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Super-gifted individuals are considered to be very rare. This paper addresses one part of a larger body of research aimed at characterization of super-giftedness in mathematics. The research population consists of three groups of students who excel in mathematics: Super-gifted in mathematics (S-MG), generally gifted students who excel in school mathematics (G-EM) and students who excel in school mathematics but are not identified as generally gifted (NG-EM). Fifty-six male students who comprised these groups performed a battery of cognitive tests: memory, speed of information processing, visual perception, and attention. We found that the between-group differences are task depended and that S-MG students can be characterized by superior performance on Working Memory test (WM – span, WM – total score) and the accuracy of Pattern-recognition, which was an indicator of visual perception. (PsycINFO Database Record (c) 2016 APA, all rights reserved) (Source: journal abstract)
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This study represents part of more extensive research aimed at a multidimensional examination of mathematical giftedness. This study aimed to:1. Examine the link between cognitive abilities and General giftedness (G), Excellence in Mathematics (EM) and gender. The cognitive abilities that were examined include: memory, attention, speed of information processing and visual perception.2. Examine differences and similarities in cognitive abilities of excelling in mathematics students who vary in their degree of general giftedness (S-MG, G-EM, and NG-EM), as reflected in memory, speed of information processing, attention and visual perception.3. Examine the cognitive profiles of students from four study groups according to memory, speed of information processing, attention and visual perception traits.4. Identify cognitive components that can predict General giftedness (G) and Excellence in mathematics (EM). The cognitive components (determined after factor analysis) that were examined include: STM_WM, Pattern-recall, Visual serial processing and Numeric processing. Population and sampling procedure: The sampling procedure included 1200 10th -11th grade students who undergo a battery of general intelligence (Raven's Advanced Progressive Matrix Test (RPMT)) and mathematical ability (Scholastic Assessment Test in Mathematics, (SAT-M)) tests. After completion of this procedure, a sample of 200 students was selected. These students were subdivided into four experimental groups, determining the research population by a combination of EM and G factors:G-EM group: students who are identified as generally gifted and excelling in mathematics;G-NEM group: students who are identified as generally gifted but do not excel in mathematics;NG-EM group: students excelling in mathematics who are not identified as generally gifted; NG-NEM group: students who are identified as being neither generally gifted nor excelling in mathematics.Students from G groups are mainly chosen from classes for gifted students (IQ>130) or with Raven score above 27. Students who are sampled as EM are those that study mathematics at high level (HL) with SAT-M scores higher than 26 and math score above 90.Another study group participated in this study are super-mathematically-gifted (S-MG). These students satisfied all criteria for the G-EM group and additionally displayed exceptional achievements in mathematics: membership in national Olympiad teams (in mathematics or computer sciences) or studying university mathematics courses parallel with their high school studies, and attaining scores above 95.The study findings are reported based on 190 students divided into four study groups and 7 S-MG students who fully completed the cognitive tasks. The cognitive abilities that were examined include: memory, speed of information processing (SIP), attention and visual perception. Data Analysis: In chapters 3.1-3.3 multivariate analysis of variance tests (MANOVA) were used to compare the cognitive abilities (memory, speed of information processing, attention and visual perception) of participants from the four study groups.In chapter 3.4 non-parametric tests were used for the analysis of the between-group in all cognitive tests between S-MG, G-EM and NG-EM students.In chapter 3.5 non-hierarchical K-means cluster analysis was conducted to identify the cognitive profile of participants'. Thereafter, a structural equation modeling (SEM) was used in order to determine which cognitive categories can predict general giftedness (G) and excellence in mathematics (EM). (PsycInfo Database Record (c) 2022 APA, all rights reserved)
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