10,865 research outputs found
A Bibliometric Study of Instructional Design Journal Articles, 2001-2020
The purpose of this study was to examine instructional design (ID) articles in a broad range of scholarly journals published from 2001 through 2020 to determine the field’s state of publication. By using three bibliometric methods, content analysis, citation analysis, and network analysis, the publication patterns and content of the articles were examined. Specific purposes were to determine the most prolific and highly cited scholars, countries, and journals; to determine trends evident in the bibliometric data; and to compare the differences in coverage and accuracy of the citation indices Web of Science, Scopus, and Google Scholar within the parameters of the study. Bibliometric data for the study were collected by searching each of the three citation indices for articles with the keywords “instructional design” from 160 journals selected for the study based on prior compilations of significant publications in the field of ID. These articles were limited to publications dates 2001-2020 and English language. The searches retrieved 853 articles from the Web of Science, 973 from Scopus, and 8069 from Google Scholar. Bibliometric analyses were applied to the retrieved articles. Results of the analyses identified the most prolific authors as J. J. G. van Merriënboer, F. Paas, and P. A. Kirschner. D. M. Merrill, M. D. Dickey, and T. A. Brush were the most cited xiii authors. Authors in 61 countries published articles matching the study’s parameters. The United States was the most active country in publishing ID articles, followed by the Netherlands, Taiwan, Germany, and Australia. Topics in ID articles changed during the timeframe of the study. In 2001, frequent topics related to the mechanics of instructional design, but in 2020, technology and instructional delivery platforms had become the most frequent topics, perhaps due to the COVID pandemic and the resulting transition from classroom instruction to e-learning and remote instruction. Journals with the highest number of ID articles were Computers in Human Behavior, Instructional Science, Educational Technology & Society, and TechTrends. Educational Technology Research & Development and Computer & Education were also the most highly cited ID journals during this 20-year period. Citation analyses revealed that ID authors tend to repeatedly cite the same authors. Additionally, co-citation and bibliographic coupling are common among ID articles. Numerous instances of co-authorship are evident as well. Scopus and Web of Science were noted to be similar in coverage and accuracy. Google Scholar retrieved many more articles but included more irrelevant items, thus requiring time-consuming efforts from the researcher to identify pertinent items. Google Scholar also contained more errors in names and punctuation. It appears to be best suited for a broad search for information on a topic, while Scopus and Web of Science are more suitable for scholarly research. This study offers insight into the productivity, trends, and emphases of specific ID journals as well as of the ID field in general. The research supports scholarly communications by identifying collaboration patterns and opportunities for researchers and their institutions
Design and update of a classification system : the UCSD map of science
Global maps of science can be used as a reference system to chart career trajectories, the location of emerging research
frontiers, or the expertise profiles of institutes or nations. This paper details data preparation, analysis, and layout performed
when designing and subsequently updating the UCSD map of science and classification system. The original classification
and map use 7.2 million papers and their references from Elsevier’s Scopus (about 15,000 source titles, 2001–2005) and
Thomson Reuters’ Web of Science (WoS) Science, Social Science, Arts & Humanities Citation Indexes (about 9,000 source
titles, 2001–2004)–about 16,000 unique source titles. The updated map and classification adds six years (2005–2010) of WoS
data and three years (2006–2008) from Scopus to the existing category structure–increasing the number of source titles to
about 25,000. To our knowledge, this is the first time that a widely used map of science was updated. A comparison of the
original 5-year and the new 10-year maps and classification system show (i) an increase in the total number of journals that
can be mapped by 9,409 journals (social sciences had a 80% increase, humanities a 119% increase, medical (32%) and
natural science (74%)), (ii) a simplification of the map by assigning all but five highly interdisciplinary journals to exactly one
discipline, (iii) a more even distribution of journals over the 554 subdisciplines and 13 disciplines when calculating the
coefficient of variation, and (iv) a better reflection of journal clusters when compared with paper-level citation data. When
evaluating the map with a listing of desirable features for maps of science, the updated map is shown to have higher
