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Journal of Experimental Child Psychology Nov 2023Schoolchildren with better executive functioning skills achieve better mathematics results. It is less clear how inhibition, cognitive flexibility, and working memory...
Schoolchildren with better executive functioning skills achieve better mathematics results. It is less clear how inhibition, cognitive flexibility, and working memory combine to predict mathematics achievement and difficulty throughout primary and secondary school. This study aimed to find the best combination of executive function measures for predicting mathematical achievement in Grades 2, 6, and 10 and to test whether this combination predicts the probability of having mathematical difficulties across school grades even when fluid intelligence and processing speed were included in the models. A total of 426 students-141 2nd graders (72 girls), 143 6th graders (72 girls), and 142 10th graders (79 girls)-were cross-sectionally assessed with 12 executive tasks, one standardized mathematical task, and a standardized test of intelligence. Bayesian regression analyses found various combinations of executive predictors of mathematical achievement for each school grade spanning Grade 2 to measures of cognitive inhibition (negative priming) and cognitive flexibility (verbal fluency); Grade 6 to measures of inhibition: resistance to distractor interference (receptive attention), cognitive flexibility (local-global), and working memory (counting span); and Grade 10 to measures of inhibition: resistance to distractor interference (receptive attention) and prepotent response inhibition (stop signal) and working memory (reading span). Logistic regression showed that the executive models derived from the Bayesian analyses had a similar ability to classify students with mathematical difficulty and their peers with typical achievement to broader cognitive models that included fluid intelligence and processing speed. Measures of processing speed, cognitive flexibility (local-global), and prepotent response inhibition (stop signal) were the main risk factors in Grades 2, 6, and 10, respectively. Cognitive flexibility (verbal fluency) in Grade 2 and fluid intelligence, which was more stable in all three grades, acted as protective factors against mathematical difficulty. These findings inform practical considerations for establishing preventive and intervention proposals.
Topics: Female; Humans; Child; Executive Function; Bayes Theorem; Memory, Short-Term; Mathematics; Schools
PubMed: 37307647
DOI: 10.1016/j.jecp.2023.105715 -
Cells & Development Jun 2023Adult stem cells are described as a discrete population of cells that stand at the top of a hierarchy of progressively differentiating cells. Through their unique... (Review)
Review
Adult stem cells are described as a discrete population of cells that stand at the top of a hierarchy of progressively differentiating cells. Through their unique ability to self-renew and differentiate, they regulate the number of end-differentiated cells that contribute to tissue physiology. The question of how discrete, continuous, or reversible the transitions through these hierarchies are and the precise parameters that determine the ultimate performance of stem cells in adulthood are the subject of intense research. In this review, we explain how mathematical modelling has improved the mechanistic understanding of stem cell dynamics in the adult brain. We also discuss how single-cell sequencing has influenced the understanding of cell states or cell types. Finally, we discuss how the combination of single-cell sequencing technologies and mathematical modelling provides a unique opportunity to answer some burning questions in the field of stem cell biology.
Topics: Neural Stem Cells; Brain; Models, Theoretical; Adult Stem Cells; Mathematics
PubMed: 37179018
DOI: 10.1016/j.cdev.2023.203849 -
Mathematical Biosciences and... Mar 2020
Topics: Biological Science Disciplines; Mathematics; Models, Theoretical
PubMed: 32987510
DOI: 10.3934/mbe.2020167 -
Cognitive Science Apr 2021Topological relations such as inside, outside, or intersection are ubiquitous to our spatial thinking. Here, we examined how people reason deductively with topological...
Topological relations such as inside, outside, or intersection are ubiquitous to our spatial thinking. Here, we examined how people reason deductively with topological relations between points, lines, and circles in geometric diagrams. We hypothesized in particular that a counterexample search generally underlies this type of reasoning. We first verified that educated adults without specific math training were able to produce correct diagrammatic representations contained in the premisses of an inference. Our first experiment then revealed that subjects who correctly judged an inference as invalid almost always produced a counterexample to support their answer. Noticeably, even if the counterexample always bore a certain level of similarity to the initial diagram, we observed that an object was more likely to be varied between the two drawings if it was present in the conclusion of the inference. Experiments 2 and 3 then directly probed counterexample search. While participants were asked to evaluate a conclusion on the basis of a given diagram and some premisses, we modulated the difficulty of reaching a counterexample from the diagram. Our results indicate that both decreasing the counterexample density and increasing the counterexample distance impaired reasoning performance. Taken together, our results suggest that a search procedure for counterexamples, which proceeds object-wise, could underlie diagram-based geometric reasoning. Transposing points, lines, and circles to our spatial environment, the present study may ultimately provide insights on how humans reason about topological relations between positions, paths, and regions.
