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The objective of this study was to identify biomechanical predictors for accuracy and speed of the wrist shot in floorball, comparing two different starting feet positions.Ten floorball players performed 2 series of 10 stationary wrist shots, in 2 different positions (feet at a right angle to the end of the stick, oriented towards a target and feet parallel to the end of the stick and to the target). A 12-camera motion capture system, tracking reflective markers on key landmarks, was used to record participant and stick kinematics. Accuracy of the shot was quantified by distance of impact from target centre. Player gaze was approximated from head position.Shot accuracy was significantly better (P = 0.007) when feet were at right angle (0.22 [0.14] m) than when they were parallel (0.27 [0.20] m). Ball speed was no significantly different (P = 0.485) between the right angle position (23.50 [17.52] m · s?1) and the parallel position (23.50 [17.95] m · s?1). Between self-selected position and imposed position, there was no significant difference. Players looking at the target during shooting had greater accuracy. Regression models suggested that ball speed was mainly influenced, in both positions, by the flexion of the supporting leg (ankle, knee and hip), by the rotation of the hip and of the trunk, especially for the spine angles, and by the rotation and abduction–adduction movements of the wrist of the hand on the top of the stick. The comparison between players showed important differences in these technical skills. 相似文献
22.
The aims of the study presented in this paper were twofold:
to analyse if and how pupils who received some kind of special education differed from students who received no such support with respect to different self-concept and ability factors; and
to investigate substantive consequences of different theoretical bases for statistical modelling.
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24.
Bengt Persson 《欧洲特需教育杂志》2013,28(4):337-347
According to Swedish legislation as well as laws pertaining to disabled citizens, Swedish schools are to be accessible for all children and adolescents. This implies that disabilities of any type must not be allowed to prevent students from completing their schooling on their own terms. The purpose of this research was to study the degree to which the Swedish school is accessible for all students. A total 200 professionals and politicians were interviewed alongside more than 30 upper secondary school students. The results show that the ambition level is high with regard to adapting educational programmes for the disabled student group, especially in the rhetoric of politicians and civil servants. However, in practice, teachers and head teachers have considerably more difficulty in delivering to students satisfactory schooling. This is often due to conflict between the striving for inclusion and the difficulty adapting learning environments during everyday classroom instruction. By use of institutional theory the study demonstrates that intentions as described of responsible politicians are altered in the system when confronted with the institutional reality. Schools’ meeting the natural variation of difference in the student group causes complications in educational work in which various solutions are attempted. When educational differentiation is found wanting in attempts to meet students’ various needs, various types of special solutions are sought, which have the objective of reducing heterogeneity among the students. This type of organisational differentiation seems accepted and legitimised where it concerns students having various kinds of school‐related difficulties, while seeming to create a disadvantage for some other students. One should understand this as thought coercion, where pressure from professionals in schools leaves little room for other strategies and in which the concept of the inclusive school is challenged. 相似文献
25.
Mixture modeling is a widely applied data analysis technique used to identify unobserved heterogeneity in a population. Despite mixture models' usefulness in practice, one unresolved issue in the application of mixture models is that there is not one commonly accepted statistical indicator for deciding on the number of classes in a study population. This article presents the results of a simulation study that examines the performance of likelihood-based tests and the traditionally used Information Criterion (ICs) used for determining the number of classes in mixture modeling. We look at the performance of these tests and indexes for 3 types of mixture models: latent class analysis (LCA), a factor mixture model (FMA), and a growth mixture models (GMM). We evaluate the ability of the tests and indexes to correctly identify the number of classes at three different sample sizes (n = 200, 500, 1,000). Whereas the Bayesian Information Criterion performed the best of the ICs, the bootstrap likelihood ratio test proved to be a very consistent indicator of classes across all of the models considered. 相似文献
26.
