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Effects of General and Broad Cognitive Abilities on Mathematics Achievement

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Abstract

This study investigated the direct and indirect effects of general intelligence and 7 broad cognitive abilities on mathematics achievement. Structural equation modeling was used to investigate the simultaneous effects of both general and broad cognitive abilities on students' mathematics achievement. A hierarchical model of intelligence derived from the Cattell-Horn-Carroll (CHC) taxonomy of intelligence was used for all analyses. The participants consisted of 4 age-differentiated subsamples (ranging from ages 5 to 19) from the standardization sample of the Woodcock-Johnson III (WJ III; Woodcock, McGrew, & Mather, 2001). Data from each of the 4 age-differentiated subsamples were divided into 2 data sets. At each age level, one data set was used for model testing and modification, and a second data set was used for model validation. The following CHC broad cognitive ability factors demonstrated statistically significant direct effects on the mathematics achievement variables: Fluid Reasoning, Crystallized Intelligence, and Processing Speed. In contrast, across all age levels, the general intelligence factor demonstrated indirect effects on the mathematics achievement variable. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
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... Similarly, sustained attention highly correlates with reasoning (Buehner et al., 2006). In the same way, processing speed is a predictor of reasoning (Kail et al., 2015) and one of the most determinant factors in the acquisition of mathematical skills (Floyd et al., 2003), which have a strong relationship with both performance in this subject and in computational automaticity (Taub et al., 2008). Besides, people with musical studies show significantly higher scores in fluid cognition than those without them, fluid intelligence being understood as the ability to think abstractly and to solve problems (Meyer et al., 2020). ...
... As reinforcement to these arguments, we appeal to the results of previous research showing that musical training improves the general intelligence of adolescents (Rickard et al., 2012) and mathematics (Mehr et al., 2013). Ultimately, we believe that the music employed, including adolescents' musical preferences, has had a role in increasing sustained attention, processing speed, and fluid cognition, which have in turn favored mathematical performance (Buehner et al., 2006;Floyd et al., 2003;Kail et al., 2015;Meyer et al., 2020;Schrank & Wendling, 2018;Taub et al., 2008). Furthermore, from these results, we support the hypothesis of Thompson et al. (2001) that the underlying mechanism of the effects of music listening on academic performance is due to increased arousal, which then leads to improved cognitive performance. ...
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Si bien numerosos estudios han mostrado que la música de fondo mejora el rendimiento académico de adolescentes, pocos han contrastado resultados a partir de sus preferencias musicales o de composiciones de Mozart. Participaron en el estudio 185 adolescentes pertenecientes a los cursos de 1º a 4º de Educación Secundaria Obligatoria con edades comprendidas entre 12 y 17 años con una (EM = 13,63; DS = 1,26) de las cuales el 52,4% eran chicas. Se realizó una asignación aleatoria de los grupos a una de dos condiciones experimentales: escuchar su preferencia musical o composiciones de Mozart mientras desarrollaban una prueba matemática. Los resultados muestran que los chicos obtienen significativamente mejores resultados en matemáticas que las chicas. Asimismo, se aprecia una disminución en el tiempo de ejecución de tareas matemáticas y que los estudiantes con rendimiento más bajo obtienen mayor beneficio con música. Igualmente, en el grupo que escuchó su preferencia musical se produjo una mayor mejora en las chicas y en cambio, en el que escuchó música de Mozart esta se manifestó en los chicos. Se considera que la optimización de los niveles de excitación ha mejorado el enfoque atencional, lo que a su vez ha incrementado la velocidad de procesamiento haciendo que aumentara la eficiencia para seleccionar información y encontrar respuestas más acertadas, redundando, de este modo, en el rendimiento matemático. Asimismo, se presta especial atención a que la escucha de música durante el desempeño de tareas matemáticas ha ayudado en mayor medida al alumnado con un pobre rendimiento matemático. A través de este artículo se manifiesta, debido a su importancia, una posición en pro de un mayor reconocimiento y presencia musical a nivel curricular en Educación Secundaria Obligatoria.
