1,720,966 research outputs found
Enhance learning experience using technology in class
Full text linkMajority of the students now have access to portable devices that can provide countless information at their fingertips through various resources such as learning games and interactive applications. These resources allow immediate communication and interaction between students and instructors. In this study we measured students’ perception of the effectiveness of using technological tools in lectures on their academic performance and their level of understanding of the course topic. Students, who have taken statistics courses at the University of Toronto completed a survey that identified variables connected to their perception of using technology in class and the ways in which, in turn, their learning experiences were enhanced. The results of the survey showed that a significant portion of students perceived that they gained a deeper level of understanding of lecture contents when technology was used in class. Thus, based on the results of our study, we recommend that instructors take advantage of using technology in their class in order to create a more immersive learning environment for their students than using traditional instructional methodsPeer Reviewe
On New Constructive Tools in Bayesian Nonparametric Inference
No full textThe Bayesian nonparametric inference requires the construction of priors on infinite dimensional spaces such as the space of cumulative distribution functions and the space of cumulative hazard functions. Well-known priors on the space of cumulative distribution functions are the Dirichlet process, the two-parameter Poisson-Dirichlet process and the beta-Stacy process. On the other hand, the beta process is a popular prior on the space of cumulative hazard functions. This thesis is divided into three parts. In the first part, we tackle the problem of sampling from the above mentioned processes. Sampling from these processes plays a crucial role in many applications in Bayesian nonparametric inference. However, having exact samples from these processes is impossible. The existing algorithms are either slow or very complex and may be difficult to apply for many users. We derive new approximation techniques for simulating the above processes. These new approximations provide simple, yet efficient, procedures for simulating these important processes. We compare the efficiency of the new approximations to several other well-known approximations and demonstrate a significant improvement. In the second part, we develop explicit expressions for calculating the Kolmogorov, Levy and Cramer-von Mises distances between the Dirichlet process and its base measure. The derived expressions of each distance are used to select the concentration parameter of a Dirichlet process. We also propose a Bayesain goodness of fit test for simple and composite hypotheses for non-censored and censored observations. Illustrative examples and simulation results are included. Finally, we describe the relationship between the frequentist and Bayesian nonparametric statistics. We show that, when the concentration parameter is large, the two-parameter Poisson-Dirichlet process and its corresponding quantile process share many asymptotic pr operties with the frequentist empirical process and the frequentist quantile process. Some of these properties are the functional central limit theorem, the strong law of large numbers and the Glivenko-Cantelli theorem
How to Measure Evidence and Its Strength: Bayes Factors or Relative Belief Ratios?
Full text linkBoth the Bayes factor and the relative belief ratio satisfy the principle of
evidence and so can be seen to be valid measures of statistical evidence.
Certainly Bayes factors are regularly employed. The question then is: which of
these measures of evidence is more appropriate? It is argued here that there
are questions concerning the validity of a current commonly used definition of
the Bayes factor based on a mixture prior and, when all is considered, the
relative belief ratio has better properties as a measure of evidence. It is
further shown that, when a natural restriction on the mixture prior is imposed,
the Bayes factor equals the relative belief ratio obtained without using the
mixture prior. Even with this restriction, this still leaves open the question
of how the strength of evidence is to be measured. It is argued here that the
current practice of using the size of the Bayes factor to measure strength is
not correct and a solution to this issue is presented. Several general
criticisms of these measures of evidence are also discussed and addressed
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
Understanding Gender Differences in Academic Achievement Among Engineering Students
No full textIn recent years, a noticeable shift has occurred in academic performance, with females consistently outperforming males in mathematical engineering courses. To investigate the factors contributing to this trend, we conducted a comprehensive survey at a main university in UAE. Analyzing data from 431 engineering students, we found that the time spent studying outside the classroom plays a pivotal role, evidenced by a statistically significant p-value of 0.04, contributing to the gender-based performance disparity. Building upon these findings, we propose short-term solutions that instructors and universities can implement promptly to address this issue. This study underscores the importance of ongoing institution-level, student-focused research to identify and address gender-based performance differences, ultimately leading to the reduction of this educational gap. The findings also offer insights into the theoretical understanding of gendered academic engagement, particularly in emerging educational systems.
Keywords: Academic Performance, Gender Disparities, Mathematical Engineering, Student Success, Study Habits, Undergraduate
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