Digital Commons Network^™

Optimisation Of Stepped Basin Solar Still With Response Surface Methodology And Machine Learning Methods, M. Balamurugan, V. Santhanam, B. Deepanraj, S. P Manikandan, M. Yuvaperiyasamy, N. Senthilkumar

Mansoura Engineering Journal

This research focuses on enhancing the distillate output of a stepped basin solar still by optimizing key operational variables using Response Surface Methodology (RSM) and advanced machine learning techniques. As water scarcity remains a critical global challenge, solar stills offer a viable, sustainable solution for desalination. These systems offer an energy-efficient approach to converting saline water intofreshwater, providing an alternative to conventional desalination methods. The primary objective was to investigate how variations in solar radiation, step height, and water inlet temperature influence the productivity of the stepped basin solar still. The solar radiation ranged from 600 to 1000 W/m², the …

The Contributors, Marites Tiongco

DLSU Business & Economics Review

No abstract provided.

Professional Identity Exploration And Commitment Development By Stem Undergraduates From Underrepresented Groups During Near-Peer Mentoring, Joseph A. Brobst, Joanna K. Garner, David Hartenstine, Perry Fizzano

Center for Educational Partnerships Publications

This study examines near-peer mentoring as a context for professional identity development by undergraduates from groups that are underrepresented in STEM higher education. Mentees were students in a computer science/mathematics‑focused scholarship program, with a two-tiered near-peer mentoring component that paired 1st-2nd‑year undergraduate mentees with 3^rd-4^th year mentors and 3^rd-4^th year mentees with early‑career professional mentors. We analyzed mentoring conversation summaries from three mentor–mentee pairs, spanning one academic year. Mentoring relationships provided safe spaces for students’ professional identity exploration and the development of commitments toward career paths and life goals. Across all cases, conversation summaries …

Strengthening Literacy Outcomes For Students With Severe Disabilities: The Impact Of Teacher Preparation, Evidence-Based Approaches, And Learning Environments, Kallie Casale

All Electronic Theses and Dissertations

This literature review thesis examines factors influencing literacy instruction for students with severe disabilities, focusing on evidence-based approaches, educator training, and learning environments. The findings highlight that systematic instruction and specialized training, such as online modules, eCoaching, and practice-based feedback, significantly improve educator knowledge and student skill acquisition. The review demonstrates that comprehensive curricula, such as the Early Literacy Skills Builder (ELSB), yield greater gains in phonics and decoding than traditional sight-word approaches. The review of research also illustrates that inclusive settings promote academic progress through peer modeling and higher learning expectations than traditional self-contained environments. However, some educators prefer …

Supporting Early Literacy In Preschool: The Influence Of Activity Settings, Shared Reading, And Teacher–Child Interactions, Megan Turnquist

All Electronic Theses and Dissertations

This literature review explores current research about the activities and settings currently in place in preschool classrooms across North America. While a majority of the preschool day is spent in whole-group and free-choice activities, research indicates that instruction provided in small groups and book reading are two important ways to harness engagement and deliver high-quality instruction. Different kinds of teacher-child interactions during book reading can support the development of crucial early literacy skills, such as vocabulary and print knowledge. While time spent on literacy content varied widely across classrooms, teachers responded well to training in both print referencing and dialogic …

From Implementation To Impact: Schoolwide Mtss Systems And Student Growth, Amanda Kay Reinarts

All Electronic Theses and Dissertations

Multi-Tiered Systems of Support (MTSS) are widely used in schools to organize academic, behavioral, and social-emotional support for students. Although MTSS is intended to function as a comprehensive schoolwide framework, implementation often becomes fragmented when schools treat it as a standalone tiered-intervention model rather than an integrated system of support, instruction, assessment, and intervention. This fragmentation can limit the effectiveness of MTSS and reduce its impact on student achievement and organizational improvement. This literature review examines how school leaders leverage MTSS as a dynamic, schoolwide system to improve student achievement and organizational effectiveness. This review focuses on leadership structures, organizational …

The Impact Of Special Education Inclusion On The Academic And Social Development Of Students With Disabilities, Sarah Phoebe Phelps