Topics: Adult; Humans; Mathematics
PubMed: 33873252
DOI: 10.1111/cogs.12959 -
Developmental Cognitive Neuroscience Apr 2018Brain imaging studies on academic achievement offer an exciting window on experience-dependent cortical plasticity, as they allow us to understand how developing brains... (Review)
Review
Brain imaging studies on academic achievement offer an exciting window on experience-dependent cortical plasticity, as they allow us to understand how developing brains change when children acquire culturally transmitted skills. This contribution focuses on the learning of arithmetic, which is quintessential to mathematical development. The nascent body of brain imaging studies reveals that arithmetic recruits a large set of interconnected areas, including prefrontal, posterior parietal, occipito-temporal and hippocampal areas. This network undergoes developmental changes in its function, connectivity and structure, which are not yet fully understood. This network only partially overlaps with what has been found in adults, and clear differences are observed in the recruitment of the hippocampus, which are related to the development of arithmetic fact retrieval. Despite these emerging trends, the literature remains scattered, particularly in the context of atypical development. Acknowledging the distributed nature of the arithmetic network, future studies should focus on connectivity and analytic approaches that investigate patterns of brain activity, coupled with a careful design of the arithmetic tasks and assessments of arithmetic strategies. Such studies will produce a more comprehensive understanding of how the arithmetical brain unfolds, how it changes over time, and how it is impaired in atypical development.
Topics: Brain; Child; Female; Humans; Learning; Magnetic Resonance Imaging; Male; Mathematics; Neuroimaging
PubMed: 28566139
DOI: 10.1016/j.dcn.2017.05.002 -
Journal of the Royal Society, Interface Feb 2021One-shot anonymous unselfishness in economic games is commonly explained by social preferences, which assume that people care about the monetary pay-offs of others.... (Review)
Review
One-shot anonymous unselfishness in economic games is commonly explained by social preferences, which assume that people care about the monetary pay-offs of others. However, during the last 10 years, research has shown that different types of unselfish behaviour, including cooperation, altruism, truth-telling, altruistic punishment and trustworthiness are in fact better explained by preferences for following one's own personal norms-internal standards about what is right or wrong in a given situation. Beyond better organizing various forms of unselfish behaviour, this moral preference hypothesis has recently also been used to increase charitable donations, simply by means of interventions that make the morality of an action salient. Here we review experimental and theoretical work dedicated to this rapidly growing field of research, and in doing so we outline mathematical foundations for moral preferences that can be used in future models to better understand selfless human actions and to adjust policies accordingly. These foundations can also be used by artificial intelligence to better navigate the complex landscape of human morality.
Topics: Altruism; Artificial Intelligence; Cooperative Behavior; Humans; Mathematics; Morals; Punishment
PubMed: 33561377
DOI: 10.1098/rsif.2020.0880 -
Journal of Experimental Child Psychology Jul 2022Preterm birth affects the academic development of children, especially in mathematics. Remarkably, only a few studies have measured specific effects of preterm birth on...
Preterm birth affects the academic development of children, especially in mathematics. Remarkably, only a few studies have measured specific effects of preterm birth on mathematical skills in primary school. The aim of this study was to compare 11-year-old children, with an IQ above 70, born very preterm (N = 64) and full-term (N = 72) on a variety of 5th grade mathematical skills and cognitive abilities important for mathematical learning. The measures were spontaneous focusing on numerosity (SFON), spontaneous focusing on quantitative relations (SFOR), arithmetic fluency, mathematics achievement, number line estimation, rational number magnitude knowledge, mathematics motivation, reading skills, visuospatial processing, executive functions, and naming speed. The children born very preterm and full-term differed in arithmetic fluency, SFON and SFOR. Domain general cognitive abilities did not fully explain the group differences in SFON and SFOR. Retrospective comparisons of the samples at the age of five years showed large group differences in early mathematical skills and cognitive abilities. Despite lower early mathematical skills, the children born very preterm reached peer equivalent performance in many mathematical skills by the age of 11 years. Nevertheless, they appear less likely to focus on implicit mathematical features in their everyday life.
