Informing the Development of School-Based Strategies to Promote Children\u27s Executive Function Skills: Considerations, Challenges, and Future Directions

In recent years awareness of the importance of executive function (EF) skills for students\u27 academic growth has increased. Research suggests that experience in school promotes EF development; however, recommendations regarding evidence-based practices that educators can use to support EF in their classrooms are limited. Here we outline two main reasons that this may be the case. First, there are significant challenges in the measurement of EF, which have implications for our understanding of how children use EF skills in support of learning in the moment and in real-world settings like the classroom. Second, there is limited direct research on the types of classroom experiences that promote EF. In describing both, we highlight emerging evidence and new methods that are helping us better understand the development of EF and the ways in which school experiences shape this growth, which will ultimately inform the development of school-based strategies to promote these skills

An Experimental Investigation of Contrasting Instructional Conditions on Children’s Developing Memory Skills

Results from observational work conducted in elementary school classrooms have indicated that teachers do not explicitly teach skills for remembering, but it is also apparent that specific aspects of instruction are important for children's mnemonic development. A rich literature has characterized the development of children's mnemonic strategies and highlighted the importance of social contexts, such as the elementary school classroom, for the emergence of these skills. Although linkages between aspects of teachers' language in the classroom and children's memory performance have been documented, these investigations have largely been correlational in nature. Thus, it is not possible to make causal statements about the impact of classroom instruction on children's mnemonic abilities. Given these limitations, this project was designed to increase understanding of the impact of classroom instruction on memory development through the use of an experimental manipulation of the way in which new information was taught to children. Teachers were trained to lead an instructional unit in memory-rich and low-memory modes of instruction. First- and second-grade children participated in 10 days of lessons on a unit entitled Things that Move that varied in terms of the teachers' use of memory-relevant language. In addition, the children were given pretest, posttest, and 1-month follow-up assessments of memory strategy use and content knowledge. The goals of the project included (1) training instructors in the use of contrasting levels of memory-relevant language, (2) exploring relations among measures of children's mnemonic skill and content knowledge, and (3) examining children's performance on these measures as a function of assignment to the memory-rich or low-memory condition. The data from this project suggest that it is possible to train teachers in the use of memory-relevant instructional techniques. In addition, linkages between children's memory strategy use and recall for familiar and content specific items were identified. Although memory-rich instruction was not found to be related to children's performance on memory strategy tasks involving familiar items, children who participated in the memory-rich instructional unit exhibited more sophisticated strategy use in a content-specific memory task and demonstrated higher levels of content-related strategy knowledge than did their peers exposed to low-memory instruction

Associations between developmental changes in error‐related brain activity and executive functions in early childhood

Behavioral evidence indicates that skills associated with children’s cognitive control (e.g., response inhibition and attentional control) undergo rapid development during early childhood. A particularly important time is the transition to elementary school. Yet, at present, relatively little is known about developmental changes in the brain processes linked to cognitive control during this period, including those associated with error monitoring, including the error‐related negativity (ERN) and the error positivity (Pe). Moreover, understanding how ERP correlates of cognitive control relate to behavioral measures of these skills over time is also limited. In the present study, repeated assessments of 4‐ to 6‐year‐old children’s (N = 49, mean age = 5 years 10 months) performance on a go/no‐go task were collected to examine developmental changes in error processing and response inhibition across 6 months. Data revealed the presence of both the ERN and Pe at each time point, but also showed individual differences in the test‐retest associations for each component. Behavioral changes in response inhibition on the go/no‐go task and a standardized measure of attentional control were associated with changes in electrophysiological measures of error processing. Additional analyses comparing children of the same age who had completed the go/no‐go task once to those who participated longitudinally revealed that, with repeated assessments, children exhibited behavioral changes in performance that could be attributed to both development and to the effects of practice, such as strategic accommodation.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142529/1/psyp13040.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142529/2/psyp13040_am.pd

The Causal Impact of Schooling on Children's Development: Lessons for Developmental Science

Entry into formal schooling is a signature developmental milestone for young children and their families and represents an important period of cognitive, social, and emotional development. Until recently, few researchers have attempted to isolate the unique impact of schooling on children’s developmental and academic outcomes. The application of quasiexperimental methods has provided researchers with the tools to examine when and how schooling shapes children’s development. In this article, we summarize three main insights from this work: (a) Schooling produces major, unique changes in children’s growth across a wide range of psychological processes important for learning; (b) the effects of schooling are not universal across all domains; and (c) schooling impacts cognitive processes that are not explicitly taught. We also propose that a deeper look at classroom instruction and brain development can expand our understanding of how schooling influences academic success and positive life outcomes and provide a model for developmental science more broadly

Interactional Structure Applied to the Identification and Generation of Visual Interactive Behavior: Robots that (Usually) Follow the Rules

Peer reviewe

Accelerated gene evolution and subfunctionalization in the pseudotetraploid frog Xenopus laevis

Ancient whole genome duplications have been implicated in the vertebrate and teleost radiations, and in the emergence of diverse angiosperm lineages, but the evolutionary response to such a perturbation is still poorly understood. The African clawed frog Xenopus laevis experienced a relatively recent tetraploidization {approx} 40 million years ago. Analysis of the considerable amount of EST sequence available for this species together with the genome sequence of the related diploid Xenopus tropicalis provides a unique opportunity to study the genomic response to whole genome duplication

Spectro-spatial Profile for Gender Identification using Emotional-based EEG Signals

 Identifying gender has become essential specially to support automatic human-computer interface applications and to customize interactions based on affective responses. The electroencephalogram (EEG) has been adopted for recording the neuronal information as waveforms from the scalp. The objective of this study was twofold. First, to identify genders from four different emotional states using spectral relative power biomarkers. Second, to develop Spectro-spatial profiles that afford additional information for gender identification using emotional-based EEGs. The dataset has been collected from ten healthful volunteer students from the University of Vienna while watching short emotional audio-visual clips of angry, happiness, sadness, and neutral emotions. Wavelet (WT) has been used as a denoising technique, the spectral relative power features of delta (), theta (), alpha (), beta () and gamma () were extracted from each recorded EEG channel. In the subsequent steps, analysis of variance (ANOVA) and Pearson’s correlation analysis were performed to characterize the emotional-based EEG biomarkers towards developing the Spectro-spatial profile to identify gender differences. The results show that the spectral set of features may provide and convey reliable biomarkers for identifying Spectro-spatial profiles from four different emotional states. EEG biomarkers and profiles enable more comprehensive insights into various human behavior effects and as an intervention on the brain. The results revealed that almost high relative powers from all emotional states appear in females compared to males. Particularly,  was the most prominent for anger,  and  were widely observed in happiness,  was the most appears in sadness,  and  were the powers that appears widely in neutral. Moreover, in females, neut was correlated with and _ang, _neut was mostly correlated with _ang. Besides, _neut was correlated with _ang, _neut was correlated with _ang, _neut was mostly correlated with _sad. Moreover, in males, _neut showed a very strong correlation with _sadness whereas _neut was correlated with _hap and _neut was correlated with _hap. Therefore, the proposed system using the WT denoising method, spectral relative power markers, and the spectro-spatial profile plays a crucial role in characterizing the emotional-based EEGs towards gender identification. The classification results were 89.46% for SVM and 90% for the KNN. Therefore, the proposed system using the WT denoising method, spectral relative powers features, SVM, and KNN classifiers were crucial in gender identification and characterizing the emotional EEG signals

Effective EEG channels for emotion identification over the brain regions using differential evolution algorithm

The motivation of this study was to detect the most effective electroencephalogram (EEG) channels for various emotional states of the brain regions (i.e. frontal, temporal, parietal and occipital). The EEGs of ten volunteer participants without health conditions were captured while the participants were shown seven, short, emotional video clips with audio (i.e. anger, anxiety, disgust, happiness, sadness, surprise and neutral). The Savitzky-Golay (SG) filter was adopted for smoothing and denoising the EEG dataset. The spectral features were performed by employing the relative spectral powers of delta (δRP), theta (θRP), alpha (αRP), beta (βRP), and gamma (γRP). The differential evolution-based channel selection algorithm (DEFS_Ch) was computed to find the most suitable EEG channels that have the greatest efficacy for identifying the various emotional states of the brain regions. The results revealed that all seven emotions previously mentioned were represented by at least two frontal and two temporal channels. Moreover, some emotional states could be identified by channels from the parietal region such as disgust, happiness and sadness. Furthermore, the right and left occipital channels may help in identifying happiness, sadness, surprise and neutral emotional states. The DEFS_Ch algorithm raised the linear discriminant analysis (LDA) classification accuracy from 80% to 86.85%, indicating that DEFS_Ch may offer a useful way for reliable enhancement of the detection of different emotional states of the brain regions

Intra-Annual Variation in the Stable Oxygen and Carbon and Trace Element Composition of Sclerosponges

This paper presents data to support the presence of (1) intra-annual signals in the chemical composition (δ18O and Sr/Ca) of the skeletons ofsclerosponges from the Bahamas and (2) variable rates of skeletal accretion. These conclusions are based on data obtained by using a microsampling method for the stable oxygen and carbon isotopes in which material was extracted at a resolution of one sample every 34 μm and a laser microprobe which obtained trace element data every 20 μm (Sr, Mg, and Pb). An age model was established using a combination of changes in the concentration of Pb, the change in the δ13C of the skeleton of the sclerosponges, and U/Th isotopic measurements. These methods yield a mean growth rate of 220 μm/yr but suggest that the growth rate in this particular sclerosponge was not constant. The calculated growth rate is within error identical to that determined by U/Th methods. The variable growth rate was confirmed through spectral analysis of the δ18O and Sr/Ca data that showed peaks corresponding to the annual cycle in these parameters as well as peaks corresponding to growth rates of approximately 128, 212, 270, and 400 μm/yr. The presence of these additional frequencies suggests a growth rate between approximately 100 and 300 μm/yr. These conclusions were supported by modeling of oxygen isotopic data measured on a scleractinian coral as well as model isotope data generated on synthetic time series. These findings have important implications for the use of sclerosponges as proxies of paleoclimate because they emphasize the need for a precise yearly chronology in order that proxy data can be compared with climatic variables. Copyright 2002 by the American Geophysical Union