All Electronic Theses and Dissertations

Research of special education inclusion in mainstream classrooms indicated that it can enhance the academic and social development of students with disabilities, and that it could also make a positive impact on the peers without disabilities. However, there is continued concern regarding teacher readiness, resource limitations, and the appropriateness of full inclusion for students with significant disabilities. To create a successful inclusive classroom, teachers need support, proven strategies, and the implementation of the strategies. This literature review will look at the successes and challenges of inclusive education as a whole, and highlight the evolution of exclusive practices to the current …

Pafex: Compiler-Based Floating-Point Exception Detection For Gpu Kernels With Papispecific Software-Defined Events, Samin Islam, Shirley V. Moore, Christoph Q. Lauter

Graduate Student Papers (CS)

As high-performance computing becomes progressively heterogeneous, the dependence upon vendor specific tools for numerical correctness has become an impediment to portability. Although modern GPUs comply with the IEEE 754 standard, the lack of practical native hardware support to raise and handle exceptions (special values like ±∞ or NaN) is a well-known architectural limitation. To embed portable numerical correctness across heterogeneous systems, we propose an architecture agnostic prototype based on LLVM-compiler infrastructure. This framework detects floating-point exceptions in GPU kernels at the Intermediate Representation (IR) level, instrumenting both device code and host code, strictly complying with the 2019 IEEE 754 standard. …

Advancing Food Equity Through Explainable Ai (Xai): Identifying Place-Based Factors And Conditions Of Food Security, Leslie Hoglund, Hyoshin Park

Health Behavior, Policy & Management Faculty Publications

Food behaviors, food security, and their association with socioeconomic factors constitute a critical area of study with implications for public health, economic stability, and social equity. Understanding these relationships are essential for developing effective policies and interventions that promote sustainable, healthy food systems and greater food equity. This paper employs explainable artificial intelligence (XAI) methods to identify key features influencing household food behaviors. The insights gained from the XAI analysis are further utilized in conjunction with inverse reinforcement learning (IRL) to examine expert behaviors related to eating habits satisfaction. The XAI results reveal that household health conditions, spending patterns, and …

Niu Working Papers 2025 - 2026, Northern Illinois University

Working Papers

No abstract provided.

Entry Requirements As Predictors Of Early Academic Success And Student Performance In Undergraduate Occupational Therapy Education, Eileen Du Plooy, Daleen Casteleijn, Denise Franzsen, Gopika Ramkilawon

Journal of Occupational Therapy Education

The selection process for health sciences programs such as occupational therapy is complex, involving a combination of academic and non-academic selection criteria as entry requirements. This study aimed to investigate the predictive value of entry requirement variables on academic performance during the first and second year of an undergraduate occupational therapy program in South Africa. A quantitative, cross-sectional design was utilized, and the sample included 129 first- and second- year occupational therapy students. Data was collected retrospectively through educational data mining of university records and institutional dashboards. The variables analyzed included National Senior Certificate Grade12 (NSC12) grades (Mathematics, Life Sciences, …

A Scholarly Exploration Of Teaching Strategies For Learning About Pediatric Sleep, Laura J. Carpenter, Amanda M. Buono

Journal of Occupational Therapy Education

The occupation of sleep is an area of occupational therapy practice for which many practitioners report a lack of confidence and/or knowledge to properly address. The current study addresses this concern by studying the effects of a learning module on students’ confidence and knowledge to address pediatric sleep. The study used a pre-test, post-test non-experimental design and collected survey responses from 48 entry-level occupational therapy students in three different programs. The lecture portion of the module included content about both assessing and intervening, while the case study emphasized intervention-planning only. Results indicated significant gains in knowledge overall (z = …

The Role Of Department Chairs In Supporting Student Learning Outcomes, Tommy C. Molden Jr

Dissertations

The purpose of this qualitative study was to examine high school department chairs’ perceptions of their role in relation to teacher leadership in achieving student learning outcomes.  The study adds significant implications for department chair training in the context of teacher leadership and the achievement of student learning outcomes.  Further, the study extends the literature on the importance of department chairs’ perceptions of their proficiency for adapting to and institutionalizing the role as teacher leader to increase student achievement.  Additionally, the study identified training strategies and resources that enhance department chair competence in teacher leadership for student achievement of learning …

Study Approaches And Mindset In Predicting Entry-Level Occupational Therapy Student Well-Being: A Multiple Linear Regression Analysis, Elena Wong Espiritu, Katie Eison, Maya Pakulski, Alandry Vise, Alexandria West, Ava Woessner

