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Waismeyer, Anna; Meltzoff, Andrew N.; Gopnik, Alison – Developmental Science, 2015
How do young children learn about causal structure in an uncertain and variable world? We tested whether they can use observed probabilistic information to solve causal learning problems. In two experiments, 24-month-olds observed an adult produce a probabilistic pattern of causal evidence. The toddlers then were given an opportunity to design…
Descriptors: Toddlers, Young Children, Probability, Causal Models
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Huey, Maryann E.; Baker, Deidra L. – Mathematics Teacher, 2015
Many teachers of required secondary school mathematics classes are introducing statistics and probability topics traditionally relegated to college or AP Statistics courses. As a result, they need guidance in preparing lesson plans and orchestrating effective classroom discussions. In this article, the authors will describe the students' learning…
Descriptors: Misconceptions, Causal Models, Secondary School Mathematics, Probability
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Kemp, Charles; Shafto, Patrick; Tenenbaum, Joshua B. – Cognitive Psychology, 2012
Humans routinely make inductive generalizations about unobserved features of objects. Previous accounts of inductive reasoning often focus on inferences about a single object or feature: accounts of causal reasoning often focus on a single object with one or more unobserved features, and accounts of property induction often focus on a single…
Descriptors: Generalization, Logical Thinking, Inferences, Probability
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers