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Yousif, Sami R.; Alexandrov, Emma; Bennette, Elizabeth; Aslin, Richard N.; Keil, Frank C. – Developmental Science, 2022
A large and growing body of work has documented robust illusions of area perception in adults. To date, however, there has been surprisingly little in-depth investigation into children's area perception, despite the importance of this topic to the study of quantity perception more broadly (and to the many studies that have been devoted to studying…
Descriptors: Computation, Decision Making, Task Analysis, Heuristics
Smith, Kendal N.; Lamb, Kristen N.; Henson, Robin K. – Gifted Child Quarterly, 2020
Multivariate analysis of variance (MANOVA) is a statistical method used to examine group differences on multiple outcomes. This article reports results of a review of MANOVA in gifted education journals between 2011 and 2017 (N = 56). Findings suggest a number of conceptual and procedural misunderstandings about the nature of MANOVA and its…
Descriptors: Multivariate Analysis, Academically Gifted, Gifted Education, Educational Research
Kustos, Paul Nicholas – ProQuest LLC, 2010
Student difficulty in the study of probability arises in intuitively-based misconceptions derived from heuristics. One such heuristic, the one of note for this research study, is that of representativeness, in which an individual informally assesses the probability of an event based on the degree to which the event is similar to the sample from…
Descriptors: Sample Size, Self Efficacy, Heuristics, Likert Scales
Morsanyi, Kinga; Primi, Caterina; Chiesi, Francesca; Handley, Simon – Contemporary Educational Psychology, 2009
In three studies we looked at two typical misconceptions of probability: the representativeness heuristic, and the equiprobability bias. The literature on statistics education predicts that some typical errors and biases (e.g., the equiprobability bias) increase with education, whereas others decrease. This is in contrast with reasoning theorists'…
Descriptors: Heuristics, Logical Thinking, Psychology, Statistics