1,720,987 research outputs found
Exploring the impact of gender identity and stereotypes on secondary pupils’ computer science enrolment interest
No full textDespite recent government initiatives, there continues to be a shortage of individuals working in Science, Technology, Engineering and Mathematics (STEM) industries. There is a particular underrepresentation of female STEM workers, with females opting out of STEM fields at each step of the ‘STEM pipeline’, from classroom to boardroom. This thesis identifies and explores the impact of different factors on interest in choosing STEM subjects at post-16 level and how gender identity and stereotypes impact upon computer science enrolment interest. A systematic review of the literature that explores influences on STEM subject choice at post-16 level highlighted thirteen key factors that predict STEM subject choice; these factors could be categorised as either intrinsic or extrinsic to the individual. A fourteenth factor, an individual’s sex, interacted with the majority of these identified factors. This systematic literature review highlights the insufficiency of theories of decision-making in explaining the decision-making that occurs during STEM subject choice, since an individual’s biological sex appears so influential. The empirical study investigates whether gender identity and other well-evidenced influences predict enrolment interest in computer science. It aims to explore whether stereotypical cues in a learning environment affect students’ interest. Year 9 students (n= 168) completed measures assessing gender identity. They were shown either a stereotypical or a non-stereotypical computer science classroom and completed measures assessing their enrolment interest in computer science, belonging, stereotype threat, self-efficacy and utility value. Femininity significantly predicted enrolment interest, and this relationship was mediated by stereotype threat. The stereotypicality of the classroom did not moderate the mediation of stereotype threat on femininity and enrolment interest. This empirical study extends previous research by showing that it is one’s gender identity, rather than simply their sex, that predicts enrolment interest. We highlight the need to consider and challenge stereotypes that continue to exist in relation to subjects such as computer science, in order for all students to feel included
Adolescent data for gender identity, stereotypes, belonging, computer science enrolment interest
No full textData to support Doctoral thesis Exploring the Impact of Gender Identity and Stereotypes on Secondary Pupils’ Computer Science Enrolment Interest. University of Southampton.
This is data collected from adolescents between July 2019 and December 2019. It was collected via iSurvey and has been exported to Excel and cleaned and exported to SPSS.
This dataset contains: Data collected from each participant to assess their enrolment interest in computer science, stereotype threat and feelings of belonging (collected twice, pre and post image viewing) and their gender identity, self-efficacy (expectations of success) and utility value. All data collected using 7-point scales.
Date of data collection: 19.7.19 and 5.12.19
geographic location of data collection: South West of England </span
Exploring the impact of gender identity and stereotypes on secondary pupils’ computer science enrolment interest
No full textThere is an underrepresentation of women working in Science, Technology, Engineering and Mathematics (STEM) industries. Initiatives to encourage greater diversity in STEM have been less successful in computer science. This research investigates whether identification with gender stereotypes (defined as the extent to which one identifies with stereotypical masculine or feminine traits) and other factors predict enrolment interest in computer science and whether stereotypical cues impact on these relationships. British secondary school students were shown either a stereotypical or a non-stereotypical computer science classroom and completed measures assessing their identification with gender stereotypes, enrolment interest, belonging, stereotype threat, self-efficacy and utility value. Femininity significantly predicted lower enrolment interest and this relationship appeared to be mediated by stereotype threat. This study extends previous research by showing that young peoples’ identification with gender stereotypes predicts enrolment interest to some degree. We highlight the need to challenge persistent stereotypes regarding who best ‘fits’ computer science
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Full text link“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
Full text linkWe 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
Full text linkWe 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
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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