The Effect of Hints and Model Answers in a Student-Controlled Problem-Solving Program for Secondary Physics Education

Many students experience difficulties in solving applied physics problems. Most programs that want students to improve problem-solving skills are concerned with the development of content knowledge. Physhint is an example of a student-controlled computer program that supports students in developing their strategic knowledge in combination with support at the level of content knowledge. The program allows students to ask for hints related to the episodes involved in solving a problem. The main question to be answered in this article is whether the program succeeds in improving strategic knowledge by allowing for more effective practice time for the student (practice effect) and/or by focusing on the systematic use of the available help (systematic hint-use effect). Analysis of qualitative data from an experimental study conducted previously show that both the expected effectiveness of practice and the systematic use of episode-related hints account for the enhanced problem-solving skills of students

Developing classroom formative assessment in dutch primary mathematics education

In the last two decades Dutch primary school students scored below expectation in international mathematics tests. An explanation for this may be that teachers fail to adequately assess their students’ understanding of learning goals and provide timely feedback. To improve the teachers’ formative assessment practice, researchers, curriculum experts and teachers worked together to develop a model for classroom formative assessment (CFA). In three pilot studies, six teachers from three different schools implemented the CFA-model and evaluated its feasibility together with the researchers by means of checklists. The CFA-model was primarily changed with regard to the assessment techniques. Teachers indicated that classroom management and preparation time were preconditions for an optimal implementation. Analysis of covariance was used to explore students’ learning outcomes. The results showed that a correct implementation of the CFA-model might result in the enhancement of students’ mathematical performance. The implications of the three pilots for the implementation of the CFA-model on a larger scale are discussed

The relationship between primary school leaders' utilization of distributed leadership and teachers' capacity to change

Although it is generally known that distributed leadership is relevant for reinforcing teachers' capacity to change, how leadership roles are distributed among teachers largely depends on how principals perceive distributed leadership. Specifying principals' perceptions and how these are related to teachers' capacity to change leads to theories about the knowledge and beliefs of leaders with regard to distributed leadership that are crucial for achieving educational change as a team. Combining questionnaire data from 787 Dutch primary school teachers and interview data from 58 principals in a parallel mixed methods design, this study shows differences in how school leaders distribute leadership roles. In addition, the results indicate that several aspects of teachers' capacity to change, namely, joint work, collegial support, knowledge sharing, self-efficacy and their internalization of school goals, are more present in schools in which school leaders distribute leadership among teachers than in schools in which they do not

Testing the effectiveness of classroom formative assessment in Dutch primary mathematics education

Classroom formative assessment (CFA) is considered to be a fundamental part of effective teaching, as it is presumed to enhance student performance. However, there is only limited empirical evidence to support this notion. In this effect study, a quasi-experiment was conducted to compare 2 conditions. In the treatment condition, 17 teachers implemented a CFA model containing both daily and weekly goal-directed instruction, assessment, and immediate instructional feedback for students who needed additional support. In the control condition, 17 teachers implemented a modification to their usual practice. They assessed their students’ mastery of learning goals on the basis of half-yearly mathematics tests, and prepared weekly pre-teaching sessions for groups of low-achieving students. The posttests showed no significant differences in student performance between the 2 conditions after controlling for student and teacher characteristics. The degree of implementation of the CFA model, however, appeared to be positively related to the 5th-grade students’ performance

Mimivirus Gene Promoters Exhibit an Unprecedented Conservation among all Eukaryotes

The initial analysis of the recently sequenced genome of Acanthamoeba polyphaga Mimivirus, the largest known double-stranded DNA virus, predicted a proteome of size and complexity more akin to small parasitic bacteria than to other nucleo-cytoplasmic large DNA viruses, and identified numerous functions never before described in a virus. It has been proposed that the Mimivirus lineage could have emerged before the individualization of cellular organisms from the 3 domains of life. An exhaustive in silico analysis of the non-coding moiety of all known viral genomes, now uncovers the unprecedented perfect conservation of a AAAATTGA motif in close to 50% of the Mimivirus genes. This motif preferentially occurs in genes transcribed from the predicted leading strand and is associated with functions required early in the viral infectious cycle, such as transcription and protein translation. A comparison with the known promoter of unicellular eukaryotes, in particular amoebal protists, strongly suggests that the AAAATTGA motif is the structural equivalent of the TATA box core promoter element. This element is specific to the Mimivirus lineage, and may correspond to an ancestral promoter structure predating the radiation of the eukaryotic kingdoms. This unprecedented conservation of core promoter regions is another exceptional features of Mimivirus, that again raises the question of its evolutionary origin

