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Previsão de evasão universitária com aprendizado de máquina
Full text linkStudent dropout is a problem that affects higher education institutions around the world,
having negative impacts on both students and institutions, whether public or private.
It is essential that institutions have tools that help them control evasion, providing
managers with an understanding of the educational expectations of students entering
higher education, in order to improve understanding of this phenomenon. Recent studies
on university dropout prediction using machine learning represent a significant advance in
the area of education. By employing the Cross-Validation Technique (K-Fold) along with a
variety of classification algorithms such as decision trees, logistic regression, random forest,
and support vector machines, among others. This work seeks to understand and anticipate
dropout patterns among students. This approach not only identifies risk factors for
dropout, but also provides valuable information for educational institutions in developing
proactive student retention strategies. By accurately predicting the likelihood of a student
dropping out of their studies, universities can intervene early, offering personalized support
and additional resources to help students overcome academic and personal challenges. To
achieve this, in relation to the student recovery model, LogisticRegression techniques ,
GradientBoosting and XG Boost obtained similar and promising results, above 90% for
graduate F1-Score and dropout F1-score close to 89%. As for the cases of interpretable
algorithms, model for student dismissal, the best results were for the Random Forest and
Decision Tree models with values of 91% for Graduate F1-Score, 84% for dropout F1-score.
This work represents a significant contribution to improving the quality and effectiveness
of educational programs, promoting the retention and success of university students.A evasão de alunos é um problema que afeta as instituições de ensino superior no mundo
todo, tendo impactos negativos tanto para os alunos quanto para as instituições, sejam
elas públicas ou privadas. É essencial, que as instituições tenham ferramentas que os
auxiliem no controle da evasão, proporcionando aos gestores a compreensão das expectativas
educacionais dos alunos que ingressam no ensino superior, a fim de aprimorar a compreensão
desse fenômeno. Os estudos recentes sobre previsão de evasão universitária utilizando
aprendizado de máquina representa um avanço significativo na área da educação. Ao
empregar a Técnica de Validação Cruzada (K-Fold) juntamente com uma variedade de
algoritmos de classificação, como árvores de decisão, regressão logística, floresta aletória e
máquinas de vetores de suporte, entre outros. Este trabalho busca entender e antecipar os
padrões de evasão entre os alunos. Essa abordagem não apenas identifica fatores de risco
para a evasão, mas também fornece informações valiosas para instituições educacionais no
desenvolvimento de estratégias proativas de retenção de alunos. Ao prever com precisão a
probabilidade de um estudante abandonar seus estudos, as universidades podem intervir
precocemente, oferecendo suporte personalizado e recursos adicionais para ajudar os alunos
a superar desafios acadêmicos e pessoais.Para isso, em relação ao modelo de recuperação dos
alunos as técnicas LogisticRegression, GradientBoosting e XG Boost obtiveram resultados
semelhantes e promissores, acima de 90% para F1-Score de formando e F1-score de evasão
próximo a 89%. Já para os casos de algoritmos interpretáveis, modelo para desligamento de
Alunos, os melhores resultados foram para os modelos Random Forest e Decision Tree com
valores de 91% para F1-Score de Formando, 84% para F1-score de evasão. Este trabalho
representa uma contribuição significativa para a melhoria da qualidade e da eficácia dos
programas educacionais, promovendo a retenção e o sucesso dos alunos universitários
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
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
Author Under Sail The Imagination of Jack London, 1893-1902
No full textIn Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Intro -- Title Page -- Copyright Page -- Dedication -- Contents -- Acknowledgments -- Introduction -- 1. Spirit Truth -- 2. From Absorption to Theatricality and Back Again -- 3. "I Will Build a New Present" -- 4. Sons as Authors -- 5. Fathers as Publishers -- 6. The Daughter as Author -- 7. Lovers as Authors -- 8. At Sea with the Family -- 9. Yellow News, Yellow Stories -- 10. The Return Home -- Notes -- Bibliography -- Index -- About Jay WilliamsIn Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Description based on publisher supplied metadata and other sources.Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, YYYY. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries
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