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.

Attention and Effort

because observed behavior is the result of interactions between environmental factors and genes during the extended period of development. Therefore, to better understand expert and exceptional performance, we must require that the account specify the different environmental factors that could selectively promote and facilitate the achievement of such performance. In addition, recent research on expert performance and expertise (Chi, Glaser, & Farr, 1988; Ericsson & Smith, 1991a) has shown that important characteristics of experts' superior performance are acquired through experience and that the effect of practice on performance is larger than earlier believed possible. For this reason, an account of exceptional performance must specify the environmental circumstances, such as the duration and structure of activities, and necessary minimal biological attributes that lead to the acquisition of such characteristics and a corresponding level of performance. An account that explains how a majority of individuals can attain a given level of expert performance might seem inherently unable to explain the exceptional performance of only a small number of individuals. However, if such an empirical account could be empirically supported, then the extreme characteristics of experts could be viewed as having been acquired through learning and adaptation, and studies of expert performance could provide unique insights into the possibilities and limits of change in cognitive capacities and bodily functions. In this article we propose a theoretical framework that explains expert performance in terms of acquired characteristics resulting from extended deliberate practice and that limits the role of innate (inherited) characteristics to general levels of activity and emotionality. We provide empirical support from two new studies and from already published evidence on expert performance in many different domains.

/pdf/the-role-of-deliberate-practice-in-the-acquisition-of-expert-3j9768t5su.pdf

The role of deliberate practice in the acquisition of expert performance.

Research in the area of educational technology has often been critiqued for a lack of theoretical grounding. In this article we propose a conceptual framework for educational technology by building on Shulman’s formulation of ‘‘pedagogical content knowledge’’ and extend it to the phenomenon of teachers integrating technology into their pedagogy. This framework is the result of 5 years of work on a program of research focused on teacher professional development and faculty development in higher education. It attempts to capture some of the essential qualities of teacher knowledge required for technology integration in teaching, while addressing the complex, multifaceted, and situated nature of this knowledge. We argue, briefly, that thoughtful pedagogical uses of technology require the development of a complex, situated form of knowledge that we call Technological Pedagogical Content Knowledge (TPCK). In doing so, we posit the complex roles of, and interplay among, three main components of learning environments: content, pedagogy, and technology. We argue that this model has much to offer to discussions of technology integration at multiple levels: theoretical, pedagogical, and methodological. In this article, we describe the theory behind our framework, provide examples of our teaching approach based upon the framework, and illustrate the methodological contributions that have resulted from this work.

/pdf/technological-pedagogical-content-knowledge-a-framework-for-4g4dquqx44.pdf

Technological Pedagogical Content Knowledge: A Framework for Teacher Knowledge

https://onlinelibrary.wiley.com/doi/pdf/10.1207/s15516709cog1202_4

Cognitive load during problem solving: Effects on learning

Perception in chess

Publisher Summary This chapter describes the progress made toward understanding chess skill. It describes the work on perception in chess, adding some new analyses of the data. It presents a theoretical formulation to characterize how expert chess players perceive the chess board. It describes some tasks that correlate with chess skill and the cognitive processes of skilled chess players. It is believed that the demonstration of de Groot's, far from being an incidental side effect of chess skill, actually reveals one of the most important processes that underlie chess skill—the ability to perceive familiar patterns of pieces. In the first experiment discussed in the chapter, two tasks were used. The memory task was very similar to de Groot's task: chess players saw a position for 5 seconds and then attempted to recall it. Unlike de Groot, multiple trials were used—5 seconds of viewing followed by recall—until the position was recalled perfectly. The second task or the perception task for simplicity involved showing chess players a position in plain view.

The mind's eye in chess.

On the process of comparing sentences against pictures

As genetics needs its model organisms, its Drosophila and Neurospora, so psychology needs standard task environments around which knowledge and understanding can cumulate. Chess has proved to be an excellent model environment for this purpose. About a decade ago in the pages of this journal, one of us, with Allen Newell, described the progress that had been made up to that time in using information-processing models and the techniques of computer simulation to explain human problem-solving processes. (Simon et al, 1964). A part of our article was devoted to a theory of the processes that expert chess players use in discovering checkmating combinations (Simon et al, 1962), a theory that was subsequently developed further, embodied in a running computer program, mater, and subjected to additional empirical testing. (Baylor et al, 1966).

Skill in Chess

After more than 230 hours of practice in the laboratory, a subject was able to increase his memory span from 7 to 79 digits. His performance on other memory tests with digits equaled that of memory experts with lifelong training. With an appropriate mnemonic system, there is seemingly no limit to memory performance with practice.

/pdf/acquisition-of-a-memory-skill-1srgxqog4x.pdf

William G. Chase

Papers

Perception in chess

The mind's eye in chess.

On the process of comparing sentences against pictures

Skill in Chess

Acquisition of a memory skill