2,533 research outputs found
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Who are Rural Students? How Definitions of Rurality Affect Research on College Completion
Given a revived national discourse about rural populations, more educational research on rural students is necessary, including ways that rural students transition to college and the success (or lack thereof) that they experience once there. However, the National Center for Education Statistics (NCES) has changed the definition of rurality used in each iterative dataset over the last few decades, casting doubt on the consistency of what is meant by the term rural. The purpose of this study is to: (a) communicate to the educational research audience various ways of defining rural students, and specifically how NCES has changed their definition of rurality over their last three major data collections; (b) demonstrate how conclusions about rural students’ and their college degree completion may differ based on these alternate NCES definitions; and (c) discuss how this specific example using NCES data relates to the wider landscape of research on rural students. Results show that conclusions about college degree completion change depending on the definition of rurality used for analysis. Therefore, the education research community should consider the options for defining rural students, report transparently about the choices made, consider the sensitivity of results to the definition of rurality, and ultimately build a more robust body of literature concerning rural students’ college success. Gaining definitional clarity will be beneficial, particularly for those who wish to translate their research into practical action for the benefit of rural students
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The Influence of STEM Definitions for Research on Women\u27s College Attainment
Background Prior research has inconsistently operationalized Science, Technology, Engineering, and Math (STEM) fields, presenting an interpretation challenge. A content analysis of 51 quantitative, gender-focused, higher education-oriented, STEM-related studies in the ERIC database published between January 2010 and July 2018 revealed that only 13 articles used an existing STEM definition. In 15, STEM was not explicitly defined, and others defined STEM independently. This wide range of definitions may lead to confusion or misrepresentation of findings for interventions and practices to support women in STEM. To illustrate the issue and prompt recommendations for future research, this study uses data from the United States National Center for Education Statistics’ Education Longitudinal Study (ELS:2002/12) to investigate the connection between STEM definition and the outcome of college degree completion, comparing results by gender for five ways of operationalizing STEM fields. Results We found the size, direction, and significance of the gender gap depended on STEM operationalization. When STEM was defined as high paradigm fields, the odds of women attaining a non-STEM degree were higher than otherwise. When social science fields were included in STEM, there was no statistically significant difference by gender. When looking specifically at fields considered related to science and engineering, the direction of the relationship was reversed. Conclusion While our findings follow expectations about social science fields and gender, it is noteworthy that results regarding STEM degree completion by gender for science and engineering-related fields were opposite those of high paradigm STEM fields. This result highlights that the definition of STEM matters, and inconsistent operationalization in the literature presents an interpretation challenge. We argue the field should strive to find common categorizations of STEM that retain the legitimate variation in how STEM can and should be defined, while providing a basis for consistent comparison. We recommend researchers and practitioners developing research-based practices: 1) interpret research findings understanding potential inconsistency from different STEM operationalizations, 2) explicitly describe STEM operational definitions to enable comparing findings, 3) routinely analyze sensitivity to alternate STEM definitions, and 4) find common STEM categorizations that retain legitimate variation while providing a basis for consistent comparison
Financial Planning for College: Parental Preparation and Capital Conversion
This study explores the conversion of cultural capital into economic capital, and specifically financial capital in the form of parental financial planning for children’s college education, including reported financial preparations and savings. Using data from the Education Longitudinal Study (ELS:2002), logistic regression-based analyses of aspects of cultural capital indicated that parental involvement exhibited the most prevalent relationship with financial planning and the amount saved, and that parents’ expectations, but not their aspirations, corresponded to engagement in financial planning. Findings support the conclusion that some parents convert part of their cultural capital to financial capital in preparation for paying for their child’s college education, perhaps representing a typically hidden facet of social class reproduction
Familial inference: tests for hypotheses on a family of centres
Statistical hypotheses are translations of scientific hypotheses into
statements about one or more distributions, often concerning their centre.
Tests that assess statistical hypotheses of centre implicitly assume a specific
centre, e.g., the mean or median. Yet, scientific hypotheses do not always
specify a particular centre. This ambiguity leaves the possibility for a gap
between scientific theory and statistical practice that can lead to rejection
of a true null. In the face of replicability crises in many scientific
disciplines, significant results of this kind are concerning. Rather than
testing a single centre, this paper proposes testing a family of plausible
centres, such as that induced by the Huber loss function (the Huber family).
Each centre in the family generates a testing problem, and the resulting family
of hypotheses constitutes a familial hypothesis. A Bayesian nonparametric
procedure is devised to test familial hypotheses, enabled by a novel pathwise
optimization routine to fit the Huber family. The favourable properties of the
new test are demonstrated theoretically and experimentally. Two examples from
psychology serve as real-world case studies.Comment: To appear in Biometrik
A framework for automated anomaly detection in high frequency water-quality data from in situ sensors
River water-quality monitoring is increasingly conducted using automated in
situ sensors, enabling timelier identification of unexpected values. However,
anomalies caused by technical issues confound these data, while the volume and
velocity of data prevent manual detection. We present a framework for automated
anomaly detection in high-frequency water-quality data from in situ sensors,
using turbidity, conductivity and river level data. After identifying end-user
needs and defining anomalies, we ranked their importance and selected suitable
detection methods. High priority anomalies included sudden isolated spikes and
level shifts, most of which were classified correctly by regression-based
methods such as autoregressive integrated moving average models. However, using
other water-quality variables as covariates reduced performance due to complex
relationships among variables. Classification of drift and periods of
anomalously low or high variability improved when we applied replaced anomalous
measurements with forecasts, but this inflated false positive rates.
