1,720,962 research outputs found
Optimal Test Design for Estimation of Mean Ability Growth
No full textThe design of an achievement test is crucial for many reasons. This article focuses on a population’s ability growth between school grades. We define design as the allocating of test items concerning the difficulties. The objective is to present an optimal test design method for estimating the mean and percentile ability growth with good precision. We use the asymptotic expression of the variance in terms of the test information. With that criterion for optimization, we propose to use particle swarm optimization to find the optimal design. The results show that the allocation of the item difficulties depends on item discrimination and the magnitude of the ability growth. The optimization function depends on the examinees’ abilities, hence, the value of the unknown mean ability growth. Therefore, we will also use an optimum in-average design and conclude that it is robust to uncertainty in the mean ability growth. A test is, in practice, assembled from items stored in an item pool with calibrated item parameters. Hence, we also perform a discrete optimization using simulated annealing and compare the results to the particle swarm optimization. </p
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Test Design for Mean Ability Growth and Optimal Item Calibration for Achievement Tests
No full textIn this thesis, we examine two topics in the area of educational measurement. The first topic studies how to best design two achievement tests with common items such that a population mean-ability growth is measured as precisely as possible. The second examines how to calibrate newly developed test items optimally. These topics are two optimal design problems in achievement testing. Paper I consist of a simulation study where different item difficulty allocations are compared regarding the precision of mean ability growth when controlling for estimation method and item difficulty span. We take a more theoretical approach on how to allocate the item difficulties in Paper II. We use particle swarm optimization on a multi-objective weighted sum to determine an exact design of the two tests with common items. The outcome relies on asymptotic results of the test information function. The general conclusion of both papers is that we should allocate the common items in the middle of the difficulty span, with the two separate test items on different sides. When we decrease the difference in mean ability between the groups, the ranges of the common and test items coincide more. In the second part, we examine how to apply an existing optimal calibration method and algorithm using data from the Swedish Scholastic Aptitude Test (SweSAT). We further develop it to consider uncertainty in the examinees' ability estimates. Paper III compares the optimal calibration method with random allocation of items to examinees in a simulation study using different measures. In most cases, the optimal design method estimates the calibration items more efficiently. Also, we can identify for what kind of items the method works worse. The method applied in Paper III assumes that the estimated abilities are the true ones. In Paper IV, we further develop the method to handle uncertainty in the ability estimates which are based on an operational test. We examine the asymptotic result and compare it to the case of known abilities. The optimal design using estimates approaches the optimal design assuming true abilities for increasing information from the operational test
Variations on the Author
Get PDF“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
Get PDFWe 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
Get PDFWe 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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