Children's interpretations of covariation data: Explanations reveal understanding of relevant comparisons |
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| Institution: | 1. LMU Munich, Germany;2. University of Wisconsin-Madison, USA;3. Technical University of Munich, Germany;1. Department of Applied Psychology, New York University, NY, United States;2. Université Sainte-Anne, Church Point, Canada;3. PERFORM Center, Concordia University, Montreal, Canada;4. Department of Childhood Education, University of Johannesburg, South Africa;1. The Pennsylvania State University, 226 CEDAR Building, University Park, PA 16803, USA;2. The Pennsylvania State University, 223 CEDAR Building, University Park, PA 16803, USA;1. German Institute for International Educational Research, Schloßstraße 29, 60486, Frankfurt am Main, Germany;2. MPRG REaD (Reading Education and Development), Max Planck Institute for Human Development, Lentzeallee 94, 14195, Berlin, Germany |
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| Abstract: | This research investigates children's understanding of the significance of comparisons between data categories for judgments of covariation. Past studies showed that children sometimes neglect some of the relevant data categories. This may occur because children fail to understand the relevance of the comparisons between data categories. To investigate this interpretation, 51 second graders and 43 fourth graders were tested in a between-subject design. In the standard condition, children were asked to explain their own covariation judgments. In the explain-correct condition, children were told the correct judgments and asked to explain them. Children in the explain-correct condition often provided explanations that were consistent with the correct judgments; children in the standard condition did so less often. Thus, when asked to explain correct judgments, elementary school children's explanations reveal that they possess a basic conceptual understanding of inference from covariation data. |
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| Keywords: | Scientific reasoning Evidence evaluation Data interpretation Statistical reasoning Development |
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