Three aspects of cognitive development

By Robert S. Siegler. 1976

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Citations in the corpus

A mathematical theory of semantic development in deep neural networks (2018, neutral): “W(1)(t) = Q √ A(t)V , W(2)(t) = U √ A(t)Q, [7]”
Semantic Cognition: A Parallel Distributed Processing Approach (2004, background): “Predictive error-driven learning is the engine that drives knowledge acquisition and representational change in many PDP models of cognitive development, including an early model (McClelland, 1989) of children’s understanding of balance scales (Inhelder & Piaget, 1958; Siegler, 1976); several simple”
Theories of Mind in Transition: A Microgenetic Study of the Development of False Belief Understanding (2006, background): “For example, Siegler (1976) gave children Piagetian balance-scale problems and asked them to predict which way the balance would tip; when children were able to view the actual outcome following their predictions, their reasoning improved.”
Learning new problem-solving strategies leads to changes in problem representation (2009, background): “Children form inaccurate or incomplete problem representations for many different types of problems, including balance scale problems (Siegler, 1976; Siegler & Chen, 1998), arithmetic word problems (Dean & Malik, 1986), probability problems (Dean & Mollaison, 1986), proportional reasoning problems…”
A Cognitive Diagnosis Model for Cognitively Based Multiple-Choice Options (2009, methodology): “…model can be applied to the area of cognition and development, specifically the balance scale problems, which have been extensively used to study proportional reasoning in children (e.g., Halford, Andrews, Dalton, Boag, & Zielinski, 2002; Shultz, Mareschal, & Schmidt, 1994; Siegler, 1976, 1981).”
The Developmental Course of Distance, Time, and Velocity Concepts:A Generative Connectionist Model (2000, background): “…include (a) the balance scale task (e.g., Inhelder & Piaget, 1958; McClelland, 1989; Newell, 1990; Schmidt & Ling, 1996; Shultz & Schmidt, 1991; Siegler, 1976, 1981; Wilkening & Anderson, 1982, 1991), (b) area judgment tasks (e.g., N. H. Anderson & Cuneo, 1977; Avons & Thomas, 1990; Lohaus &…”
Learning hierarchical categories in deep neural networks (2013, background): “Furthermore, humans can exhibit stage-like transitions as they learn, rapidly moving from ignorance to mastery (Inhelder & Piaget, 1958; Siegler, 1976).”
Connectionist models of development (2003, background): “Children often appear to show stage-like developmental changes, for example, in their understanding of balance scale problems (Inhelder & Piaget, 1958; Siegler, 1976).”
A Comparative Evaluation of Approximate Probabilistic Simulation and Deep Neural Networks as Accounts of Human Physical Scene Understanding (2016, methodology): “sized explicit reasoning about textbook-style physics problems (McCloskey, 1983), with models focused on people’s qualitative judgments (Forbus, 1984; Siegler, 1976), recent studies of physical scene understanding have looked at more”
Effects of a Cooperative Learning Program on the Elaborations of Students During Help Seeking and Help Giving (2005, result): “In contrast to the work of Siegler (1976), Phelps and Damon (1989), and Tudge (1992), our study did not involve a real balance beam with removable pegs on each side of the fulcrum or the capacity to actually tip left or right.”
The development of scientific reasoning skills. (2000, methodology): “This procedure is analogous to the rule-assessment approach described in Siegler (1976, 1981).”
Developing Conceptual Understanding and Procedural Skill in Mathematics: An Iterative Process. (2001, background): “Fourth, manipulations that result in improved problem representations also lead to improved procedural knowledge (Alibali, McNeil, & Perrott, 1998: Siegler, 1976).”