... Further, the present study did not assess whether the outcomes examined had any impact on the academic performance of students who participated in the Brain Balance programme. However, the outcomes examined here (sensory motor skills, attention and cognitive performance) have been shown in previous studies to influence and be predictive of academic achievement, including in maths, reading comprehension and writing (Bull et al., 2008;Checa & Rueda, 2011;Geertsen et al., 2016;Hajovsky et al., 2018;Khng & Ng, 2021;Rennie et al., 2014;Schmidt et al., 2017;Taub et al., 2008;Worthen, 2010). It would be useful for future studies of the Brain Balance programme in a school setting to examine pre-and post-programme scores on standardized academic tests, in order to elucidate whether program-related improvements in sensory motor skills, VADTRS scores and CBS cognitive performance translate to improvements in academic outcomes. ...
... Además, el presente estudio no evaluó si los resultados examinados tuvieron algún impacto en el rendimiento académico de los estudiantes que participaron en el programa Brain Balance. Sin embargo, los resultados examinados aquí (habilidades motoras sensoriales, atención y rendimiento cognitivo) han demostrado en estudios anteriores que influyen y son predictivos del rendimiento académico, incluso en matemáticas, comprensión lectora y escritura (Bull et al., 2008;Checa & Rueda, 2011;Geertsen et al., 2016;Hajovsky et al., 2018;Khng & Ng, 2021;Rennie et al., 2014;Schmidt et al., 2017;Taub et al., 2008;Worthen, 2010). Sería útil para futuros estudios del programa Brain Balance en un entorno escolar examinar las puntuaciones antes y después del programa en pruebas académicas estandarizadas, con el fin de dilucidar si las mejoras relacionadas con el programa en las habilidades motoras sensoriales, las puntuaciones VADTRS y el rendimiento cognitivo CBS se traducen en mejoras en los resultados académicos. ...
... Furthermore, children's non-verbal ability is known to play a role in mathematics achievement (e.g. Taub et al., 2008), and this was controlled for by measuring children's non-verbal reasoning skills. ...
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Early detection of and relevant information on children’s mathematical difficulties is important to initiate targeted teaching and intervention. This study investigated the extent to which strategy use in single-digit addition provides additional predictive information about 61 grade one children’s (6-year-old) mathematical achievement 3 years later that is not available from a standardised mathematics achievement test. Four predictors available in year one (arithmetic strategy use, mathematical achievement, non-verbal reasoning skills and sex) explained 54% of the variation in grade four mathematics achievement. Arithmetic strategy use was the most important single predictor of year four mathematics achievement ( R ² = 30%) and explained an additional 12% variation if added to a model comprised by the three other year one predictors. This result suggests that systematically obtained measures of how young children solve single-digit arithmetic problems might provide useful information about their foundational number knowledge, which in turn may reveal how well they achieve later in school.
... Numerous academic studies have investigated the relationship between grade level and general cognitive ability as well as academic achievement (Boulanger, 1981;Fleming & Malone, 1983;Steinkamp & Maehr, 1983). As grade levels progress, the accumulation of academic knowledge increases, leading intelligence to be considered the strongest predictor of academic success (Gottfredson, 2002;Kuncel et al., 2004;Rosander et al., 2011;Taub et al., 2008). Laidra et al. (2007) emphasized a causal relationship between intelligence and achievement, revealing that the most powerful predictor of success at all levels of students is their general cognitive ability. ...
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... In a large prospective study of 70,000 students, it was found that general intelligence could explain up to 58.6% of the variation in performance on national tests at the age of 16 years (Deary et al., 2007). Fluid intelligence is part of general intelligence and is recognized as a causal factor when experiencing non-familiar situations in general (Valentin Kvist & Gustafsson, 2008;Watkins et al., 2007) and solving mathematical tasks in particular (Floyd et al., 2003;Taub et al., 2008). Ravens Advanced Progressive Matrices (APM) (Raven & Raven, 1991), which is the most common test for fluid intelligence, consists of 48 regular test items and 12 practice items. ...
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