mapping accuracy, easier understandability as fewer journals are multiply classified, and higher usability for the generation
of data overlays, among others
Design and update of a classification system: The UCSD map of science
Global maps of science can be used as a reference system to chart career trajectories, the location of emerging research frontiers, or the expertise profiles of institutes or nations. This paper details data preparation, analysis, and layout performed when designing and subsequently updating the UCSD map of science and classification system. The original classification and map use 7.2 million papers and their references from Elsevier's Scopus (about 15,000 source titles, 2001-2005) and Thomson Reuters' Web of Science (WoS) Science, Social Science, Arts & Humanities Citation Indexes (about 9,000 source titles, 2001-2004)-about 16,000 unique source titles. The updated map and classification adds six years (2005-2010) of WoS data and three years (2006-2008) from Scopus to the existing category structure-increasing the number of source titles to about 25,000. To our knowledge, this is the first time that a widely used map of science was updated. A comparison of the original 5-year and the new 10-year maps and classification system show (i) an increase in the total number of journals that can be mapped by 9,409 journals (social sciences had a 80% increase, humanities a 119% increase, medical (32%) and natural science (74%)), (ii) a simplification of the map by assigning all but five highly interdisciplinary journals to exactly one discipline, (iii) a more even distribution of journals over the 554 subdisciplines and 13 disciplines when calculating the coefficient of variation, and (iv) a better reflection of journal clusters when compared with paper-level citation data. When evaluating the map with a listing of desirable features for maps of science, the updated map is shown to have higher mapping accuracy, easier understandability as fewer journals are multiply classified, and higher usability for the generation of data overlays, among others
Large-scale comparison of bibliographic data sources: Scopus, Web of Science, Dimensions, Crossref, and Microsoft Academic
We present a large-scale comparison of five multidisciplinary bibliographic data sources: Scopus, Web of Science, Dimensions, Crossref, and Microsoft Academic. The comparison considers scientific documents from the period 2008-2017 covered by these data sources. Scopus is compared in a pairwise manner with each of the other data sources. We first analyze differences between the data sources in the coverage of documents, focusing for instance on differences over time, differences per document type, and differences per discipline. We then study differences in the completeness and accuracy of citation links. Based on our analysis, we discuss the strengths and weaknesses of the different data sources. We emphasize the importance of combining a comprehensive coverage of the scientific literature with a flexible set of filters for making selections of the literature.Merit, Expertise and Measuremen
Citatna analiza časopisa 'Stomatološki glasnik Srbije' prema bazama Web of Science, Scopus i Google Scholar
Introduction. For a long time, The Institute for Scientific Information (ISI, now Thomson Scientific, Philadelphia, US) citation databases, available online through the Web of Science (WoS), had an unique position among bibliographic databases. The emergence of new citation databases, such as Scopus and Google Scholar (GS), call in question the dominance of WoS and the accuracy of bibliometric and citation studies exclusively based on WoS data. The aim of this study was to determine whether there were significant differences in the received citation counts for Serbian Dental Journal (SDJ) found in WoS and Scopus databases, or whether GS results differed significantly from those obtained by WoS and Scopus, and whether GS could be an adequate qualitative alternative for commercial databases in the impact assessment of this journal. Material and Methods. The data regarding SDJ citation was collected in September 2010 by searching WoS, Scopus and GS databases. For further analysis, all relevant data of both, cited and citing articles, were imported into Microsoft Access® database. Results. One hundred and fifty-eight cited papers from SDJ and 249 received citations were found in the three analyzed databases. 74% of cited articles were found in GS, 46% in Scopus and 44% in WoS. The greatest number of citations (189) was derived from GS, while only 15% of the citations, were found in all three databases. There was a significant difference in the percentage of unique citations found in the databases. 