Journal of Occupational Therapy Education

Academic factors (grades, assignments, study approaches, study strategies, rigorous curriculums, workload) and mindset factors (academic resilience, educational self-efficacy) are known individual factors that impact student well-being. However, if and how these factors in combination predict well-being in occupational therapy students has not been explored. The purpose of this study was to explore study approaches and mindset factors in predicting entry-level occupational therapy student well-being. Entry-level occupational therapy students (master’s and doctorate) from across the United States were recruited (N = 305). Using a quantitative cross-sectional design, data was collected using four standardized assessments and analyzed using a multiple linear regression. …

Expanding Astrobiology: The Case For A Lunar Biorepository, Mary Hagedorn, Lynne R. Parenti, Robert A. Craddock, Pierre Comizzoli, Paula Mabee, Bonnie Meinke, Susan Wolf, John C. Bischof, Rebecca D. Sandlin, Shannon N. Tessier, Mahmet Toner, Baptiste Journaux, Robert Ambrose, Garret Fitzpatrick

Articles

Earth’s resources are essential to support an expanding presence beyond the planet. Yet global conflicts, environmental change, and natural disasters threaten ecosystems and biodiversity, putting the integrity of Earth’s ecosystems and its resources at risk. These converging challenges underscore the urgency to develop innovative strategies to conserve Earth’s biodiversity. Astrobiology—seeking to understand life’s origins, limits, and potential beyond Earth—plays a central role in this effort, helping to preserve Earth’s species while also providing critical assets to explore and work in space. A Lunar Biorepository was proposed to hold cryopreserved samples from among the most critical species on Earth. Here, we …

Machine Learning: Thematic Feature Grouping, And The Magnificent Seven: A Forecasting Analysis, Mirarmia Jalali, Mohammad Najand, Andrew Cohen

Finance Faculty Publications

This study examines the predictability of monthly excess returns for the “Magnificent Seven” U.S. technology firms using machine learning and economically motivated thematic feature grouping. Framed as a focused study of the most systemically consequential equity panel in modern markets—seven firms representing over 30% of the S&P 500—the analysis confronts a small-N, large-P environment where economically structured dimensionality reduction is essential. Using 154 firm-level characteristics categorized into 13 economic themes, we evaluate linear, penalized, tree-based, and neural network models in a small-N, large-P setting. Unrestricted models suffer substantial overfitting and fail to outperform the historical average benchmark out-of-sample. In contrast, …

Natural Resource Rents And Energy Poverty Nexus In Next Eleven Economies, Muhammad Salah Uddin, Ayub Ali, Zobayer Ahmed, Md Nasir Uddin Sikdar, Ahsan Habib, Abdullah Elah Al-Mahde

Finance Faculty Publications

Energy poverty (EP) remains a persistent global challenge with important implications for economic development, public health, and social welfare. While natural resources, particularly oil and gas, are often viewed as key sources of energy access, their effectiveness in mitigating EP remains underexplored in emerging economies. This study examines the relationship between natural resource rents (NRR), specifically oil rents (OR) and natural gas rents (NGR), and energy poverty (EP) in the Next Eleven (N-11) countries from 2000 to 2020. The primary objective is to assess how NRR influences EP at various levels of poverty using the Method of Moments Quantile Regression …

The Molecular Effects Of Microwave Irradiation Upon Antibiotic-Resistant Bacterial Pathogens, Alistair White

Peninsula Dental School Theses

IntroductionAntimicrobial resistance is a global health crisis due to the emergence and spread of multidrug-resistant bacteria, driven by poor antibiotic stewardship, particularly in low to middle income countries where antibiotics can be bought over the counter. Currently, the molecular diagnosis of infections and genomic DNA extraction are both hindered by several factors including, expense, time, technical expertise, and the requirement of a laboratory-based setting. This makes it difficult to extract genomic material at point-of-care preventing the use of rapid molecular methods for the detection of antibiotic resistant genes. Thus, the gold standard for determining the appropriate antibiotics to treat infections …

Design, Synthesis, And Characterization Of Phosphonate-Functionalized Diimide Ligands For Metal-Organic Framework Construction, Kenya Rosas, Jonathan Uribe

Posters - 2026

• Metal–organic frameworks (MOFs) are solid, porous materials composed of metalions reacted with organic linkers

