1,720,969 research outputs found

    The Impact Of Cross-Linguistic Orthographic Similarity In Different Learning Contexts: Incidental Vs Intentional Learning

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    Some foreign language words are much easier to learn than others. This can be due to a variety of factors such as concreteness and word type. Cross-linguistic orthographic similarity, whether the combination and position of letters within words conform to native language spelling rules, also plays an important role. Very little is known however, about the effect of cross-linguistic orthographic similarity in different learning contexts. The current research therefore examines this with participants learning Welsh (Study 1) and Polish (Study 2) words through incidental and intentional learning tasks before completing meaning recall and translation recognition tasks. Cross-linguistic orthographic similarity was measured using the comparative judgement approach. Using mixed-effects models, both studies revealed robust effects of both cross-linguistic orthographic similarity and learning contexts. Crucially, the data showed very little learning for cross-linguistically dissimilar items especially in the incidental learning context with implications for teaching and learning

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Variations on the Author

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    “Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship

    Appropriate Similarity Measures for Author Cocitation Analysis

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    We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis

    Dispelling the Myths Behind First-author Citation Counts

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    We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more sophisticated methods

    Author Index

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    Early Study development

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    Learning Words With Unfamiliar Orthography: The Role Of Cognitive Abilities

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    This project investigated the mechanisms supporting the learning of words with familiar and unfamiliar orthographies. Participants took part in a series of learning tasks where FL words where presented orally and in writing along with a picture depicting the meaning of the words. Word learning was then measured through a meaning recall task. Participants also completed a series of memory tasks (short-term and working memory), tasks assessing their phonological and acoustic abilities, as well as a native language vocabulary test. We collected orthographic and phonological familiarity judgments using another sample of participants. The files attached include the individual differences data (predictors.txt), the recall data, the orthographic and phonological judgment data as well as a code book. It also includes the list of stimuli (Welsh words) and the results of the principal component analysis
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