Evidence of open access of scientific publications in Google Scholar: A large-scale analysis

This article uses Google Scholar (GS) as a source of data to analyse Open Access (OA) levels across all countries and fields of research. All articles and reviews with a DOI and published in 2009 or 2014 and covered by the three main citation indexes in the Web of Science (2,269,022 documents) were selected for study. The links to freely available versions of these documents displayed in GS were collected. To differentiate between more reliable (sustainable and legal) forms of access and less reliable ones, the data extracted from GS was combined with information available in DOAJ, CrossRef, OpenDOAR, and ROAR. This allowed us to distinguish the percentage of documents in our sample that are made OA by the publisher (23.1%, including Gold, Hybrid, Delayed, and Bronze OA) from those available as Green OA (17.6%), and those available from other sources (40.6%, mainly due to ResearchGate). The data shows an overall free availability of 54.6%, with important differences at the country and subject category levels. The data extracted from GS yielded very similar results to those found by other studies that analysed similar samples of documents, but employed different methods to find evidence of OA, thus suggesting a relative consistency among methods.     

Author-level metrics in the new academic profile platforms: The online behaviour of the Bibliometrics community

The new web-based academic communication platforms do not only enable researchers to better advertise their academic outputs, making them more visible than ever before, but they also provide a wide supply of metrics to help authors better understand the impact their work is making. This study has three objectives: a) to analyse the uptake of some of the most popular platforms (Google Scholar Citations, ResearcherID, ResearchGate, Mendeley and Twitter) by a specific scientific community (bibliometrics, scientometrics, informetrics, webometrics, and altmetrics); b) to compare the metrics available from each platform; and c) to determine the meaning of all these new metrics. To do this, the data available in these platforms about a sample of 811 authors (researchers in bibliometrics for whom a public profile Google Scholar Citations was found) were extracted. A total of 31 metrics were analysed. The results show that a high number of the analysed researchers only had a profile in Google Scholar Citations (159), or only in Google Scholar Citations and ResearchGate (142). Lastly, we find two kinds of metrics of online impact. First, metrics related to connectivity (followers), and second, all metrics associated to academic impact. This second group can further be divided into usage metrics (reads, views), and citation metrics. The results suggest that Google Scholar Citations is the source that provides more comprehensive citation-related data, whereas Twitter stands out in connectivity-related metrics.     

Analyzing learners’ engagement and behavior in MOOCs on programming with the Codeboard IDE

Educational technology research and development - Massive Open Online Courses (MOOCs) can be enhanced with the so-called learning-by-doing, designing the courses in a way that the learners are...     

To click or not to click: investigating conflict detection and sourcing in a multiple document hypertext environment

This study investigated whether accessing conflicting claims in other documents by means of hyperlinks embedded within currently read documents may facilitate conflict detection and source-content integration. Norwegian undergraduates (n?=?85) read multiple conflicting documents on a controversial health-related issue, with half of the conflicting claims across documents hyperlinked and the other half not. Moreover, half of the participants were told that they would get more information by clicking on the links (weak prompting condition) while the other half were additionally told that clicking on the links was necessary to get a more complete understanding of the issue (strong prompting condition). Results indicated that the extent to which participants accessed conflicting claims in other documents via the hyperlinks was positively related to their detection of cross-document conflicts as well as their integration of source-content information. A mediational analysis indicated that conflict detection mediated the effect of accessing conflicting claims via the hyperlinks on source-content integration. No relationship was found between the prompting condition and participants’ selection of the hyperlinks. The theoretical significance as well as the practical value of our findings are discussed.

     

A Hypothetical Learning Progression for Quantifying Phenomena in Science

In this article, we report on a three-pronged effort to create a hypothetical learning progression for quantification in science. First, we drew from history and philosophy of science to define the quantification competency and develop hypothetical levels of the learning progression. More specifically, the quantification competency refers to the ability to analyze phenomena through (a) abstracting relevant measurable variables from phenomena and observations, (b) investigating the mathematical relationships among the variables, and (c) conceptualizing scientific ideas that explain the mathematical relationships. The quantification learning progression contains four levels of increasing sophistication: level 1, holistic observation; level 2, attributes; level 3, measurable variables; and level 4, relational complexity. Second, we analyzed the practices in the Next Generation Science Standards for current, largely tacit, assumptions about how quantification develops (or ought to develop) through K-12 education. While several pieces of evidence support the learning progression, we found that quantification was described inconsistently across practices. Third, we used empirical student data from a field test of items in physical and life sciences to illustrate qualitative differences in student thinking that align with levels in the hypothetical learning progression for quantification. By generating a hypothetical learning progression for quantification, we lay the groundwork for future standards development efforts to include this key practice and provide guidance for curriculum developers and instructors in helping students develop robust scientific understanding.

     

Toward Interdisciplinary Learning: Development and Validation of an Assessment for Interdisciplinary Understanding of Global Carbon Cycling

Research in Science Education - This study developed and validated an assessment that measures interdisciplinary understanding using the topic of carbon cycling, the Interdisciplinary Science...     

The impact of exercise training on the lipid peroxidation metabolomic profile and respiratory infection risk in older adults

Aging is associated with oxidative stress that may increase susceptibility to respiratory infections (RIs). We aimed to assess the impact of exercise training on the risk of RIs in older adults and on a targeted metabolomic profile of stress oxidative lipid peroxidation-related metabolites. Methods: In an 8-month clinical trial, 38 participants over 60 years of age were allocated to an exercise group (EG), in which participants underwent 90-min training sessions three times/week(n?=?20), or a control group (CG), in which participants maintained daily physical activities(n?=?18). Daily respiratory symptoms and RIs number and severity were collected. Serum by-products were assessed by comprehensive two-dimensional gas chromatography coupled to mass spectrometry with time of flight analyzer. Serum metabolomic profiling comprised 76 metabolites (alcohols, aldehydes, alkanes, and ketones). Principal components analysis and ANOVA-simultaneous component analysis were used to evaluate the metabolomic profile change. Results: The odds ratio of RIs for the EG was 2.0 CI 95% [0.2;25]. The incidence of RIs was 47% [23;70] in the EG vs. 44%[12;77] in the CG. The metabolomic profiling showed that alkanes and aldehydes classes differed between the EG and the CG before and after intervention. A calibration model showed a relation between the metabolites from four main classes (ketones, alcohols, alkanes and aldehydes) and the prediction of the number of RIs. Conclusion: Moderate exercise training, in older adults, compared with no exercise in controls, did not show a difference in the risk of RIs. A pattern of lipid peroxidation was associated with the number of RIs.