VTechWorks
VTechWorks provides global access to Virginia Tech scholarship, including journal articles, books, theses, dissertations, conference papers, slide presentations, technical reports, working papers, administrative documents, videos, images, and more by faculty, students, and staff. Faculty can deposit items to VTechWorks from Elements, including journal articles covered by the University open access policy. Email vtechworks@vt.edu for help.
Open Access Policy
Virginia Tech's open access policy enables researchers to deposit the accepted version of scholarly articles with no embargo.
Theses and Dissertations
Virginia Tech was first in the world to require ETDs in 1997, and continues to add scans of older theses and dissertations.
Open Textbooks
More than 50 freely available and openly licensed textbooks are among our most downloaded items.
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Recent Submissions
The Effect of Time and Safety on the Retention of Peace Education Concepts
Schupp, Julie Rebecca (Virginia Tech, 2026-03-19)
Peace education programs are widely implemented in schools and community settings worldwide, most often through short-term or time-limited interventions. Although these programs are widely used, research often measures success based on immediate, visible changes rather than on how children retain and express learning over time. This limitation is especially consequential for elementary-aged learners, whose learning develops gradually and is expressed in developmentally specific ways.
This dissertation examines how elementary-aged children engage with and retain peace education concepts following a short-term instructional intervention, with particular attention to time and perceived safety. Using a mixed-methods design, the study integrates survey data and semi-structured interviews collected at multiple time points. Research was conducted in the Khanke Camp in the Kurdistan Region of Iraq, a displacement-affected setting where participants were Yezidi children living in an IDP camp, and Culpeper County, Virginia, a comparatively stable educational environment examined as a smaller, exploratory case.
Findings indicate that short-term peace education programs generate recognition-based engagement and surface alignment with program values but rarely produce sustained conceptual retention over time. Children most often recalled peace education concepts through narrative memory, repetition, and emotionally salient experiences rather than through abstract explanation. Physical safety and institutional stability did not function as straightforward predictors of retention; instead, learning gained salience when program content intersected meaningfully with children's lived experiences and social environments. By conceptualizing learning as a developmentally mediated process of meaning-making and foregrounding recognition alongside articulation, this study challenges evaluation models that equate learning with immediate behavioral change or verbal sophistication. The dissertation contributes a developmentally grounded and contextually responsive framework for evaluating short-term peace education interventions with children, emphasizing the analytic importance of time, context, and ethical restraint.
Computational Models for Resistome Risk Assessment and Environmental Surveillance
Rumi, Monjura Afrin (Virginia Tech, 2026-03-19)
Antibiotic resistance (AR) is a major global threat to human health and economic stability. Without effective intervention, AR is projected to cause substantial loss of life and severe global economic burden. Addressing this challenge requires coordinated national and international efforts that consider all pathways through which antibiotic resistance can emerge and spread. Many public health and regulatory organizations advocate for a One Health approach, which integrates human, animal, and environmental health perspectives. Core components of this approach include the monitoring, risk assessment, and mitigation of antibiotic resistance.
This dissertation addresses all three of these components through the development and application of computational methods for analyzing antibiotic resistance genes (ARGs) in environmental metagenomic data.
In Chapter 2, I presented a risk assessment framework designed to evaluate the potential health risk associated with ARGs at a given location. Using metagenomic sequencing data, this framework computes a resistome risk score that quantifies the level of ARG contamination. The method was shown to be robust across different genome assembly strategies and varying sequencing depths.
In Chapter 3, I applied this framework to 1,326 metagenomic samples collected from 12 distinct environmental types. This large-scale analysis disentangles biological (e.g., ARG relative abundance), ecological (e.g., taxonomic diversity), and technical (e.g., sequencing coverage) factors that influence resistome risk scores. The results demonstrate that risk scores are significantly affected by taxonomic diversity and are strongly correlated with anthropogenic markers.
In Chapter 4, I introduced ARGfore, a forecasting model designed to predict future ARG abundance based on longitudinal surveillance data. Forecasting ARG trends enables earlier detection of emerging resistance risks and supports proactive mitigation strategies.
Finally, in Chapter 5, I described WWTPredictor, a regression-based model that predicts the abundance of metagenomic features—specifically ARGs and microbial taxa—released into the environment from WWTPs based on incoming wastewater data. This model provides a quantitative framework for anticipating environmental discharge risks and supports data-driven decision-making in public health and environmental management.
High-resolution Analysis of Demographic and Socioeconomic Characteristics of Households with Private Wells in the USA
Sear, Caroline Benson (Virginia Tech, 2026-03-19)
Private domestic wells supply drinking water to roughly 15% of the United States population, yet remain largely unregulated, and poorly characterized in terms of the populations they serve. While prior national studies describe broad patterns of domestic well use, they are generally limited to coarse regional resolutions or smaller geographic extents. Here, we present a national, high-resolution analysis of the demographic and socioeconomic profiles of households with private wells in the United States. We integrate geospatial data from a national database of groundwater wells with block- and block group- level demographic information from the 2020 U.S. Census and American Community Survey. Domestic wells are identified and spatially linked to population characteristics including race, educational attainment, and household income, with results aggregated to the county level. We further stratify findings by urban-rural classification to examine patterns across population density gradients. Our analysis revealed substantial spatial variation in the demographic characteristics of well users as compared to nonwell users. Overall, well users are more likely than their public water counterparts to identify as White and to reside in households with higher incomes than county medians. Differences in educational attainment are more variable across states and counties, but are generally modest in magnitude. Across counties, increases in educational attainment and in the proportion of White-identifying well users are associated with higher household incomes. These findings provide a demographic context for domestic well reliance and may support the development of more targeted policies and resources for domestic testing, treatment, and maintenance for populations dependent on private wells.
The TECHtonic, Spring 2026
(Virginia Tech, 2026-03)
The Spring 2026 issue of TECHtonic, the magazine for the Department of Geosciences.
31st Annual Geosciences Student Research Symposium
GSRS Coordinating Committee (Virginia Tech. Department of Geosciences, 2026-03-19)
An abstract book for the 31st GSRS held Thursday, March 19 and Friday March 20, 2026 in Kelly Hall and Derring Hall.