31 research outputs found

    Graduate Students as Academic Writers: Writing Anxiety, Self-Efficacy, and Emotional Intelligence

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    Researchers interested in psychological factors affecting writers in higher-education institutions, or academic writers, are concerned with internal variables affecting writing productivity; however few empirical studies explore these factors with samples of students who are in the process of earning master’s or doctoral degrees (i.e., graduate students). In this study, we examined writing anxiety, self-efficacy, and emotional intelligence in a sample of graduate students at a large, research-intensive university in the United States. Using a survey, we collected measures on these variables in addition to demographic information from the participants. We then used the measures to descriptively compare groups of students with similar characteristics and to run three regression models to identify which variables best predicted writing anxiety. Our findings indicate self-efficacy is a statistically significant and large predictor of writing anxiety while emotional intelligence (EI) is not, though descriptive data showed moderate effects between EI and first language (i.e., whether or not a student reported English as a first language). In the presence of self-efficacy, gender remained a significant predictor of writing anxiety, while first language did not. We discuss implications for future research and practice focused on helping graduate student academic writers succeed

    Multi-ethnic genome-wide association study for atrial fibrillation

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    Atrial fibrillation (AF) affects more than 33 million individuals worldwide and has a complex heritability. We conducted the largest meta-analysis of genome-wide association studies (GWAS) for AF to date, consisting of more than half a million individuals, including 65,446 with AF. In total, we identified 97 loci significantly associated with AF, including 67 that were novel in a combined-ancestry analysis, and 3 that were novel in a European-specific analysis. We sought to identify AF-associated genes at the GWAS loci by performing RNA-sequencing and expression quantitative trait locus analyses in 101 left atrial samples, the most relevant tissue for AF. We also performed transcriptome-wide analyses that identified 57 AF-associated genes, 42 of which overlap with GWAS loci. The identified loci implicate genes enriched within cardiac developmental, electrophysiological, contractile and structural pathways. These results extend our understanding of the biological pathways underlying AF and may facilitate the development of therapeutics for AF

    A framework for human microbiome research

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    A variety of microbial communities and their genes (the microbiome) exist throughout the human body, with fundamental roles in human health and disease. The National Institutes of Health (NIH)-funded Human Microbiome Project Consortium has established a population-scale framework to develop metagenomic protocols, resulting in a broad range of quality-controlled resources and data including standardized methods for creating, processing and interpreting distinct types of high-throughput metagenomic data available to the scientific community. Here we present resources from a population of 242 healthy adults sampled at 15 or 18 body sites up to three times, which have generated 5,177 microbial taxonomic profiles from 16S ribosomal RNA genes and over 3.5 terabases of metagenomic sequence so far. In parallel, approximately 800 reference strains isolated from the human body have been sequenced. Collectively, these data represent the largest resource describing the abundance and variety of the human microbiome, while providing a framework for current and future studies

