Su búsqueda

The actiotope model of giftedness (AMG) highlights the interactions between the individual and the environment. Educational and learning capital (ELC) are essential resources that promote the development of excellence. The study objectives were to examine the contribution of educational capital (EC), learning capital (LC), and general intelligence (GI) to scholastic achievements (SA) of school age students, and to examine whether the effect of EC on GI and SA is mediated by LC. Two hundred, fifth grade, students completed GI and mathematical achievement tests. Teachers completed the teacher’s checklist for each student participant and students’ school grades in mathematics, science, language, and English were collected. Results demonstrated that GI, EC, and LC contributed, altogether, 80% to the prediction of SA, the contribution of LC being higher. Moreover, contribution of EC to SA was mediated by LC. The study corroborates the AMG by demonstrating that both the environment and the individual control the ability to reach excellence and giftedness. (PsycInfo Database Record (c) 2021 APA, all rights reserved) (Source: journal abstract)

The Actiotope Model of Giftedness regards giftedness as a product of the interaction between the individual and the environment. The aim of this study is to evaluate the validity of the Questionnaire of Educational and Learning Capital (QELC) on 187 primary school students from Israel and to examine whether the educational and learning capitals of the students are associated with general intelligence and academic achievement. In the study correlations were found between social, infrastructural, didactic, organismic, actional, episodic and attentional capitals. No correlations were found, however, between general intelligence and other subscales of the QELC. The results of reliabilities and the two-factor CFA model affirmed the validity of the educational and learning capital using the Hebrew version of QELC. (PsycInfo Database Record (c) 2022 APA, all rights reserved) (Source: journal abstract)

Self-regulated learning (SRL) is an active process that assists students in managing their thoughts, behaviors, and emotions to navigate their learning experiences successfully. The study examined the differences in motivation and SRL between gifted and high achievers (GHAs) and typical achievers (TAs) in science, technology, engineering, and mathematics (STEM) disciplines by addressing the contribution of socioeconomic status (SES). A sample of 151 students in 11th and 12th grades from two high schools in Israel were divided into four study groups based on their general intelligence, school grades, and SES. Participants completed SRL and motivation questionnaires. The results indicated that among GHAs, all motivation measures were significantly higher than those of TAs, especially among students from low-SES environments. GHA students reported using more SRL strategies than TA students regarding organization, metacognition, time and learning environment, peer learning, and effort regulation. Students from low-SES environments reported using more organization strategies than those from high-SES environments, whereas TA students surpassed their GHA counterparts in critical thinking. (PsycInfo Database Record (c) 2025 APA, all rights reserved) (Source: journal abstract)

This paper presents part of a multidimensional examination of mathematical giftedness. The present study examined the memory mechanisms associated with general giftedness (G) and excellence in mathematics (E) in four groups of 10th–12th grade students (16–18 years old) varying in levels of G and E. The participants first underwent the Raven test for general ability evaluation and SAT-M—the mathematical excellence tests in order to design the study groups. Afterwards, the students were tested on a battery of three memory tests including tests for short-term (STM) and working memory (WM). The results reveal that the G factor is related to high STM for both phonological loop and phonological central executive mechanisms. It was also found that the E factor is associated with high visual–spatial memory (VSM), in particular with the visual central executive mechanism. An interaction effect was found between G and E factors regarding WM. The central executive mechanism appeared to be related to both G and E factors. In addition, gender differences were shown within the groups. Male participants performed better than their female counterparts on a phonological storage task and a phonological central executive mechanism task. The results can contribute to the theoretical knowledge regarding similarities and differences in memory mechanisms in G and E groups. (PsycInfo Database Record (c) 2020 APA, all rights reserved) (Source: journal abstract)

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)

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)

In order to achieve the present study’s goal—to understand better the phenomenon of mathematical giftedness—we performed a multidimensional examination of the mental processing in students who exhibited mathematical expertise (EM) at the secondary school level. The study included participants from the three groups: students who excelled in school mathematics but were not identified as generally gifted (NG-EM), generally gifted excelling in mathematics (G-EM) students, and students with superior performance in mathematics (S-MG). The research integrated three salient dimensions of mental processing: domain-general cognitive traits, domain-specific (mathematical) creativity, and neuro-cognitive functioning expressed in event-related potentials (ERPs) when solving mathematical problems. In the three study dimensions, we found four types of characteristics of S-MG students: accumulative, G-related, unique and unraveling. This paper defines and exemplifies the characteristics of the four types. (PsycINFO Database Record (c) 2017 APA, all rights reserved) (Source: journal abstract)