Topics: Achievement; Child; Child, Preschool; Humans; Infant, Extremely Premature; Infant, Newborn; Mathematics; Premature Birth; Retrospective Studies
PubMed: 35219122
DOI: 10.1016/j.jecp.2022.105390 -
International Journal of Environmental... Dec 2021Research suggests that integrated STEM activities can best support students in developing their mathematical and scientific understanding. On one hand, while science...
Research suggests that integrated STEM activities can best support students in developing their mathematical and scientific understanding. On one hand, while science provides mathematics with real-life authentic problems to investigate, mathematics provides science powerful tools to explore those problems. In line with this call, in this study, we designed an integrated lesson at the cross-section of proportional reasoning and added sugar present in food products to explore how added sugar provides students with a meaningful context to engage in proportional reasoning and how proportional reasoning helps students identify the quantity of added sugar present in different food products and provides students with a platform to initiate a conversation around quality of food products. Developed on the theoretical framework of Realistic Mathematics Education (RME), this lesson was remotely implemented on three middle school students. The result section highlights the design principle of the lesson that provided students with an opportunity to construct an understanding of both the disciplines through a mutual interaction.
Topics: Curriculum; Humans; Mathematics; Problem Solving; Students; Sugars
PubMed: 34886547
DOI: 10.3390/ijerph182312821 -
International Journal of Environmental... Jul 2020This study aimed to investigate secondary students' mathematics achievement emotions and their mediating effects on the relationships between classroom environmental...
This study aimed to investigate secondary students' mathematics achievement emotions and their mediating effects on the relationships between classroom environmental characteristics, namely, teacher-student interactional styles (i.e., teacher leadership and student freedom styles), and students' mathematics learning outcomes in mainland China. A sample of 1423 Grade 7 to 9 junior secondary students responded to a questionnaire that comprised three sets of scales for assessing students' perceived teacher-student interactional styles, mathematics achievement emotions, and cognitive and affective learning outcomes. The results indicated that students' mathematics learning outcomes were positively associated with both teacher leadership and student freedom styles. Moreover, students' mathematics achievement emotions mediated the relationships between these two interactional styles and their mathematics learning outcomes. These results highlight the importance of mathematics achievement emotions in student learning, and provide implications for the improvement of mathematics classroom environments.
Topics: Achievement; Adolescent; Child; China; Emotions; Humans; Mathematics; Students
PubMed: 32630336
DOI: 10.3390/ijerph17134742 -
Bulletin of Mathematical Biology Oct 2023Computing has revolutionised the study of complex nonlinear systems, both by allowing us to solve previously intractable models and through the ability to visualise...
Computing has revolutionised the study of complex nonlinear systems, both by allowing us to solve previously intractable models and through the ability to visualise solutions in different ways. Using ubiquitous computing infrastructure, we provide a means to go one step further in using computers to understand complex models through instantaneous and interactive exploration. This ubiquitous infrastructure has enormous potential in education, outreach and research. Here, we present VisualPDE, an online, interactive solver for a broad class of 1D and 2D partial differential equation (PDE) systems. Abstract dynamical systems concepts such as symmetry-breaking instabilities, subcritical bifurcations and the role of initial data in multistable nonlinear models become much more intuitive when you can play with these models yourself, and immediately answer questions about how the system responds to changes in parameters, initial conditions, boundary conditions or even spatiotemporal forcing. Importantly, VisualPDE is freely available, open source and highly customisable. We give several examples in teaching, research and knowledge exchange, providing high-level discussions of how it may be employed in different settings. This includes designing web-based course materials structured around interactive simulations, or easily crafting specific simulations that can be shared with students or collaborators via a simple URL. We envisage VisualPDE becoming an invaluable resource for teaching and research in mathematical biology and beyond. We also hope that it inspires other efforts to make mathematics more interactive and accessible.
Topics: Humans; Models, Biological; Mathematical Concepts; Nonlinear Dynamics; Mathematics; Students
PubMed: 37823924
DOI: 10.1007/s11538-023-01218-4