58% originated from GS, while Scopus and WoS gave 6% and 4% unique citations, respectively. The highest percentage of databases overlap was found between WoS and Scopus (70%), while the overlap between Scopus and GS was 18% only. In case of WoS and GS the overlap was 17%. Most of the SDJ citations came from original scientific articles. Conclusion. WoS, Scopus and GS produce quantitatively and qualitatively different citation counts for SDJ articles. None of the examined databases can provide a comprehensive picture and it is necessary to take into account all three available sources.Uvod. Dugo vremena citatne baze Instituta za naučne informacije u Filadelfiji (ISI; sada Thomson Scientific), dostupne i u elektronskom obliku preko servisa Web of Science (WoS), zauzimale su jedinstvenu poziciju među bibliografskim bazama. Nastanak novih baza i alata koji omogućuju pronalaženje citata, kao što su Scopus i Google Scholar (GS), dovodi u pitanje dominantnost baze WoS i preciznost bibliometrijskih studija zasnovanih isključivo na podacima preuzetim iz ovog izvora. Cilj ovoga rada je bio da se utvrdi da li postoje značajne razlike u broju dobijenih citata časopisa 'Stomatološki glasnik Srbije' (SGS) preko baza WoS i Scopus, odnosno da li se rezultati GS značajno razlikuju od onih dobijenih preko WoS i Scopus i da li GS može biti adekvatna kvalitativna zamena komercijalnim bazama podataka u proceni učinka ovoga časopisa. Materijal i metode rada. Pretraživanjem baza WoS, Scopus i GS prikupljeni su podaci o broju ostvarenih citata za SGS. Svi relevantni podaci, kako citiranih, tako i citirajućih radova, uneti su u Microsoft Access ® bazu podataka i zatim analizirani i upoređivani. Rezultati. U sve tri analizirane baze pronađeno je 158 citiranih radova SGS, kao i 249 primljenih citata. Od ukupnog broja citiranih radova, 74% je citirano na GS, 46% na Scopus, a 44% na WoS. Najveći broj citata (189) potiče iz GS, dok zajednički citati pronađeni u sve tri baze čine samo 15%. Značajna je razlika u procentu jedinstvenih citata među bazama, gde na GS 58% čine jedinstveni citati, a Scopus i WoS imaju 6%, odnosno 4%. Najveće poklapanje u broju i obeležjima pronađenih citata uočeno je između baza WoS i Scopus (70%), zatim između Scopus i GS (18%), pa WoS i GS (17%). Većinu ostvarenih citata SGS (82%) čine originalni naučni radovi. Zaključak. WoS, Scopus i GS daju i kvantitativno i kvalitativno različite podatke o citiranosti SGS. Za prikupljanje kompletnih podataka o citiranosti SGS nijedna od ispitanih baza ne može da pruži sveobuhvatnu sliku, te je neophodno u obzir uzeti sva tri raspoloživa izvora
A Systematic Literature Review With Bibliometric Meta-Analysis Of Deep Learning And 3D Reconstruction Methods In Image Based Food Volume Estimation Using Scopus, Web Of Science And IEEE Database
Purpose- Estimation of food portions is necessary in image based dietary monitoring techniques. The purpose of this systematic survey is to identify peer reviewed literature in image-based food volume estimation methods in Scopus, Web of Science and IEEE database. It further analyzes bibliometric survey of image-based food volume estimation methods with 3D reconstruction and deep learning techniques.
Design/methodology/approach- Scopus, Web of Science and IEEE citation databases are used to gather the data. Using advanced keyword search and PRISMA approach, relevant papers were extracted, selected and analyzed. The bibliographic data of the articles published in the journals over the past twenty years were extracted. A deeper analysis was performed using bibliometric indicators and applications with Microsoft Excel and VOS viewer. A comparative analysis of the most cited works in deep learning and 3D reconstruction methods is performed.
Findings: This review summarizes the results from the extracted literature. It traces research directions in the food volume estimation methods. Bibliometric analysis and PRISMA search results suggest a broader taxonomy of the image-based methods to estimate food volume in dietary management systems and projects. Deep learning and 3D reconstruction methods show better accuracy in the estimations over other approaches. The work also discusses importance of diverse and robust image datasets for training accurate learning models in food volume estimation.
Practical implications- Bibliometric analysis and systematic review gives insights to researchers, dieticians and practitioners with the research trends in estimation of food portions and their accuracy. It also discusses the challenges in building food volume estimator model using deep learning and opens new research directions.
Originality/value- This study represents an overview of the research in the food volume estimation methods using deep learning and 3D reconstruction methods using works from 1995 to 2020. The findings present the five different popular methods which have been used in the image based food volume estimation and also shows the research trends with the emerging 3D reconstruction and deep learning methodologies. Additionally, the work emphasizes the challenges in the use of these approaches and need of developing more diverse, benchmark image data sets for food volume estimation including raw food, cooked food in all states and served with different containers
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Montreal Cognitive Assessment for the diagnosis of Alzheimer's disease and other dementias.
