Measuring Pupils’ Attitudes Towards Socioscientific Issues

Science & Education - This paper presents the results of a large-scale study to validate a questionnaire that measures pupils’ attitudes towards socioscientific issues (the PASSI...     

A Flexible Latent Class Approach to Estimating Test‐Score Reliability

The latent class reliability coefficient (LCRC) is improved by using the divisive latent class model instead of the unrestricted latent class model. This results in the divisive latent class reliability coefficient (DLCRC), which unlike LCRC avoids making subjective decisions about the best solution and thus avoids judgment error. A computational study using large numbers of items shows that DLCRC also is faster than LCRC and fast enough for practical purposes. Speed and objectivity render DLCRC superior to LCRC. A decisive feature of DLCRC is that it aims at closely approximating the multivariate distribution of item scores, which might render the method suited when test data are multidimensional. A simulation study focusing on multidimensionality shows that DLCRC in general has little bias relative to the true reliability and is relatively accurate compared to LCRC and classical lower bound methods coefficients α and λ2 and the greatest lower bound.     

An SEM Approach for the Evaluation of Intervention Effects Using Pre-Post-Post Designs

A directly applicable latent variable modeling procedure for classical item analysis is outlined. The method allows one to point and interval estimate item difficulty, item correlations, and item-total correlations for composites consisting of categorical items. The approach is readily employed in empirical research and as a by-product permits examining the latent structure of tentative versions of multiple-component measuring instruments. The discussed procedure is straightforwardly utilized with the increasingly popular latent variable modeling software Mplus, and is illustrated on a numerical example.     

Mediation Analysis in a Latent Growth Curve Modeling Framework

This article presents several longitudinal mediation models in the framework of latent growth curve modeling and provides a detailed account of how such models can be constructed. Logical and statistical challenges that might arise when such analyses are conducted are also discussed. Specifically, we discuss how the initial status (intercept) and change (slope) of the putative mediator variable can be appropriately included in the causal chain between the independent and dependent variables in longitudinal mediation models. We further address whether the slope of the dependent variable should be controlled for the dependent variable's intercept to improve the conceptual relevance of the mediation models. The models proposed are illustrated by analyzing a longitudinal data set. We conclude that for certain research questions in developmental science, a multiple mediation model where the dependent variable's slope is controlled for its intercept can be considered an adequate analytical model. However, such models also show several limitations.     

Asking for Help: A Relational Perspective on Help Seeking in the Workplace

In the context of the complexity of today’s organizations, help seeking behavior is considered as an important step to problem solving and learning in organizations. Yet, help seeking has received less attention in organizational literature. To increase the potential impact of help seeking on learning, it is essential to understand which mechanisms affect help seeking. The present study questioned whether the characteristics of the relationships that employees have in the workplace are related to help seeking behavior. This study draws on a social network perspective to investigate the employees’ relationships within their professional network. In particular, the role of accessibility, awareness of expertise, trust, and hierarchy in help seeking was explored. Results indicated that the perceptions of the help provider’s expertise, accessibility and trust were positively associated with the likelihood to seek help, frequency by which help is sought, and perceived quality of the help. Moreover, employees seem more likely to seek help upward from higher status individuals and less likely downward from lower status individuals. Employees perceived the help of higher status individuals as more useful and constructive. These results highlight the importance of investing in the strength of relationships, ensuring the accessibility of expertise and fostering a work environment, in which employees trust and respect each other. Furthermore, the results suggest valuable and promising avenues for future research and practice.     

Inventive progress measured by multi-stage patent citation analysis

Studies of technological change constitute a field of growing importance and sophistication. In this paper we contribute to the discussion with a methodological reflection and application of multi-stage patent citation analysis for the measurement of inventive progress. Investigating specific patterns of patent citation data, we conclude that single-stage citation analysis cannot reveal technological paths or lineages. Therefore, one should also make use of indirect citations and bibliographical coupling. To measure aspects of cumulative inventive progress, we develop a “shared specialization measure” of patent families. We relate this measure to an expert rating of the technological value added in the field of variable valve actuation for internal combustion engines. In sum, the study presents promising evidence for multi-stage patent citation analysis in order to explain aspects of technological change.     

Tracking vocabulary and reading growth in children from lower and higher socioeconomic backgrounds during the transition from primary to secondary education

We examined the relation between socioeconomic status (SES), vocabulary, and reading in middle childhood, during the transition from primary (elementary) to secondary (high) school. Children (N = 279, 163 girls) completed assessments of everyday and curriculum-related vocabulary, (non)word reading, and reading comprehension at five timepoints from age 10 to 13. Piecewise linear mixed-effects models showed significant growth in everyday vocabulary and word reading between every time point. Curriculum vocabulary and reading comprehension showed significant growth during the school year, but not during the summer holidays. There were significant effects of SES on all measures except word reading; yet, SES differences did not widen over time. Our findings motivate targeted reading and vocabulary support for secondary school students from lower SES backgrounds.     

Model method drawing acts as a double-edged sword for solving inconsistent word problems

Educational Studies in Mathematics - Drawing bar diagrams has been shown to improve performance on mathematical word problems wherein the relational keyword is consistent with the required...     

Local Observed‐Score Kernel Equating

Three local observed‐score kernel equating methods that integrate methods from the local equating and kernel equating frameworks are proposed. The new methods were compared with their earlier counterparts with respect to such measures as bias—as defined by Lord's criterion of equity—and percent relative error. The local kernel item response theory observed‐score equating method, which can be used for any of the common equating designs, had a small amount of bias, a low percent relative error, and a relatively low kernel standard error of equating, even when the accuracy of the test was reduced. The local kernel equating methods for the nonequivalent groups with anchor test generally had low bias and were quite stable against changes in the accuracy or length of the anchor test. Although all proposed methods showed small percent relative errors, the local kernel equating methods for the nonequivalent groups with anchor test design had somewhat larger standard error of equating than their kernel method counterparts.     

Improving the Bandwidth Selection in Kernel Equating

We investigate the current bandwidth selection methods in kernel equating and propose a method based on Silverman's rule of thumb for selecting the bandwidth parameters. In kernel equating, the bandwidth parameters have previously been obtained by minimizing a penalty function. This minimization process has been criticized by practitioners for being too complex and that it does not offer sufficient smoothing in certain cases. In addition, the bandwidth parameters have been treated as constants in the derivation of the standard error of equating even when they were selected by considering the observed data. Here, the bandwidth selection is simplified, and modified standard errors of equating (SEEs) that reflect the bandwidth selection method are derived. The method is illustrated with real data examples and simulated data.