New developments in the science of learning science of learning overview mind and brain how experts differ from novices how children learn learning and transfer the learning environment curriculum, instruction and commnity effective teaching - examples in history, mathematics and science teacher learning technology to support learning conclusions from new developments in the science of learning.

How people learn: Brain, mind, experience, and school.

Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268

Behavioral scientists routinely publish broad claims about human psychology and behavior in the world's top journals based on samples drawn entirely from Western, Educated, Industrialized, Rich, and Democratic (WEIRD) societies. Researchers - often implicitly - assume that either there is little variation across human populations, or that these "standard subjects" are as representative of the species as any other population. Are these assumptions justified? Here, our review of the comparative database from across the behavioral sciences suggests both that there is substantial variability in experimental results across populations and that WEIRD subjects are particularly unusual compared with the rest of the species - frequent outliers. The domains reviewed include visual perception, fairness, cooperation, spatial reasoning, categorization and inferential induction, moral reasoning, reasoning styles, self-concepts and related motivations, and the heritability of IQ. The findings suggest that members of WEIRD societies, including young children, are among the least representative populations one could find for generalizing about humans. Many of these findings involve domains that are associated with fundamental aspects of psychology, motivation, and behavior - hence, there are no obvious a priori grounds for claiming that a particular behavioral phenomenon is universal based on sampling from a single subpopulation. Overall, these empirical patterns suggests that we need to be less cavalier in addressing questions of human nature on the basis of data drawn from this particularly thin, and rather unusual, slice of humanity. We close by proposing ways to structurally re-organize the behavioral sciences to best tackle these challenges.

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The WEIRDest People in the World

Individual differences in working memory and reading

1. Introduction 2. The emergence of learning activity as a historical form of human learning 3. The zone of proximal development as the basic category of expansive research 4. The instruments of expansion 5. Toward an expansive methodology 6. Epilogue.

Learning by expanding: An activity-theoretical approach to developmental research

1. Whose Children are we Talking About? 2. Evolution and Cognitive Development 3. Cognitive Variability: The Ubiquity of Multiplicity 4. Strategic Development: Trudging up the Staircase or Swimming with the Tide 5. The Adaptivity of Multiplicity 6. Formal Models of Strategy Choice or Plasterers and Professors 7. How Children Generate New Ways of Thinking 8. A New Agenda for Cognitive Development

Emerging Minds: The Process of Change in Children's Thinking

The authors propose that conceptual and procedural knowledge develop in an iterative fashion and that improved problem representation is 1 mechanism underlying the relations between them. Two experiments were conducted with 5th- and 6th-grade students learning about decimal fractions. In Experiment 1, children's initial conceptual knowledge predicted gains in procedural knowledge, and gains in procedural knowledge predicted improvements in conceptual knowledge. Correct problem representations mediated the relation between initial conceptual knowledge and improved procedural knowledge. In Experiment 2, amount of support for correct problem representation was experimentally manipulated, and the manipulations led to gains in procedural knowledge. Thus, conceptual and procedural knowledge develop iteratively, and improved problem representation is 1 mechanism in this process.

https://psych.wisc.edu/alibali/home/Publications_files/Rittle-JohnsonSieglerandAlibali2001.pdf

Developing Conceptual Understanding and Procedural Skill in Mathematics: An Iterative Process.

We examined children's and adults' numerical estimation and the representations that gave rise to their estimates. The results were inconsistent with two prominent models of numerical representation: the logarithmic-ruler model, which proposes that people of all ages possess a single, logarithmically spaced representation of numbers, and the accumulator model, which proposes that people of all ages represent numbers as linearly increasing magnitudes with scalar variability. Instead, the data indicated that individual children possess multiple numerical representations; that with increasing age and numerical experience, they rely on appropriate representations increasingly often; and that the numerical context influences their choice of representation. The results, obtained with second graders, fourth graders, sixth graders, and adults who performed two estimation tasks in two numerical contexts, strongly suggest that one cause of children's difficulties with estimation is reliance on logarithmic representations of numerical magnitudes in situations in which accurate estimation requires reliance on linear representations.

The Development of Numerical Estimation Evidence for Multiple Representations of Numerical Quantity

Two experiments examined kindergartners', first graders', and second graders' numerical estimation, the internal representations that gave rise to the estimates, and the general hypothesis that developmental sequences within a domain tend to repeat themselves in new contexts. Development of estimation in this age range on 0-to-100 number lines followed the pattern observed previously with older children on 0-to-1,000 lines. Between kindergarten and second grade (6 and 8 years), patterns of estimates progressed from consistently logarithmic to a mixture of logarithmic and linear to a primarily linear pattern. Individual differences in number-line estimation correlated strongly with math achievement test scores, improved estimation accuracy proved attributable to increased linearity of estimates, and exposure to relevant experience tended to improve estimation accuracy.

Robert S. Siegler

Papers

Emerging Minds: The Process of Change in Children's Thinking

Developing Conceptual Understanding and Procedural Skill in Mathematics: An Iterative Process.

The Development of Numerical Estimation Evidence for Multiple Representations of Numerical Quantity

Development of Numerical Estimation in Young Children

Children's Thinking : What Develops?