• MOFs are customizable through variations in their metal ions, organic linkers, and the functional groups of the organic linker all yielding a structure with different properties

• MOFs have a variety of applications, ranging from storage and catalysis to drug delivery

• The synthesis and characterization of four phosphonate-based diimide ligands:
  • N,N´-bis(phosphonomethyl)-pyromellitimide (PPMI).
  • N,N´-bis(phosphonobenzyl)-pyromellitimide (PPMI-Ph).
  • N,N´-bis(phosphonomethyl)-3,3′,4,4′-biphenylenediimide (PBDI).
  • N,N´-bis(phosphonobenzyl)-3,3′,4,4′-biphenylenediimide (PBDI-Ph).

• These ligands were then coordinated with zinc or copper metal ions to make MOFs.

Stability Of Brown Carbon And Lipid Monolayers At The Air-Water Interface, Maaike Snider

Student Scholarship

No abstract provided.

Developing A Serious Game-Based Platform To Support Programming Learning, Noven Indra Prasetya, Nia Saurina, Arief Ardiansyah

Journal of Educational Technology Development and Exchange (JETDE)

Programming learning, especially among informatics students, faces significant challenges related to understanding concepts and syntax, as well as low engagement in programming courses. To address these issues, this research developed DolananCoding, a serious game-based learning platform specifically designed for C++ programming learning. The platform integrates a live coding feature, enabling students to write code directly, along with a leaderboard to motivate them through healthy competition. The immersive concept in DolananCoding is designed to provide an interactive and enjoyable learning experience, aiming to enhance students’ engagement, motivation, and learning outcomes in C++ programming. This research aims to test the effectiveness of …

Large Language Model-Based Automated Item Generation In Stem Assessments: Historical Mapping And A Scoping Review Of Empirical Studies, Moses Oluoke Omopekunola

Journal of Educational Technology Development and Exchange (JETDE)

Educational assessments, from low-stakes classroom tests to high-stakes national examinations, require item pools that are valid, fair, and secure. Automated Item Generation (AIG) aims to efficiently produce large pools of calibrated test items. This paper adopts a two-part design: (1) a brief historical mapping situating LLM-based AIG within the broader AIG trajectory; and (2) a scoping review of empirical studies on LLM-based AIG for STEM assessments, published between January 2022 and January 2026. A structured search of ERIC, Lens and OpenAlex yielded 1,267 records; after deduplication and screening, 7 studies were retained for synthesis. In all studies, LLMs were primarily …

Digital Transformation And Artificial Intelligence In Education In Vietnam: A Bibliometric And Systematic Review, Minh-Anh Thi Nguyen, Van-Quynh Ha

Journal of Educational Technology Development and Exchange (JETDE)

Globally, digital transformation (DT) is reshaping education through data-driven innovation, artificial intelligence (AI), and emerging learning technologies. These transformative forces are influencing not only instructional methods but also governance, equity, and sustainability in education. Within this context, the study provides a comprehensive review of DT and AI in Vietnam’s education sector. Combining bibliometric mapping with a systematic content analysis, it synthesizes recent scholarly developments to reveal key research trends, methodological orientations, and conceptual structures. Five thematic clusters are identified, including digital competence, institutional transformation strategies, AI literacy, and learner engagement, potentially reflecting a shift from institutional readiness toward learner-centered innovation. …

Coding, Machine Learning, And Game Engines In Initial Teacher Training, Sara Redondo-Duarte, José Manuel Sáez-López

Journal of Educational Technology Development and Exchange (JETDE)

This study evaluated the integration of coding, visual block programming, game engines, and machine learning (ML) modeling in initial teacher education. The aim was to examine the feasibility of this instructional approach and its association with pre-service teachers’ computational knowledge and attitudes toward programming and artificial intelligence (AI). A one-group pretest-posttest design was implemented with 129 undergraduate students enrolled in Primary Education degree programs at two public universities in Spain. Knowledge of computational concepts was assessed with a 10-item test analyzed using a paired-samples Student’s t-test, while attitudes toward programming and ML were evaluated with two Likert scales analyzed using …

Investigation Of Dean’S Transformational Leadership Profiles And Digital Transformation Maturity In Guangxi Public Higher Vocational Colleges, Lili Ding, Jamilah Binti Ahmad, Yuqiang Luo

Journal of Educational Technology Development and Exchange (JETDE)

Background: As China builds an innovation-driven economy, vocational education provides essential skilled workers for key industries, helping to elevate vocational colleges into crucial centers for talent development and social mobility. In this context, the dean’s transformational leadership may play an important role in supporting institutional digital transformation.