BACKGROUND: Dementia is a progressive syndrome of global cognitive impairment with significant health and social care costs. Global prevalence is projected to increase, particularly in resource-limited settings. Recent policy changes in Western countries to increase detection mandates a careful examination of the diagnostic accuracy of neuropsychological tests for dementia. OBJECTIVES: To determine the diagnostic accuracy of the Montreal Cognitive Assessment (MoCA) at various thresholds for dementia and its subtypes. SEARCH METHODS: We searched MEDLINE, EMBASE, BIOSIS Previews, Science Citation Index, PsycINFO and LILACS databases to August 2012. In addition, we searched specialised sources containing diagnostic studies and reviews, including MEDION (Meta-analyses van Diagnostisch Onderzoek), DARE (Database of Abstracts of Reviews of Effects), HTA (Health Technology Assessment Database), ARIF (Aggressive Research Intelligence Facility) and C-EBLM (International Federation of Clinical Chemistry and Laboratory Medicine Committee for Evidence-based Laboratory Medicine) databases. We also searched ALOIS (Cochrane Dementia and Cognitive Improvement Group specialized register of diagnostic and intervention studies). We identified further relevant studies from the PubMed 'related articles' feature and by tracking key studies in Science Citation Index and Scopus. We also searched for relevant grey literature from the Web of Science Core Collection, including Science Citation Index and Conference Proceedings Citation Index (Thomson Reuters Web of Science), PhD theses and contacted researchers with potential relevant data. SELECTION CRITERIA: Cross-sectional designs where all participants were recruited from the same sample were sought; case-control studies were excluded due to high chance of bias. We searched for studies from memory clinics, hospital clinics, primary care and community populations. We excluded studies of early onset dementia, dementia from a secondary cause, or studies where participants were selected on the basis of a specific disease type such as Parkinson's disease or specific settings such as nursing homes. DATA COLLECTION AND ANALYSIS: We extracted dementia study prevalence and dichotomised test positive/test negative results with thresholds used to diagnose dementia. This allowed calculation of sensitivity and specificity if not already reported in the study. Study authors were contacted where there was insufficient information to complete the 2x2 tables. We performed quality assessment according to the QUADAS-2 criteria.Methodological variation in selected studies precluded quantitative meta-analysis, therefore results from individual studies were presented with a narrative synthesis. MAIN RESULTS: Seven studies were selected: three in memory clinics, two in hospital clinics, none in primary care and two in population-derived samples. There were 9422 participants in total, but most of studies recruited only small samples, with only one having more than 350 participants. The prevalence of dementia was 22% to 54% in the clinic-based studies, and 5% to 10% in population samples. In the four studies that used the recommended threshold score of 26 or over indicating normal cognition, the MoCA had high sensitivity of 0.94 or more but low specificity of 0.60 or less. AUTHORS' CONCLUSIONS: The overall quality and quantity of information is insufficient to make recommendations on the clinical utility of MoCA for detecting dementia in different settings. Further studies that do not recruit participants based on diagnoses already present (case-control design) but apply diagnostic tests and reference standards prospectively are required. Methodological clarity could be improved in subsequent DTA studies of MoCA by reporting findings using recommended guidelines (e.g. STARDdem). Thresholds lower than 26 are likely to be more useful for optimal diagnostic accuracy of MoCA in dementia, but this requires confirmation in further studies.This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1002/14651858.CD010775.pub
Montreal Cognitive Assessment for the detection of dementia
Background: Dementia is a progressive syndrome of global cognitive impairment with significant health and social care costs. Global prevalence is projected to increase, particularly in resource‐limited settings. Recent policy changes in Western countries to increase detection mandates a careful examination of the diagnostic accuracy of neuropsychological tests for dementia.
Objectives: To determine the accuracy of the Montreal Cognitive Assessment (MoCA) for the detection of dementia.
