Correlations between the stanford-binet: Fourth edition and the WISC-R with a learning disabled population

The Fourth Edition of the Stanford-Binet and the WISC-R were compared as instruments for assessing the intellectual strengths and weaknesses of students classified as learning disabled in the primary and secondary grades. Results found only a 3.28-point difference (p≥.0001) between the S-B Composite score and the WISC-R Full Scale score. Correlations between the four broad areas of the S-B and the three scales of the WISC-R ranged from .494 (S-B Abstract/Visual Reasoning with WISC-R Verbal) to .920 (S-B Composite with WISC-R Full Scale). All correlations were found to be significant. Implications of the research findings were discussed.     

Digital Module 16: Longitudinal Data Analysis

In this digital ITEMS module, Dr. Jeffrey Harring and Ms. Tessa Johnson introduce the linear mixed effects (LME) model as a flexible general framework for simultaneously modeling continuous repeated measures data with a scientifically defensible function that adequately summarizes both individual change as well as the average response. The module begins with a nontechnical overview of longitudinal data analyses drawing distinctions with cross-sectional analyses in terms of research questions to be addressed. Nuances of longitudinal designs, timing of measurements, and the real possibility of missing data are then discussed. The three interconnected components of the LME model—(1) a model for individual and mean response profiles, (2) a model to characterize the covariation among the time-specific residuals, and (3) a set of models that summarize the extent that individual coefficients vary—are discussed in the context of the set of activities comprising an analysis. Finally, they demonstrate how to estimate the linear mixed effects model within an open-source environment (R). The digital module contains sample R code, diagnostic quiz questions, hands-on activities in R, curated resources, and a glossary.     

Txt msg n school literacy: does texting and knowledge of text abbreviations adversely affect children's literacy attainment?

This paper reports on two studies which investigated the relationship between children's texting behaviour, their knowledge of text abbreviations and their school attainment in written language skills. In Study One, 11–12‐year‐old children provided information on their texting behaviour. They were also asked to translate a standard English sentence into a text message and vice versa. The children's standardised verbal and non‐verbal reasoning scores were also obtained. Children who used their mobiles to send three or more text messages a day had significantly lower scores than children who sent none. However, the children who, when asked to write a text message, showed greater use of text abbreviations (‘textisms’) tended to have better performance on a measure of verbal reasoning ability, which is highly associated with Key Stage 2 (KS2) and 3 English scores. In Study Two, children's performance on writing measures was examined more specifically. Ten to eleven‐year‐old children were asked to complete another English to text message translation exercise. Spelling proficiency was also assessed, and KS2 Writing scores were obtained. Positive correlations between spelling ability and performance on the translation exercise were found, and group‐based comparisons based on the children's writing scores also showed that good writing attainment was associated with greater use of textisms, although the direction of this association is nor clear. Overall, these findings suggest that children's knowledge of textisms is not associated with poor written language outcomes for children in this age range.     

BE COOL! a digital learning environment to challenge and socially include gifted learners

Educational technology research and development - This paper describes the development of the BE COOL! learning environment that gives all children, gifted and non-gifted, the opportunity to learn...     

Teachers’ Integration of Scientific and Engineering Practices in Primary Classrooms

The Next-Generation Science Standards (NGSS) challenge primary teachers and students to work and think like scientists and engineers as they strive to understand complex concepts. Teachers and teacher educators can leverage what is already known about inquiry teaching as they plan instruction to help students meet the new standards. This cross-case analysis of a multiple case study examined teacher practices in the context of a semester-long professional development course for elementary teachers. We reviewed lessons and teacher reflections, examining how kindergarten and first grade teachers incorporated NGSS scientific and engineering practices during inquiry-based instruction. We found that most of the teachers worked with their students on asking questions; planning and carrying out investigations; analyzing and interpreting data, using mathematics and computational thinking; and obtaining, evaluating and communicating information. Teachers faced challenges in supporting students in developing their own questions that could be investigated and using data collection strategies that aligned with students’ development of number sense concepts. Also, some teachers overemphasized the scientific method and lacked clarity in how they elicited and responded to student predictions. Discussion focuses on teacher supports that will be needed as states transition to NGSS.