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The aims of the learning sciences (LS) are to understand the nature of learning from a broad range of perspectives, and to shape the ways that learning environments and resources are designed and used. LS incorporates both systemic and elemental approaches to investigating questions about learning, as a complement to the primarily elemental approach emphasized in cognitive science research. Thus, its greatest potential is in the integration of systemic and elemental perspectives. Four major themes are central. First, research in LS attempts to bridge the divide between research and practice. Second, research in LS is motivated by limitations of theories of learning and cognition for specifying instruction. Third, research in LS embraces the importance of analyzing and assessing complex interventions through both experimental and design-based research. Fourth, research in LS emphasizes the learning and behavior of the individual in interaction with the physical, social, and cultural world, as well as with semiotic and technical resources. Research in LS can be conceptualized along a continuum of time scales, from the more microscopic to the more macroscopic. The time-scale framework illustrates how disparate research traditions and research methods can function within a unifying framework for the study of learning and complex behavior. The effort to 'scale-up' from more elemental findings to more complex, authentic settings has been generative for LS, but faces serious challenges. There is an alternate route to establishing a cumulative scientific knowledge base, namely, 'scaling down' from more complex, ecologically valid levels to more elemental levels. Studies of basic learning processes, framed in the context of the larger system, are well positioned to support impact in authentic settings. Copyright © 2010 John Wiley & Sons, Ltd. For further resources related to this article, please visit the WIREs website.
The aims of the learning sciences (LS) are to understand the nature of learning from a broad range of perspectives, and to shape the ways that learning environments and resources are designed and used. LS incorporates both systemic and elemental approaches to investigating questions about learning, as a complement to the primarily elemental approach emphasized in cognitive science research. Thus, its greatest potential is in the integration of systemic and elemental perspectives. Four major themes are central. First, research in LS attempts to bridge the divide between research and practice. Second, research in LS is motivated by limitations of theories of learning and cognition for specifying instruction. Third, research in LS embraces the importance of analyzing and assessing complex interventions through both experimental and design-based research. Fourth, research in LS emphasizes the learning and behavior of the individual in interaction with the physical, social, and cultural world, as well as with semiotic and technical resources. Research in LS can be conceptualized along a continuum of time scales, from the more microscopic to the more macroscopic. The time-scale framework illustrates how disparate research traditions and research methods can function within a unifying framework for the study of learning and complex behavior. The effort to 'scale-up' from more elemental findings to more complex, authentic settings has been generative for LS, but faces serious challenges. There is an alternate route to establishing a cumulative scientific knowledge base, namely, 'scaling down' from more complex, ecologically valid levels to more elemental levels. Studies of basic learning processes, framed in the context of the larger system, are well positioned to support impact in authentic settings. Copyright © 2010 John Wiley & Sons, Ltd. For further resources related to this article, please visit the WIREs website.
When solving spatial problems, people often spontaneously produce hand gestures. Recent research has shown that our knowledge is shaped by the interaction between our body and the environment. In this article, we review and discuss evidence on: 1) how spontaneous gesture can reveal the development of problem solving strategies when people solve spatial problems; 2) whether producing gestures can enhance spatial problem solving performance. We argue that when solving novel spatial problems, adults go through deagentivization and internalization processes, which are analogous to young children's cognitive development processes. Furthermore, gesture enhances spatial problem solving performance. The beneficial effect of gesturing can be extended to non-gesturing trials and can be generalized to a different spatial task that shares similar spatial transformation processes.
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