Discovery of Sexual Dimorphisms in Metabolic and Genetic Biomarkers

Metabolomic profiling and the integration of whole-genome genetic association data has proven to be a powerful tool to comprehensively explore gene regulatory networks and to investigate the effects of genetic variation at the molecular level. Serum metabolite concentrations allow a direct readout of biological processes, and association of specific metabolomic signatures with complex diseases such as Alzheimer's disease and cardiovascular and metabolic disorders has been shown. There are well-known correlations between sex and the incidence, prevalence, age of onset, symptoms, and severity of a disease, as well as the reaction to drugs. However, most of the studies published so far did not consider the role of sexual dimorphism and did not analyse their data stratified by gender. This study investigated sex-specific differences of serum metabolite concentrations and their underlying genetic determination. For discovery and replication we used more than 3,300 independent individuals from KORA F3 and F4 with metabolite measurements of 131 metabolites, including amino acids, phosphatidylcholines, sphingomyelins, acylcarnitines, and C6-sugars. A linear regression approach revealed significant concentration differences between males and females for 102 out of 131 metabolites (p-values<3.8 x 10(-4); Bonferroni-corrected threshold). Sex-specific genome-wide association studies (GWAS) showed genome-wide significant differences in beta-estimates for SNPs in the CPS1 locus (carbamoyl-phosphate synthase 1, significance level: p<3.8 x 10(-10); Bonferroni-corrected threshold) for glycine. We showed that the metabolite profiles of males and females are significantly different and, furthermore, that specific genetic variants in metabolism-related genes depict sexual dimorphism. Our study provides new important insights into sex-specific differences of cell regulatory processes and underscores that studies should consider sex-specific effects in design and interpretation

Discovery of Sexual Dimorphisms in Metabolic and Genetic Biomarkers

Metabolomic profiling and the integration of whole-genome genetic association data has proven to be a powerful tool to comprehensively explore gene regulatory networks and to investigate the effects of genetic variation at the molecular level. Serum metabolite concentrations allow a direct readout of biological processes, and association of specific metabolomic signatures with complex diseases such as Alzheimer's disease and cardiovascular and metabolic disorders has been shown. There are well-known correlations between sex and the incidence, prevalence, age of onset, symptoms, and severity of a disease, as well as the reaction to drugs. However, most of the studies published so far did not consider the role of sexual dimorphism and did not analyse their data stratified by gender. This study investigated sex-specific differences of serum metabolite concentrations and their underlying genetic determination. For discovery and replication we used more than 3,300 independent individuals from KORA F3 and F4 with metabolite measurements of 131 metabolites, including amino acids, phosphatidylcholines, sphingomyelins, acylcarnitines, and C6-sugars. A linear regression approach revealed significant concentration differences between males and females for 102 out of 131 metabolites (p-values<3.8 x 10(-4); Bonferroni-corrected threshold). Sex-specific genome-wide association studies (GWAS) showed genome-wide significant differences in beta-estimates for SNPs in the CPS1 locus (carbamoyl-phosphate synthase 1, significance level: p<3.8 x 10(-10); Bonferroni-corrected threshold) for glycine. We showed that the metabolite profiles of males and females are significantly different and, furthermore, that specific genetic variants in metabolism-related genes depict sexual dimorphism. Our study provides new important insights into sex-specific differences of cell regulatory processes and underscores that studies should consider sex-specific effects in design and interpretation

The HuMet Repository: watching human metabolism at work

Metabolism oscillates between catabolic and anabolic states depending on food intake, exercise, or stresses that change a multitude of metabolic pathways simultaneously. We present the HuMet Repository for exploring dynamic metabolic responses to oral glucose/lipid loads, mixed meals, 36-h fasting, exercise, and cold stress in healthy subjects. Metabolomics data from blood, urine, and breath of 15 young, healthy men at up to 56 time points are integrated and embedded within an interactive web application, enabling researchers with and without computational expertise to search, visualize, analyze, and contextualize the dynamic metabolite profiles of 2,656 metabolites acquired on multiple platforms. With examples, we demonstrate the utility of the resource for research into the dynamics of human metabolism, highlighting differences and similarities in systemic metabolic responses across challenges and the complementarity of metabolomics platforms. The repository, providing a reference for healthy metabolite changes to six standardized physiological challenges, is freely accessible through a web portal