Search methods: We searched MEDLINE, EMBASE, BIOSIS Previews, Science Citation Index, PsycINFO and LILACS databases to August 2012. In addition, we searched specialised sources containing diagnostic studies and reviews, including MEDION (Meta‐analyses van Diagnostisch Onderzoek), DARE (Database of Abstracts of Reviews of Effects), HTA (Health Technology Assessment Database), ARIF (Aggressive Research Intelligence Facility) and C‐EBLM (International Federation of Clinical Chemistry and Laboratory Medicine Committee for Evidence‐based Laboratory Medicine) databases. We also searched ALOIS (Cochrane Dementia and Cognitive Improvement Group specialized register of diagnostic and intervention studies). We identified further relevant studies from the PubMed ‘related articles’ feature and by tracking key studies in Science Citation Index and Scopus. We also searched for relevant grey literature from the Web of Science Core Collection, including Science Citation Index and Conference Proceedings Citation Index (Thomson Reuters Web of Science), PhD theses and contacted researchers with potential relevant data. // Selection criteria: Cross‐sectional designs where all participants were recruited from the same sample were sought; case‐control studies were excluded due to high chance of bias. We searched for studies from memory clinics, hospital clinics, primary care and community populations. We excluded studies of early onset dementia, dementia from a secondary cause, or studies where participants were selected on the basis of a specific disease type such as Parkinson’s disease or specific settings such as nursing homes. //
Data collection and analysis:
We extracted dementia study prevalence and dichotomised test positive/test negative results with thresholds used to diagnose dementia. This allowed calculation of sensitivity and specificity if not already reported in the study. Study authors were contacted where there was insufficient information to complete the 2x2 tables. We performed quality assessment according to the QUADAS‐2 criteria.
Methodological variation in selected studies precluded quantitative meta‐analysis, therefore results from individual studies were presented with a narrative synthesis. // Main results: Seven studies were selected: three in memory clinics, two in hospital clinics, none in primary care and two in population‐derived samples. There were 9422 participants in total, but most of studies recruited only small samples, with only one having more than 350 participants. The prevalence of dementia was 22% to 54% in the clinic‐based studies, and 5% to 10% in population samples. In the four studies that used the recommended threshold score of 26 or over indicating normal cognition, the MoCA had high sensitivity of 0.94 or more but low specificity of 0.60 or less. // Authors' conclusions: The overall quality and quantity of information is insufficient to make recommendations on the clinical utility of MoCA for detecting dementia in different settings. Further studies that do not recruit participants based on diagnoses already present (case‐control design) but apply diagnostic tests and reference standards prospectively are required. Methodological clarity could be improved in subsequent DTA studies of MoCA by reporting findings using recommended guidelines (e.g. STARDdem). Thresholds lower than 26 are likely to be more useful for optimal diagnostic accuracy of MoCA in dementia, but this requires confirmation in further studies
Large-Scale Analysis of the Accuracy of the Journal Classification Systems of Web of Science and Scopus
Journal classification systems play an important role in bibliometric
analyses. The two most important bibliographic databases, Web of Science and
Scopus, each provide a journal classification system. However, no study has
systematically investigated the accuracy of these classification systems. To
examine and compare the accuracy of journal classification systems, we define
two criteria on the basis of direct citation relations between journals and
categories. We use Criterion I to select journals that have weak connections
with their assigned categories, and we use Criterion II to identify journals
that are not assigned to categories with which they have strong connections. If
a journal satisfies either of the two criteria, we conclude that its assignment
to categories may be questionable. Accordingly, we identify all journals with
questionable classifications in Web of Science and Scopus. Furthermore, we
perform a more in-depth analysis for the field of Library and Information
Science to assess whether our proposed criteria are appropriate and whether
they yield meaningful results. It turns out that according to our
citation-based criteria Web of Science performs significantly better than
Scopus in terms of the accuracy of its journal classification system
A review of the literature on citation impact indicators
Citation impact indicators nowadays play an important role in research
evaluation, and consequently these indicators have received a lot of attention
in the bibliometric and scientometric literature. This paper provides an
in-depth review of the literature on citation impact indicators. First, an
overview is given of the literature on bibliographic databases that can be used
to calculate citation impact indicators (Web of Science, Scopus, and Google
Scholar). Next, selected topics in the literature on citation impact indicators
are reviewed in detail. The first topic is the selection of publications and
citations to be included in the calculation of citation impact indicators. The
second topic is the normalization of citation impact indicators, in particular
normalization for field differences. Counting methods for dealing with
co-authored publications are the third topic, and citation impact indicators
for journals are the last topic. The paper concludes by offering some
recommendations for future research
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