1,720,988 research outputs found
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
LS-Lab: a Framework for Comparing Curriculum Sequencing Algorithms
No full textCurriculum sequencing is one of the most appealing challenges in Web-based learning environments: the success of a course mainly depends on the system capability to automatically adapt the learning material to the student's educational needs. Here we address the problem of how to compare and to test different curriculum sequencing algorithms in order to reason about them in a self-contained and homogeneous environment. We propose LS-LAB, a framework especially designed for comparing and testing different curriculum sequencing algorithms. LS-LAB has been designed to run different algorithms, each of them provided with its own student model representation: a super student model is able to incrementally include all of them. In this framework, the learning node has to be compliant to the IEEE LOM specifications, while, through a suitable GUI, one can insert new algorithms or run already available ones. We are carrying out the implementation by using a 3-tier Java application technology, in order to make this environment available on the Internet. Finally we show an application example
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
Enhancing Authentic Assessment in Higher Education: leveraging Digital Transformation and Artificial Intelligence
No full textThe COVID-19 pandemic necessitated universities to adopt online assessments, incorporate hybrid
teaching methods, and diversify their evaluation tools. This transformation centered on principles of
authenticity, accessibility, and responsible data management. Technology, artificial intelligence (AI),
and assessment analytics have played pivotal roles in reshaping assessment practices. Automatic
grading tools like Knowledge Tracing have proven valuable for both in-person and online learning.
Nonetheless, ongoing debates revolve around issues of data literacy and striking a balance between
humanistic and technocratic educational approaches. This proposal delves into the realm of eassessment tools, the evolution of assessment objectives, and the challenge of establishing trust in
online assessment processes. Universities are actively working to enhance assessment methods, with a
strong emphasis on authenticity and robust student support. They are also integrating e-assessment
technology to ensure genuine and effective evaluations. The proposal's overarching objective is to
contribute to the ongoing discourse surrounding the promotion of authentic and continuous assessment
within higher education. It aims to explore the opportunities presented by digital transformation, online
learning, and artificial intelligence in this educational context. Additionally, we provide an overview of
a pilot study aimed at investigating the potential application of a multimodal computer vision system to
enhance assessment methods in the university setting and create a supportive learning environment
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
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