Dynamic patterns of postprandial metabolic responses to three dietary challenges

Food intake triggers extensive changes in the blood metabolome. The kinetics of these changes depend on meal composition and on intrinsic, health-related characteristics of each individual, making the assessment of changes in the postprandial metabolome an opportunity to assess someone's metabolic status. To enable the usage of dietary challenges as diagnostic tools, profound knowledge about changes that occur in the postprandial period in healthy individuals is needed. In this study, we characterize the time-resolved changes in plasma levels of 634 metabolites in response to an oral glucose tolerance test (OGTT), an oral lipid tolerance test (OLTT), and a mixed meal (SLD) in healthy young males (n = 15). Metabolite levels for samples taken at different time points (20 per individual) during the challenges were available from targeted (132 metabolites) and non-targeted (502 metabolites) metabolomics. Almost half of the profiled metabolites (n = 308) showed a significant change in at least one challenge, thereof 111 metabolites responded exclusively to one particular challenge. Examples include azelate, which is linked to ω-oxidation and increased only in OLTT, and a fibrinogen cleavage peptide that has been linked to a higher risk of cardiovascular events in diabetes patients and increased only in OGTT, making its postprandial dynamics a potential target for risk management. A pool of 89 metabolites changed their plasma levels during all three challenges and represents the core postprandial response to food intake regardless of macronutrient composition. We used fuzzy c-means clustering to group these metabolites into eight clusters based on commonalities of their dynamic response patterns, with each cluster following one of four primary response patterns: (i) “decrease-increase” (valley-like) with fatty acids and acylcarnitines indicating the suppression of lipolysis, (ii) “increase-decrease” (mountain-like) including a cluster of conjugated bile acids and the glucose/insulin cluster, (iii) “steady decrease” with metabolites reflecting a carryover from meals prior to the study, and (iv) “mixed” decreasing after the glucose challenge and increasing otherwise. Despite the small number of subjects, the diversity of the challenges and the wealth of metabolomic data make this study an important step toward the characterization of postprandial responses and the identification of markers of metabolic processes regulated by food intake

An overview of the Lagrangian experiments undertaken during the North Atlantic regional Aerosol Characterisation Experiment (ACE-2)

One of the primary aims of the North Atlantic regional Aerosol Characterisation Experiment (ACE-2) was to quantify the physical and chemical processes affecting the evolution of the major aerosol types over the North Atlantic. The best, practical way of doing this is in a Lagrangian framework where a parcel of air is sampled over several tens of hours and its physical and chemical properties are intensively measured. During the intensive observational phase of ACE-2, between 15 June 1997 and 24 July 1997, 3 cloudy Lagrangian experiments and 3 cloud-free, Lagrangian experiments were undertaken between the south west tip of the Iberian Peninsula and the Canary Islands. This paper gives an overview of the aims and logistics of all of the Lagrangian experiments and compares and contrasts them to provide a framework for the more focused Lagrangian papers in this issue and future process modelling studies and parametrisation development. The characteristics of the cloudy Lagrangian experiments were remarkably different, enabling a wide range of different physical and chemical processes to be studied. In the 1st Lagrangian, a clean maritime air mass was sampled in which salt particle production, due to increased wind speed, dominated the change in the accumulation mode concentrations. In the 2nd Lagrangian, extensive cloud cover resulted in cloud processing of the aerosol in a polluted air mass, and entrainment of air from the free troposphere influenced the overall decrease in aerosol concentrations in the marine boundary layer (MBL). Very little change in aerosol characteristics was measured in the 3rd Lagrangian, where the pollution in the MBL was continually being topped up by entraining air from a residual continental boundary layer (CBL) above. From the analysis of all the Lagrangian experiments, it has been possible to formulate, and present here, a generalised description of a European continental outbreak of pollution over the sub-tropical North Atlantic