucial for patients experiencing mental health emergencies who need immediate access to care. Gaps in spatial accessibility, affordability, and the access and assessment process were identified due to a lack of available information in the field.

Methods: Secondary data from the Tennessee Department of Health were used to assess financial accessibility through payer source charges and patient encounters, as well as through mapping of inpatient psychiatric facilities and conducting drive …

Exploring Competitive Dynamics Between Pseudomonas Baetica And Salmonella In A Polymicrobial System, Braxton E.M. Stout

Electronic Theses and Dissertations

The global rise in antimicrobial resistance has catalyzed a greater focus on polymicrobial research aimed at characterizing microbial interactions and uncovering new therapeutic strategies. Though it has long been of interest, environmental soil-derived bacteria remain largely under-represented in research and thus uncharacterized in this field. This project aimed to identify soil microbes that display inhibitory mechanisms to potential nosocomial pathogens. Soil sample S1S3-2 displayed inhibitory phenotypes toward numerous bacteria and was identified as Pseudomonas baetica. In both planktonic and biofilm growth, P. baetica was able to inhibit Salmonella arizonae through a contact-dependent and temperature-dependent manner. Screening of a transposon insertion …

Phytochemical And In-Vitro Cytotoxic Analyses Of Flavonoid Species Isolated From Chromolaena Leivensis, Luke A. Bryant

Electronic Theses and Dissertations

As a leading cause of death worldwide, cancer and its treatments remain a primary source of interest among researchers. Modern studies are looking into bioselective cytotoxicity to create new chemotherapies that do not have the same harsh side effects as those we use today. Natural product research has a promising future for the development of such treatments. Specifically, polar flavonoids may be the key to a bioselective treatment. Such flavonoid species are native to plants, often within flower petals or within the body. A natural antioxidant, they are designed not to harm healthy cells. This study focuses on the plant …

Microbial Treatment Of Refinery Wastewater Enables Fluted Pumpkin Growth And Food Safety, Eziafakaego M. Ibo, Odera R. Umeh, Oju R. Ibor, Chukwunonso P. Okoli, Azubuike V. Chukwuka, Emmanuel D. Omogbemi, Michael U. Orji, Aina O. Adeogun

Montclair State University Scholarship & Creative Works

Global water scarcity necessitates the reuse of agricultural wastewater, but safety concerns persist about contaminant transfer to plants. This study examined how treated and untreated petroleum refinery wastewater affected the growth and development of fluted pumpkins over a six-week cultivation period. The novelty lies in our comprehensive assessment of both growth performance and contaminant bioaccumulation in fluted pumpkins. The experimental design planted fluted pumpkin seeds in soils irrigated with 100% treated wastewater, untreated wastewater, or tap water (control). Weekly growth indicators (leaf count and height) and post-harvest parameters (root length, chlorophyll concentration, fresh and dry weight) were measured, and heavy …

Generative Ai Adoption And Solvers' Popularity On Supply-Driven Crowdsourcing Platforms: The Dual Role Of Price Signals, Zimeng Zhu, Carol Hsu, Fiona Fui-Hoon Nah, Na Liu

Research Collection School Of Computing and Information Systems

Purpose – We investigate the effect of solvers’ adoption of Generative AI (GenAI) on their popularity in a supply-driven crowdsourcing platform. We also examine the impact of price signals as well as their heterogeneous impact based on the solvers’ membership duration on the platform. Design/methodology/approach – Our analysis focuses on solvers who adopt GenAI for design-related gigs on the supply-driven crowdsourcing platform. By combining propensity score matching (PSM) with multi-period difference-in-differences (DID), we examine how GenAI adoption impacts solvers’ popularity and how price signals affect this main effect. Findings – Our findings reveal that solvers who adopt GenAI tend to …

Impact Of School Nurse Education On Factors Influencing Hpv Vaccine Communication With Parents, Jihye Choi, Efrat K Gabay, Jeanette Deason, Elizabeth Baumler, Diane Santa Maria, Daisy Mullassery, Lara S Savas, Erika Thompson, Sanghamitra M Misra, Paula M Cuccaro

Faculty, Staff and Student Publications

Human papillomavirus (HPV) can cause six cancer types but can be prevented with timely vaccination in early adolescence. However, despite the wide availability of the HPV vaccine, uptake remains suboptimal among US adolescents. School nurses are invaluable resources to students and their families regarding adolescent immunization needs. As part of the All for Them vaccination program, we assessed the impact of the continued nurse education (CNE) intervention on school nurses’ HPV vaccine communication with parents. Seventy-two school nurses and nurse administrators in Texas participated in the study. Using a single-arm study design, we measured participants’ potential barriers to and self-efficacy …

The Economics Of Modern Basketball Fandom, Holden Velasco

Capstones

In an increasingly money-sucking economy, many Americans are feeling the aching of their wallets. Basketball, once serving as an escape from the outside world, has now turned into a money-making machine where fans are paying to keep it running. It’s inescapable, whether it’s the rising costs to watch the professionals, forking thousands of dollars for children to play or sports gambling being plastered everywhere. Basketball no longer feels like basketball.

Integrating Student-Mined Data In Youth Computer Science Learning: An Investigation Of Learning Outcomes And Educational Strategies, Alex Acquah

Open Access Theses & Dissertations

As data increasingly shapes participation in society, there is growing emphasis on preparing youth to engage with data through computer science education. Existing K-12 computing and data science curricula have expanded opportunities for learners to analyze and interpret data; however, many learning experiences continue to rely on datasets and inquiry structures designed by others, limiting authentic engagement, personal relevance, and learner agency. This dissertation investigates the integration of student-mined data in youth computer science learning and examines its influence on computational thinking, epistemic agency, and learning experiences among high school students. Using a qualitative approach, data collected from youths of …

Providing Effective Student Feedback: Effects Of Sociotropy, Student-Teacher Connectedness, And Expressed Disappointment And Praise On Students' Self-Esteem And Motivation, Emily Davied

All Graduate Theses and Dissertations, Fall 2023 to Present

This study examined how different types of teacher feedback (i.e., expressed pride, expressed disappointment, and near-neutral feedback) impact students’ motivation to learn and self-esteem. It also explored whether such effects vary depending on students' personality and how connected they feel to their teacher. Undergraduate students (N = 221) imagined receiving feedback from a teacher and completed surveys assessing their motivation, self-esteem, sociotropy, and connectedness with the teacher. The results showed that feedback expressing disappointment lowered students' self esteem compared to expressing pride and lowered students' motivation compared to near neutral feedback. Although sociotropy (i.e., dependence on others' approval) and teacher …

Toward Optimizing Fruit Production In Utah Soils: Apple Salt Tolerance Screening And Tart Cherry Fertility Management, Kaitlin Dabbs

All Graduate Theses and Dissertations, Fall 2023 to Present

Fruit production in Utah can be challenging due to local climate and soil conditions. Tart cherries and apples are major fruit crops in Utah, and improvements to these cropping systems would be beneficial for farmers and local consumers. Two experiments were conducted to evaluate desired improvements for these crops. The first study looked for salt tolerance in ten new apple rootstocks. Salty soils can be found throughout the state limiting the land suitable for apple production. When grown in salty soils apple trees often have reduced growth and production potential. A specialized drip irrigation system was constructed in a greenhouse …