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Bilingualism appears to be related to poor language and reading comprehension in the instructional language (L2). However, in the long term, an early age of second language acquisition (AoA) may produce higher levels of second language skills than a later onset of L2 exposure. Most studies on school-aged second language learners (L2 learners) include children with 3-7 years of second language (L2) exposure. We compared 91 early bilingual (Norwegian and a variety of different native languages) 5th graders with 196 monolingual peers on a range of linguistic skills and their relationships with reading comprehension. All bilingual learners in the sample had been exposed to the instructional language by at least the age of 2. The results, using structural equation modelling and latent variables, show that early bilingual learners' vocabulary, listening comprehension, and reading comprehension are significantly lower than those of monolingual learners. Nevertheless, they have similar levels of knowledge of conjunctions and decoding skills and corresponding predictive patterns from linguistic skills to reading comprehension. We discuss the implications of the findings.

The basic cognitive skill of numeracy is a recognized form of human capital, associated with economic and social well being for individuals and for nations. In this study, we explore how occupational complexity relates to proficiency in numeracy, among adults in full-time employment. We operationalize occupational complexity by constructing three measures of task complexity: complexity with data, complexity with people and complexity with things. Data from the international OECD survey of adult skills, 2012, is employed to investigate both the distribution of these three dimensions of occupational task complexity and how these relate to numeracy in 13 countries. The analysis indicates that data occupational complexity predicts numeracy scores, when controlling for age, gender and educational level. The findings open for a hypothesis that occupational activities may enhance basic skills in adult populations. If elaborated and supported through further studies this finding has practical implications for workplace organization and contributes to theoretical understandings of the development of basic skills in adults.

Increasingly over the past decade, there has been a demand of more thorough documentation of the quality of reading assessments. Yet, available documentation of high-quality measures are often restricted to general framework descriptions providing psychometric information as a token of test quality. In a modern view of validity, understanding what is being measured and how scores are calculated is a prerequisite for good interpretation and use of test scores. The present article aims to document the research and development process of a national adaptive screening test for reading difficulties, in which the envisioned interpretation and use of test scores is guiding the work. Given the mandatory nature of this test the sample consist of 49,828 third grade students aged 8. Significant outcomes from this design process involve detailed information on: (a) choice of sub-tests and item formats, (b) selection of high quality items, (c) choice and design of adaptive model, and finally, a statement on the challenges that are still to bemet for such a test to function optimally. The present paper is among the first to, in an open and detailedmanner, describe the development process as well as qualities and challenges of an adaptive reading screening test for students of this young age. [ABSTRACT FROM AUTHOR]

Previous studies have documented robust relationships between emergent literacy and later reading performance. A growing body of research has also reported associations between motivational factors and reading in early phases of reading development. However, there is less research about cross-lagged relationships between motivational factors and reading skills in beginning readers. To examine relationships between early reading skills, literacy interest and reader self-concept, we tested 1141 children twice during their first year of formal reading instruction in school. Cross-lagged analysis showed strong stability in reading skills and medium stability in literacy interest and reader self-concept over the first school year. We also found bidirectional relationships between reading skills and self-concept and between the motivational components of literacy interest and reader self-concept. In the final part of the article, we address the potential theoretical progress attainable through the use of cross-lagged designs in this field.

The flipped classroom is gaining acceptance in higher education as an alternative to more traditional methods of teaching. In the current study, twelve students in a Norwegian higher education institution were in-depth interviewed about their learning experiences in a two-semester long mathematics course. The first semester was taught using flipped classroom and the second semester using lectures, where both teaching modes contained a substantial amount of active learning. Overall, students report a more positive learning experience and higher engagement in the flipped classroom. The analysis revealed seven categories that the students highlight as especially conducive to their learning; commitment to peers, being recognized, feeling safe, instructor relationship, physical learning environment, learning with peers and using videos to learn new content. The results indicate that the affective dimension of student engagement is particularly prominent when students reflect upon learning in the flipped classroom.

This article describes a study which compares the effectiveness of the flipped classroom relative to the traditional lecture-based classroom. We investigated two implementations of the flipped classroom. The first implementation did not actively encourage cooperative learning, with students progressing through the course at their own pace. With this implementation, student examination scores did not differ between the lecture classes and the flipped classroom. The second implementation was organised with cooperative learning activities. In a randomised control-group pretest-posttest experiment, student scores on a post-test and on the final examination were significantly higher for the flipped classroom group than for the control group receiving traditional lectures. This demonstrates that the classroom flip, if properly implemented with cooperative learning, can lead to increased academic performance.

We present PLSIM, a new method for generating nonnormal data with a pre-specified covariance matrix that is based on coordinate-wise piecewise linear transformations of standard normal variables. In our presentation, the piecewise linear transforms are chosen to match pre-specified skewness and kurtosis values for each marginal distribution. We demonstrate the flexibility of the new method, and an implementation using R software is provided. [ABSTRACT FROM AUTHOR]

Ordinal data in social science statistics are often modeled as discretizations of a multivariate normal vector. In contrast to the continuous case, where SEM estimation is also consistent under non-normality, violation of underlying normality in ordinal SEM may lead to inconsistent estimation. In this article, we illustrate how underlying non-normality induces bias in polychoric estimates and their standard errors. This bias is strongly affected by how we discretize. It is therefore important to consider tests of underlying multivariate normality. In this study we propose a parametric bootstrap test for this purpose. Its performance relative to the test of Maydeu-Olivares is evaluated in a Monte Carlo study. At realistic sample sizes, the bootstrap exhibited substantively better Type I error control and power than the Maydeu-Olivares test in ordinal data with ten dimensions or higher. R code for the bootstrap test is provided. [ABSTRACT FROM AUTHOR]

The assessment of model fit has received widespread interest by researchers in the structural equation modeling literature for many years. Various model fit test statistics have been suggested for conducting this assessment. Selecting an appropriate test statistic in order to evaluate model fit, however, can be difficult as the selection depends on the distributional characteristics of the sampled data, the magnitude of the sample size, and/or the proposed model features. The purpose of this paper is to present a selection procedure that can be used to algorithmically identify the best test statistic and simplify the whole assessment process. The procedure is illustrated using empirical data along with an easy to use computerized implementation. [ABSTRACT FROM AUTHOR]