Research Question: How do deans’ transformational leadership domains predict institutional digital transformation maturity across leadership and pedagogy in vocational education?

Methods: A sequential explanatory mixed-methods design combined a faculty survey with semi-structured interviews. Valid survey responses from 30 faculty members were analyzed using descriptive statistics, correlations, and regression, followed by thematic analysis of …

2025-2026 Common Data Set, Southwestern Oklahoma State University

Common Data Sets

This document contains data compiled by the SWOSU Office of Institutional Research for the 2025-2026 academic year.

Unveiling Microplastic Removal And Characteristics In Wastewater From Two Municipal Wastewater Treatment Facilities In Indonesia, Nurul Setiadewi, Prayatni Soewondo, Cynthia Henny

Applied Environmental Research

Wastewater treatment plants (WWTPs) are considered an entrance pathways for microplastic (MP) pollution in aquatic environments. This study reveals the removal and characteristics of MPs in wastewater from two municipal WWTPs in Indonesia. The influent contained 17.1 ± 5.65 particles L-1 (WWTP A) and 15.45 ± 4.31 particles L-1 (WWTP B), whereas the effluent contained 1.41 ± 0.01 and 1.5 ± 0.16 particles L-1. The removal efficiency was 91.75% for WWTP A and 90.32% for WWTP B, with no statistically significant difference (p > 0.05). WWTP A employed advanced treatment units, whereas WWTP B used a conventional pond-based system. MPs were …

Assessment Of The Influence Of Human Activities On The Occurrence Of Forest Fires In Thailand Via Multiple Linear Regression (Mlr), Sittipong Ruktamatakul, Jirarat Insuk, Benjaporn Pinwongpet, Sarisa Ruktametakul, Pornpis Yimprayoon

Applied Environmental Research

Forest fires represent one of the most critical environmental challenges in Thailand, with impacts varying depending on forest type, fuel characteristics, terrain conditions, fire intensity, and the frequency of fire occurrence on the same landscape. While forest fires can contribute to ecosystem degradation, biodiversity loss, and the depletion of natural resources, such effects are not uniformly severe across all forest ecosystems. Understanding the human-induced factors contributing to forest fire occurrence is crucial for developing effective prevention strategies and promoting sustainable forest management. This study aimed to identify the anthropogenic factors influencing forest fire areas in Thailand via multiple linear regression …

Effect Of Chromium Doping On The Uv- And Sunlight-Driven Photocatalytic Performance Of Srtio3, Ro’Ikhatul Jannah, Dianisa Khoirum Sandi, Fahru Nurosyid, Risa Suryana, Didier Fasquelle, Yofentina Iriani

Applied Environmental Research

Chromium (Cr)-doped strontium titanate (SrTiO3, STO) photocatalysts with compositions of SrTi1-xCrxO3 (x = 0, 5, and 10%) were prepared via the coprecipitation method. This study aimed to investigate the effects of Cr doping on structural, morphological, and optical properties. Furthermore, this work aimed to examine the photocatalytic performance of pure and Cr-doped STO against methylene blue (MB) degradation under ultraviolet (UV) and sunlight exposure. X-ray diffraction confirmed the formation of the cubic STO phase and the insertion of the Cr dopant in the STO structures. Furthermore, Cr doping reduced the lattice constant, crystallite size, and average particle size and narrowed …

Comparative Machine Learning Models For Disease Risk Prediction, Mercy Mawusi Agbley

Theses, Dissertations and Capstones

Accurate prediction of disease outcomes is crucial for improving clinical decision-making and enabling early intervention. This study compares the performance of various statistical and machine learning models for clinical risk prediction using two healthcare datasets: diabetic retinopathy and heart disease. The models assessed include Logistic Regression, LASSO, k-Nearest Neighbors (KNN), Support Vector Machines (SVM), Neural Networks, Random Forests, Gradient Boosting Machines (GBM), and a stacked ensemble model. Prior to modeling, datasets were split into train and test sets. Standardization was applied to numeric features whilst categorical features were one-hot encoded. These transformations were later applied to the test set. Principal …