Planning middle school schedules for improved attention and achievement

The literature describes research comparing scholastic success in the morning and afternoon in elementary and high schools. The present study examines the relationship between time of day and scholastic performance in middle school. The progress of 850 seventh and eighth grade students in academic subjects taught at different hours of the day was studied. Mean achievement, as expressed in final grades, rose moderately from morning lessons to those conducted at later hours. Significant but temporary declines in achievement were observed immediately after the 10:00 recess and again during the 13:00 lesson. Variance within classes increased sharply during the day. Previous studies attributed such changes to biological rhythms. This paper indicates that many diurnal changes in scholastic performance may be clarified by integration of concepts of biological rhythms with current theories with respect to attention level. Implications of these findings for planning daily school schedules are discussed.     

Committees of division 15 1974–1975

A meta-analysis was undertaken to reexamine near- and far-transfer effects following working-memory training and to consider potential moderators more systematically. Forty-seven studies with 65 group comparisons were included in the meta-analysis. Results showed near-transfer effects to short-term and working-memory skills that were sustained at follow-up with effect sizes ranging from g = 0.37 to g = 0.72 for immediate transfer and g = 0.22 to g = 0.78 for long-term transfer. Far-transfer effects to other cognitive skills were small, limited to nonverbal (g = 0.14) and verbal (g = 0.16) ability and not sustained at follow-up. Several moderators (e.g., duration of training sessions, supervision during training) had an influence on transfer effects, including far-transfer effects. We present principles for how best to improve working memory through training in the narrow-task paradigm and conjecture how best to improve basic cognitive functions in complex activity contexts.     

Relational integration as a predictor of academic achievement

The current study aimed at applying a broad model of cognitive functions to predict performance in science and language courses at school as well as performance in a science course at university. We hypothesized that performance in science courses was predominantly related to the cognitive function known as relational integration, whereas performance in language courses should be best explained by individuals' short-term memory capacity. The sample consisted of 161 German undergraduate students who were asked to complete 33 cognitive tasks. School grades were also obtained. The analyses revealed that relational integration incrementally explained variance in science grades. Short-term memory acted as a predictor of language grades. However, mental speed was also substantially related to language grades. Predicting university exam scores revealed that short-term memory yielded an incremental predictive power. We conclude that academic performance requires different cognitive functions depending on a domain of study.     

Associations of temperament traits and mathematics grades in adolescents are dependent on the rater but independent of motivation and cognitive ability

The current study examines associations between self- and teacher-rated temperament traits (activity, inhibition, negative emotionality, persistence, distractibility, and mood) and mathematics grades. The sample includes 310 ninth grade students (mean age 15.0) from several schools in Finland. Analyses were conducted with multilevel modeling. Except for mood, all temperament traits were associated with math grades independent of motivation and standardized cognitive ability test performance (intelligence). However, some relations were found only for teacher-reports and some only for student-reports. The rater dependent differences are of interest and emphasize a need for data from multiple raters before drawing conclusions on how temperament relates to school grades. The results suggest that temperament should be taken into account in schooling and in teacher education.     

#nowplaying Madonna: a large-scale evaluation on estimating similarities between music artists and between movies from microblogs

Different term weighting techniques such as $TF\cdot IDF$ or BM25 have been used intensely for manifold text-based information retrieval tasks. Their use for modeling term profiles for named entities and subsequent calculation of similarities between these named entities have been studied to a much smaller extent. The recent trend of microblogging made available massive amounts of information about almost every topic around the world. Therefore, microblogs represent a valuable source for text-based named entity modeling. In this paper, we present a systematic and comprehensive evaluation of different term weighting measures, normalization techniques, query schemes, index term sets, and similarity functions for the task of inferring similarities between named entities, based on data extracted from microblog posts. We analyze several thousand combinations of choices for the above mentioned dimensions, which influence the similarity calculation process, and we investigate in which way they impact the quality of the similarity estimates. Evaluation is performed using three real-world data sets: two collections of microblogs related to music artists and one related to movies. For the music collections, we present results of genre classification experiments using as benchmark genre information from allmusic.com . For the movie collection, we present results of multi-class classification experiments using as benchmark categories from IMDb . We show that microblogs can indeed be exploited to model named entity similarity with remarkable accuracy, provided the correct settings for the analyzed aspects are used. We further compare the results to those obtained when using Web pages as data source.     

Development of a magnetic immunosorbent for on-chip preconcentration of amyloid �� isoforms: Representatives of Alzheimer��s disease biomarkers

Determination of amyloid β (Aβ) isoforms and in particular the proportion of the Aβ 1-42 isoform in cerebrospinal fluid (CSF) of patients suspected of Alzheimer’s disease might help in early diagnosis and treatment of that illness. Due to the low concentration of Aβ peptides in biological fluids, a preconcentration step prior to the detection step is often necessary. This study utilized on-chip immunoprecipitation, known as micro-immunoprecipitation (μIP). The technique uses an immunosorbent (IS) consisting of magnetic beads coated with specific anti-Aβ antibodies organized into an affinity microcolumn by a magnetic field. Our goal was to thoroughly describe the critical steps in developing the IS, such as selecting the proper beads and anti-Aβ antibodies, as well as optimizing the immobilization technique and μIP protocol. The latter includes selecting optimal elution conditions. Furthermore, we demonstrate the efficiency of anti-Aβ IS for μIP and specific capture of 5 Aβ peptides under optimized conditions using various subsequent analytical methods, including matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS), capillary electrophoresis, microchip electrophoresis, and immunoblotting. Synthetic Aβ peptides samples prepared in buffer and spiked in human CSF were analyzed. Finally, on-chip immunoprecipitation of Aβ peptides in human CSF sample was performed.     

Multimodal Literacies in Science: Currency, Coherence and Focus

Since the 1990s, researchers have increasingly drawn attention to the multiplicity of representations used in science. This issue of RISE advances this line of research by placing such representations at the centre of science teaching and learning. The authors show that representations do not simply transmit scientific information; they are integral to reasoning about scientific phenomena. This focus on thinking with representations mediates between well-resolved representations and formal reasoning of disciplinary science, and the capacity-limited, perceptually-driven nature of human cognition. The teaching practices described here build on three key principles: Each representation is interpreted through others; natural language is a sign system that is used to interpret a variety of other kinds of representations; and this chain of signs or representations is ultimately grounded in bodily experiences of perception and action. In these papers, the researchers provide examples and analysis of teachers scaffolding students in using representations to construct new knowledge, and in constructing new representations to express and develop their knowledge. The result is a new delineation of the power and the challenges of teaching science with multiple representations.