Feature-based methods also performed well on high priority anomalies, but were
also less proficient at detecting lower priority anomalies, resulting in high
false negative rates. Unlike regression-based methods, all feature-based
methods produced low false positive rates, but did not and require training or
optimization. Rule-based methods successfully detected impossible values and
missing observations. Thus, we recommend using a combination of methods to
improve anomaly detection performance, whilst minimizing false detection rates.
Furthermore, our framework emphasizes the importance of communication between
end-users and analysts for optimal outcomes with respect to both detection
performance and end-user needs. Our framework is applicable to other types of
high frequency time-series data and anomaly detection applications
Molecular and comparative analysis of Salmonella enterica Senftenberg from humans and animals using PFGE, MLST and NARMS
<p>Abstract</p> <p>Background</p> <p><it>Salmonella </it>species are recognized worldwide as a significant cause of human and animal disease. In this study the molecular profiles and characteristics of <it>Salmonella enterica </it>Senftenberg isolated from human cases of illness and those recovered from healthy or diagnostic cases in animals were assessed. Included in the study was a comparison with our own sequenced strain of <it>S. </it>Senfteberg recovered from production turkeys in North Dakota. Isolates examined in this study were subjected to antimicrobial susceptibility profiling using the National Antimicrobial Resistance Monitoring System (NARMS) panel which tested susceptibility to 15 different antimicrobial agents. The molecular profiles of all isolates were determined using Pulsed Field Gel Electrophoresis (PFGE) and the sequence types of the strains were obtained using Multi-Locus Sequence Type (MLST) analysis based on amplification and sequence interrogation of seven housekeeping genes (<it>aroC</it>, <it>dnaN</it>, <it>hemD</it>, <it>hisD</it>, <it>purE</it>, <it>sucA</it>, and <it>thrA</it>). PFGE data was input into BioNumerics analysis software to generate a dendrogram of relatedness among the strains.</p> <p>Results</p> <p>The study found 93 profiles among 98 <it>S</it>. Senftenberg isolates tested and there were primarily two sequence types associated with humans and animals (ST185 and ST14) with overlap observed in all host types suggesting that the distribution of <it>S. </it>Senftenberg sequence types is not host dependent. Antimicrobial resistance was observed among the animal strains, however no resistance was detected in human isolates suggesting that animal husbandry has a significant influence on the selection and promotion of antimicrobial resistance.</p> <p>Conclusion</p> <p>The data demonstrates the circulation of at least two strain types in both animal and human health suggesting that <it>S. </it>Senftenberg is relatively homogeneous in its distribution. The data generated in this study could be used towards defining a pathotype for this serovar.</p
College Enhancement Strategies and Socioeconomic Inequality
The study provides new information on the relationships between students’ socioeconomic backgrounds, utilization of college enhancement strategies, and subsequent 4-year college enrollment. Enhancement strategies represent student behaviors used to bolster the competitiveness of a college application, such as Advanced Placement exams and a variety of extracurricular activities. By drawing on two national datasets that span the 1990s (NELS) and the 2000s (ELS), the study uncovers how these relationships have changed during a period marked by escalating demand for college and growing class inequality. The findings provide partial evidence of class adaptation (Alon in Am Soc Rev 74:731–755, 2009) based on the combination of increased use of multiple enhancement strategies (“high overall use”) among higher SES students and increased influence of high overall enhancement strategy use in predicting college enrollment, particularly selective college enrollment. Implications are discussed in terms of the higher education system and pervasive social inequality
Agricultural expansion in African savannas: effects on diversity and composition of trees and mammals
AbstractLand use change (LUC) is the leading cause of biodiversity loss worldwide. However, the global understanding of LUC's impact on biodiversity is mainly based on comparisons of land use endpoints (habitat vs non-habitat) in forest ecosystems. Hence, it may not generalise to savannas, which are ecologically distinct from forests, as they are inherently patchy, and disturbance adapted. Endpoint comparisons also cannot inform the management of intermediate mosaic landscapes. We aim to address these gaps by investigating species- and community-level responses of mammals and trees along a gradient of small scale agricultural expansion in the miombo woodlands of northern Mozambique. Thus, the case study represents the most common pathway of LUC and biodiversity change in the world's largest savanna. Tree abundance, mammal occupancy, and tree- and mammal-species richness showed a non-linear relationship with agricultural expansion (characterised by the Land Division Index, LDI). These occurrence and diversity metrics increased at intermediate LDI (0.3 to 0.7), started decreasing beyond LDI > 0.7, and underwent high levels of decline at extreme levels of agricultural expansion (LDI > 0.9). Despite similarities in species richness responses, the two taxonomic groups showed contrasting β-diversity patterns in response to increasing LDI: increased dissimilarity among tree communities (heterogenisation) and high similarity among mammals (homogenisation). Our analysis along a gradient of landscape-scale land use intensification allows a novel understanding of the impacts of different levels of land conversion, which can help guide land use and restoration policy. Biodiversity loss in this miombo landscape was lower than would be inferred from existing global syntheses of biodiversity-land use relations for Africa or the tropics, probably because such syntheses take a fully converted landscape as the endpoint. As, currently, most African savanna landscapes are a mosaic of savanna habitats and small scale agriculture, biodiversity loss is probably lower than in current global estimates, albeit with a trend towards further conversion. However, at extreme levels of land use change (LDI > 0.9 or < 15% habitat cover) miombo biodiversity appears to be more sensitive to LUC than inferred from the meta-analyses. To mitigate the worst effects of land use on biodiversity, our results suggest that miombo landscapes should retain > 25% habitat cover and avoid LDI > 0.75—after which species richness of both groups begin to decline. Our findings indicate that tree diversity may be easier to restore from natural restoration than mammal diversity, which became spatially homogeneous.</jats:p
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