Herbert W. Marsh Bengt Muthén Tihomir Asparouhov Oliver Lüdtke Alexander Robitzsch Alexandre J. S. Morin 《Structural equation modeling》2013,20(3):439-476
This study is a methodological-substantive synergy, demonstrating the power and flexibility of exploratory structural equation modeling (ESEM) methods that integrate confirmatory and exploratory factor analyses (CFA and EFA), as applied to substantively important questions based on multidimentional students' evaluations of university teaching (SETs). For these data, there is a well established ESEM structure but typical CFA models do not fit the data and substantially inflate correlations among the nine SET factors (median rs = .34 for ESEM, .72 for CFA) in a way that undermines discriminant validity and usefulness as diagnostic feedback. A 13-model taxonomy of ESEM measurement invariance is proposed, showing complete invariance (factor loadings, factor correlations, item uniquenesses, item intercepts, latent means) over multiple groups based on the SETs collected in the first and second halves of a 13-year period. Fully latent ESEM growth models that unconfounded measurement error from communality showed almost no linear or quadratic effects over this 13-year period. Latent multiple indicators multiple causes models showed that relations with background variables (workload/difficulty, class size, prior subject interest, expected grades) were small in size and varied systematically for different ESEM SET factors, supporting their discriminant validity and a construct validity interpretation of the relations. A new approach to higher order ESEM was demonstrated, but was not fully appropriate for these data. Based on ESEM methodology, substantively important questions were addressed that could not be appropriately addressed with a traditional CFA approach. 相似文献
27.
This study introduces a two-part factor mixture model as an alternative analysis approach to modeling data where strong floor effects and unobserved population heterogeneity exist in the measured items. As the names suggests, a two-part factor mixture model combines a two-part model, which addresses the problem of strong floor effects by decomposing the data into dichotomous and continuous response components, with a factor mixture model, which explores unobserved heterogeneity in a population by establishing latent classes. Two-part factor mixture modeling can be an important tool for situations in which ordinary factor analysis produces distorted results and can allow researchers to better understand population heterogeneity within groups. Building a two-part factor mixture model involves a consecutive model building strategy that explores latent classes in the data for each part as well as a combination of the two-part. This model building strategy was applied to data from a randomized preventive intervention trial in Baltimore public schools administered by the Johns Hopkins Center for Early Intervention. The proposed model revealed otherwise unobserved subpopulations among the children in the study in terms of both their tendency toward and their level of aggression. Furthermore, the modeling approach was examined using a Monte Carlo simulation. 相似文献
28.
Achievement modeling is carried out in groups of students characterized by heterogeneous instructional background. Extensions of item response theory models incorporate variables reflecting different amounts of opportunity-to-leam (OTL). The effects of these OTL variables are studied with respect to their influence on both the latent trait and the item performance directly. Such direct effects may reflect instructionally sensitive items. U.S. eighth-grade mathematics data from the Second International Mathematics Study are analyzed. Here, the same test is taken by students enrolled in typical instruction and students enrolled in elementary algebra classes. It is shown that the new analysis provides a more detailed way to examine the influence of instruction on responses to test items than does conventional item response theory. 相似文献
29.
Bengt O. Muthén 《Journal of Educational Measurement》1991,28(4):338-354
This article analyzes mathematics achievement data from the Second International Mathematics Study (SIMS; Crosswhite, Dossey, Swafford, McKnight, & Cooney, 1985) in which U.S. students are measured at the beginning and end of eighth grade. The aim of the article is to address some substantive analysis questions in the SIMS data and show the potential of multilevel factor analysis methodology. Issues related to between- and within-class decomposition of achievement variance and the change of this decomposition over the course of the eighth grade are studied. As a starting point, random effects ANOVA is considered for each achievement score. Each score contains a large amount of measurement error. The effects of unreliability on variance decomposition are shown with the help of a multilevel factor analysis model. Unreliability has severely distorting effects on this type of ANOVA while multilevel factor analysis gives results corresponding to what would be obtained with perfectly reliable scores. 相似文献
30.
In this article we describe a structural equation modeling (SEM) framework that allows nonnormal skewed distributions for the continuous observed and latent variables. This framework is based on the multivariate restricted skew t distribution. We demonstrate the advantages of skewed SEM over standard SEM modeling and challenge the notion that structural equation models should be based only on sample means and covariances. The skewed continuous distributions are also very useful in finite mixture modeling as they prevent the formation of spurious classes formed purely to compensate for deviations in the distributions from the standard bell curve distribution. This framework is implemented in Mplus Version 7.2. 相似文献