    Structure, function and diversity of the healthy human microbiome

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    Author Posting. © The Authors, 2012. This article is posted here by permission of Nature Publishing Group. The definitive version was published in Nature 486 (2012): 207-214, doi:10.1038/nature11234.Studies of the human microbiome have revealed that even healthy individuals differ remarkably in the microbes that occupy habitats such as the gut, skin and vagina. Much of this diversity remains unexplained, although diet, environment, host genetics and early microbial exposure have all been implicated. Accordingly, to characterize the ecology of human-associated microbial communities, the Human Microbiome Project has analysed the largest cohort and set of distinct, clinically relevant body habitats so far. We found the diversity and abundance of each habitat’s signature microbes to vary widely even among healthy subjects, with strong niche specialization both within and among individuals. The project encountered an estimated 81–99% of the genera, enzyme families and community configurations occupied by the healthy Western microbiome. Metagenomic carriage of metabolic pathways was stable among individuals despite variation in community structure, and ethnic/racial background proved to be one of the strongest associations of both pathways and microbes with clinical metadata. These results thus delineate the range of structural and functional configurations normal in the microbial communities of a healthy population, enabling future characterization of the epidemiology, ecology and translational applications of the human microbiome.This research was supported in part by National Institutes of Health grants U54HG004969 to B.W.B.; U54HG003273 to R.A.G.; U54HG004973 to R.A.G., S.K.H. and J.F.P.; U54HG003067 to E.S.Lander; U54AI084844 to K.E.N.; N01AI30071 to R.L.Strausberg; U54HG004968 to G.M.W.; U01HG004866 to O.R.W.; U54HG003079 to R.K.W.; R01HG005969 to C.H.; R01HG004872 to R.K.; R01HG004885 to M.P.; R01HG005975 to P.D.S.; R01HG004908 to Y.Y.; R01HG004900 to M.K.Cho and P. Sankar; R01HG005171 to D.E.H.; R01HG004853 to A.L.M.; R01HG004856 to R.R.; R01HG004877 to R.R.S. and R.F.; R01HG005172 to P. Spicer.; R01HG004857 to M.P.; R01HG004906 to T.M.S.; R21HG005811 to E.A.V.; M.J.B. was supported by UH2AR057506; G.A.B. was supported by UH2AI083263 and UH3AI083263 (G.A.B., C. N. Cornelissen, L. K. Eaves and J. F. Strauss); S.M.H. was supported by UH3DK083993 (V. B. Young, E. B. Chang, F. Meyer, T. M. S., M. L. Sogin, J. M. Tiedje); K.P.R. was supported by UH2DK083990 (J. V.); J.A.S. and H.H.K. were supported by UH2AR057504 and UH3AR057504 (J.A.S.); DP2OD001500 to K.M.A.; N01HG62088 to the Coriell Institute for Medical Research; U01DE016937 to F.E.D.; S.K.H. was supported by RC1DE0202098 and R01DE021574 (S.K.H. and H. Li); J.I. was supported by R21CA139193 (J.I. and D. S. Michaud); K.P.L. was supported by P30DE020751 (D. J. Smith); Army Research Office grant W911NF-11-1-0473 to C.H.; National Science Foundation grants NSF DBI-1053486 to C.H. and NSF IIS-0812111 to M.P.; The Office of Science of the US Department of Energy under Contract No. DE-AC02-05CH11231 for P.S. C.; LANL Laboratory-Directed Research and Development grant 20100034DR and the US Defense Threat Reduction Agency grants B104153I and B084531I to P.S.C.; Research Foundation - Flanders (FWO) grant to K.F. and J.Raes; R.K. is an HHMI Early Career Scientist; Gordon&BettyMoore Foundation funding and institutional funding fromthe J. David Gladstone Institutes to K.S.P.; A.M.S. was supported by fellowships provided by the Rackham Graduate School and the NIH Molecular Mechanisms in Microbial Pathogenesis Training Grant T32AI007528; a Crohn’s and Colitis Foundation of Canada Grant in Aid of Research to E.A.V.; 2010 IBM Faculty Award to K.C.W.; analysis of the HMPdata was performed using National Energy Research Scientific Computing resources, the BluBioU Computational Resource at Rice University

    Embodied learning in a digital world: a systematic review of empirical research in K-12 education

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    There is a widespread assumption that technology-enhanced embodied learning environments, which are grounded on the notion of embodied cognition, can promote learning. The current study reviews the empirical basis of this assumption by examining literature published from 2008 to 2017 which employed technology-enhanced embodied learning environments in K-12 education. Overall, 41 journal articles were included in the review study; these were indexed in four databases (Education Research Complete [via EBSCO], ERIC, JSTOR, and Scopus) as well as in Google Scholar, or were identified via the ancestry method. As part of our analysis, we focused on the type of technology-enhanced embodied environments utilized for educational purposes, the research methods adopted for their evaluation, and the educational contexts in which they were implemented. At the core of this review study, we investigated students’ learning outcomes across the cognitive, affective, and psychomotor domains, while we examined the learning effectiveness of technology-enhanced embodied environments, as compared to other interfaces and forms of instruction. In general, the review revealed positive outcomes about the use of technology-enhanced embodied learning environments in K-12. Most of the reviewed studies were contextualized in STEM education, adopted gesture-based technologies, and evaluated students’ learning using retrospective measures grounded on pre–post-testing. Cognitive outcomes were dominant in the reviewed studies, while the evaluation of affective and psychomotor outcomes received less attention. Most of the reviewed comparative studies reported that students in the embodied learning condition had increased learning gains, when compared to their counterparts in the control or comparison groups. However, these findings should be treated with caution due to a set of methodological concerns that this review identified. We conclude this chapter with a synthesis of our findings in the form of emerged implications and we provide a set of guidelines for future research and practice in the field of technology-enhanced embodied learning environments
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