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Blokpoel, Mark; Wareham, Todd; Haselager, Pim; Toni, Ivan; van Rooij, Iris – Journal of Problem Solving, 2018
The ability to generate novel hypotheses is an important problem-solving capacity of humans. This ability is vital for making sense of the complex and unfamiliar world we live in. Often, this capacity is characterized as an inference to the best explanation--selecting the "best" explanation from a given set of candidate hypotheses.…
Descriptors: Hypothesis Testing, Logical Thinking, Inferences, Computation
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Inzunsa Cazares, Santiago – North American Chapter of the International Group for the Psychology of Mathematics Education, 2016
This article presents the results of a qualitative research with a group of 15 university students of social sciences on informal inferential reasoning developed in a computer environment on concepts involved in the confidence intervals. The results indicate that students developed a correct reasoning about sampling variability and visualized…
Descriptors: Qualitative Research, College Students, Inferences, Logical Thinking
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Pillow, Bradford H.; Pearson, RaeAnne M. – Metacognition and Learning, 2015
Two experiments investigated 1st-, 3rd-, and 5th-grade children's and adults' judgments related to the controllability of cognitive activities, including object recognition, inferential reasoning, counting, and pretending. In Experiment 1, fifth-grade children and adults rated transitive inference and interpretation of ambiguous pictures as more…
Descriptors: Adults, Grade 1, Grade 3, Grade 5
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Piantadosi, Steven T.; Tenenbaum, Joshua B.; Goodman, Noah D. – Cognition, 2012
In acquiring number words, children exhibit a qualitative leap in which they transition from understanding a few number words, to possessing a rich system of interrelated numerical concepts. We present a computational framework for understanding this inductive leap as the consequence of statistical inference over a sufficiently powerful…
Descriptors: Statistical Inference, Number Concepts, Models, Computation
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Wareham, Todd; Evans, Patricia; van Rooij, Iris – Journal of Problem Solving, 2011
Solving new problems can be made easier if one can build on experiences with other problems one has already successfully solved. The ability to exploit earlier problem-solving experiences in solving new problems seems to require several cognitive sub-abilities. Minimally, one needs to be able to retrieve relevant knowledge of earlier solved…
Descriptors: Logical Thinking, Problem Solving, Difficulty Level, Computation
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Griffiths, Thomas L.; Tenenbaum, Joshua B. – Psychological Review, 2009
Inducing causal relationships from observations is a classic problem in scientific inference, statistics, and machine learning. It is also a central part of human learning, and a task that people perform remarkably well given its notorious difficulties. People can learn causal structure in various settings, from diverse forms of data: observations…
Descriptors: Causal Models, Prior Learning, Logical Thinking, Statistical Inference
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Rips, Lance J.; Asmuth, Jennifer; Bloomfield, Amber – Cognition, 2008
According to one theory about how children learn the meaning of the words for the positive integers, they first learn that "one," "two," and "three" stand for appropriately sized sets. They then conclude by inductive inference that the next numeral in the count sequence denotes the size of sets containing one more object than the size denoted by…
Descriptors: Learning Strategies, Logical Thinking, Number Concepts, Inferences
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Rips, Lance J.; Asmuth, Jennifer; Bloomfield, Amber – Cognition, 2006
According to one theory about how children learn the concept of natural numbers, they first determine that "one", "two", and "three" denote the size of sets containing the relevant number of items. They then make the following inductive inference (the Bootstrap): The next number word in the counting series denotes the size of the sets you get by…
Descriptors: Numbers, Number Concepts, Inferences, Computation