Preprint articles as a tool for teaching data analysis and scientific communication.
Ontology highlight
ABSTRACT:
SUBMITTER: Scheifele LZ
PROVIDER: S-EPMC8691640 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The time it takes for a completed manuscript to be published traditionally can be extremely lengthy. Article publication delay, which occurs in part due to constraints associated with peer review, can prevent the timely dissemination of critical and actionable data associated with new information on rare diseases or developing health concerns such as Zika virus. Preprint servers are open access online repositories housing preprint research articles that enable authors (1) to make their research immediately and freely available and (2) to receive commentary and peer review prior to journal submission. There is a growing movement of preprint advocates aiming to change the current journal publication and peer review system, proposing that preprints catalyze biomedical discovery, support career advancement, and improve scientific communication. While the number of articles submitted to and hosted by preprint servers are gradually increasing, there has been no simple way to identify biomedical research published in a preprint format, as they are not typically indexed and are only discoverable by directly searching the specific preprint server websites. To address this issue, we created a search engine that quickly compiles preprints from disparate host repositories and provides a one-stop search solution. Additionally, we developed a web application that bolsters the discovery of preprints by enabling each and every word or phrase appearing on any web site to be integrated with articles from preprint servers. This tool, search.bioPreprint, is publicly available at http://www.hsls.pitt.edu/resources/preprint.
| S-EPMC4957174 | biostudies-literature
Project description: Not available
| S-EPMC7653533 | biostudies-literature
Project description:This study investigates the effectiveness of the online Flash game Disease Defenders in producing knowledge gains for concepts related to the scientific process. Disease Defenders was specifically designed to model how the scientific process is central to a variety of disciplines and science careers. An additional question relates to the game's ability to shift attitudes toward science. Middle school classes from grades six to eight were assigned to the experimental group (n = 489) or control group (n = 367) and asked to participate in a three-session intervention. The sessions involved completing a pretest, a game play session, and taking a posttest. Students in the experimental group played Disease Defenders while students in the control group played an alternative science game. Results showed a significant increase in mean science knowledge scores for all grades in the experimental group, with sixth grade and seventh grade students gaining more knowledge than eighth grade students. Additionally, results showed a significant positive change in science attitudes only among sixth graders, who also rated their satisfaction with the game more favorably than students in higher grades. No differences in mean test scores were found between genders for science knowledge or science attitudes, suggesting that the game is equally effective for males and females.
| S-EPMC3706166 | biostudies-literature
Project description:Scientific articles often contain relevant geographic information such as where field work was performed or where patients were treated. Most often, this information appears in the full-text article contents as a description in natural language including place names, with no accompanying machine-readable geographic metadata. Automatically extracting this geographic information could help conduct meta-analyses, find geographical research gaps, and retrieve articles using spatial search criteria. Research on this problem is still in its infancy, with many works manually processing corpora for locations and few cross-domain studies. In this paper, we develop a fully automatic pipeline to extract and represent relevant locations from scientific articles, applying it to two varied corpora. We obtain good performance, with full pipeline precision of 0.84 for an environmental corpus, and 0.78 for a biomedical corpus. Our results can be visualized as simple global maps, allowing human annotators to both explore corpus patterns in space and triage results for downstream analysis. Future work should not only focus on improving individual pipeline components, but also be informed by user needs derived from the potential spatial analysis and exploration of such corpora.
| S-EPMC7787447 | biostudies-literature
Project description:The Scientific Teaching (ST) pedagogical framework provides various approaches for science instructors to teach in a way that more closely emulates how science is practiced by actively and inclusively engaging students in their own learning and by making instructional decisions based on student performance data. Fully understanding the impact of ST requires having mechanisms to quantify its implementation. While many useful instruments exist to document teaching practices, these instruments only partially align with the range of practices specified by ST, as described in a recently published taxonomy. Here, we describe the development, validation, and implementation of the Measurement Instrument for Scientific Teaching (MIST), a survey derived from the ST taxonomy and designed to gauge the frequencies of ST practices in undergraduate science courses. MIST showed acceptable validity and reliability based on results from 7767 students in 87 courses at nine institutions. We used factor analyses to identify eight subcategories of ST practices and used these categories to develop a short version of the instrument amenable to joint administration with other research instruments. We further discuss how MIST can be used by instructors, departments, researchers, and professional development programs to quantify and track changes in ST practices.
| S-EPMC5749969 | biostudies-literature
Project description:BACKGROUND:A quantitative trait locus (QTL) is a genomic region that correlates with a phenotype. Most of the experimental information about QTL mapping studies is described in tables of scientific publications. Traditional text mining techniques aim to extract information from unstructured text rather than from tables. We present QTLTableMiner++ (QTM), a table mining tool that extracts and semantically annotates QTL information buried in (heterogeneous) tables of plant science literature. QTM is a command line tool written in the Java programming language. This tool takes scientific articles from the Europe PMC repository as input, extracts QTL tables using keyword matching and ontology-based concept identification. The tables are further normalized using rules derived from table properties such as captions, column headers and table footers. Furthermore, table columns are classified into three categories namely column descriptors, properties and values based on column headers and data types of cell entries. Abbreviations found in the tables are expanded using the Schwartz and Hearst algorithm. Finally, the content of QTL tables is semantically enriched with domain-specific ontologies (e.g. Crop Ontology, Plant Ontology and Trait Ontology) using the Apache Solr search platform and the results are stored in a relational database and a text file. RESULTS:The performance of the QTM tool was assessed by precision and recall based on the information retrieved from two manually annotated corpora of open access articles, i.e. QTL mapping studies in tomato (Solanum lycopersicum) and in potato (S. tuberosum). In summary, QTM detected QTL statements in tomato with 74.53% precision and 92.56% recall and in potato with 82.82% precision and 98.94% recall. CONCLUSION:QTM is a unique tool that aids in providing QTL information in machine-readable and semantically interoperable formats.
| S-EPMC5970438 | biostudies-literature
Project description:Primary scientific literature can be difficult to navigate for anyone unfamiliar with its foreign, formal structure. We sought to create a fun, easy learning tool to help familiarize students of all ages with the structure of a scientific article. Our main learning objective was for the student to realize that science writing is formulaic-that specific information is found in predictable locations within an article-and that, with an understanding of the formula, anyone can comfortably navigate any journal article and accurately predict what to expect to find in each section. To this end, we designed a Journal Article Scavenger Hunt that requires the user to find and identify a series of commonplace features of a primary research article. The scavenger hunt activity is quick and easy to implement, and is adaptable to various ages and settings, including the classroom, lab, and at outreach events. The questions in the scavenger hunt can be scaled in difficulty and specificity to suit the instructor's needs. Over many years of using this activity, we have received positive feedback from students of all ages, from elementary school students to lay adult-learners as well as science teachers themselves. By making the unknown seem predictable and approachable, the scavenger hunt helps a variety of audiences feel more comfortable with science and more confident in their ability to engage directly with the scientific literature. Journal of Microbiology & Biology Education.
| S-EPMC4798794 | biostudies-literature
Project description:Scientific communication poses a challenge: To clearly highlight key conclusions and implications while fully acknowledging the limitations of the evidence. Although these goals are in principle compatible, the goal of conveying complex and variable data may compete with reporting results in a digestible form that fits (increasingly) limited publication formats. As a result, authors' choices may favor clarity over complexity. For example, generic language (e.g., "Introverts and extraverts require different learning environments") may mislead by implying general, timeless conclusions while glossing over exceptions and variability. Using generic language is especially problematic if authors overgeneralize from small or unrepresentative samples (e.g., exclusively Western, middle-class). We present 4 studies examining the use and implications of generic language in psychology research articles. Study 1, a text analysis of 1,149 psychology articles published in 11 journals in 2015 and 2016, examined the use of generics in titles, research highlights, and abstracts. We found that generics were ubiquitously used to convey results (89% of articles included at least 1 generic), despite that most articles made no mention of sample demographics. Generics appeared more frequently in shorter units of the paper (i.e., highlights more than abstracts), and generics were not associated with sample size. Studies 2 to 4 (n = 1,578) found that readers judged results expressed with generic language to be more important and generalizable than findings expressed with nongeneric language. We highlight potential unintended consequences of language choice in scientific communication, as well as what these choices reveal about how scientists think about their data.
| S-EPMC6744883 | biostudies-literature
Project description:We offered four annual professional development workshops called STAR (for Scientific Teaching, Assessment, and Resources) modeled after the National Academies Summer Institute (SI) on Undergraduate Education in Biology. In contrast to the SI focus on training faculty from research universities, STAR's target was faculty from community colleges, 2-yr campuses, and public and private research universities. Because of the importance of community colleges and 2-yr institutions as entries to higher education, we wanted to determine whether the SI model can be successfully extended to this broader range of institutions. We surveyed the four cohorts; 47 STAR alumni responded to the online survey. The responses were separated into two groups based on the Carnegie undergraduate instructional program categories, faculty from seven associate's and associate's-dominant institutions (23) and faculty from nine institutions with primarily 4-yr degree programs (24). Both groups expressed the opinion that STAR had a positive impact on teaching, student learning, and engagement. The two groups reported using techniques of formative assessment and active learning with similar frequency. The mix of faculty from diverse institutions was viewed as enhancing the workshop experience. The present analysis indicates that the SI model for training faculty in scientific teaching can successfully be extended to a broad range of higher education institutions.
| S-EPMC3763006 | biostudies-literature
Project description:BACKGROUND:Social media coverage is increasingly used to spread the message of scientific publications. Traditionally, the scientific impact of an article is measured by the number of citations. At a journal level, this conventionally matures over a 2-year period, and it is challenging to gauge impact around the time of publication. OBJECTIVE:We, therefore, aimed to assess whether Web-based attention is associated with citations and to develop a predictive model that assigns relative importance to different elements of social media coverage: the #SoME_Impact score. METHODS:We included all original articles published in 2015 in a selection of the highest impact journals: The New England Journal of Medicine, The Lancet, the Journal of the American Medical Association, Nature, Cell, and Science. We first characterized the change in Altmetric score over time by taking a single month's sample of recently published articles from the same journals and gathered Altmetric data daily from the time of publication to create a mixed effects spline model. We then obtained the overall weighted Altmetric score for all articles from 2015, the unweighted data for each Altmetric component, and the 2-year citation count from Scopus for each of these articles from 2016 to 2017. We created a stepwise multivariable linear regression model to develop a #SoME_Score that was predictive of 2-year citations. The score was validated using a dataset of articles from the same journals published in 2016. RESULTS:In our unselected sample of 145 recently published articles, social media coverage appeared to plateau approximately 14 days after publication. A total of 3150 articles with a median citation count of 16 (IQR 5-33) and Altmetric score of 72 (IQR 28-169) were included for analysis. On multivariable regression, compared with articles in the lowest quantile of #SoME_Score, articles in the second, third, and upper quantiles had 0.81, 15.20, and 87.67 more citations, respectively. On the validation dataset, #SoME_Score model outperformed the Altmetric score (adjusted R2 0.19 vs 0.09; P<.001). Articles in the upper quantile of #SoME_Score were more than 5 times more likely to be among the upper quantile of those cites (odds ratio 5.61, 95% CI 4.70-6.73). CONCLUSIONS:Social media attention predicts citations and could be used as an early surrogate measure of scientific impact. Owing to the cross-sectional study design, we cannot determine whether correlation relates to causation.
| S-EPMC7195668 | biostudies-literature