An exploratory analysis into the relationships between spatial factors, domain-free general capacities and general fluid intelligence.
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The inception of psychometric research concerning individual differences in cognition was grounded in explaining and enhancing performance in education (Spearman, 1904). This work established the construct of a single general intelligence often described as IQ. The aim of enhancing educational practices continues to underpin much of psychometric research, however Cattell (1943) postulated the potential for general intelligence to comprise of two separable entities; fluid intelligence (Gf) and crystallised intelligence (Gc). Fluid intelligence is defined as “a facility in reasoning, particularly where adaptation to new situations is required” while crystallised intelligence is defined as “accessible stores of knowledge and the ability to acquire further knowledge via familiar learning strategies” (Wasserman & Tulsky, 2005, p.18). Within education the development of crystallised intelligence (Gc) is arguably more visible as content knowledge is more easily assessed. The development of novel problem solving capacities is less discernible, however it can be supported by pedagogical strategies such as problem based learning (PBL). This paper aims to afford an approach to the development of fluid intelligence (Gf) through the identification of cognitive aptitudes aligning with this construct. It is envisioned that having a greater understanding of the cognitive faculties which support novel problem solving that pedagogical interventions such as the one described by Sorby (2009) could be scientifically developed and refined. An exploratory analysis was conducted to identify associations between cognitive factors and fluid intelligence (Gf). A cohort of initial technology teacher education (ITTE) students (N = 85) completed a battery of 17 psychometric tests selected as indicators for various cognitive constructs. Results illustrate an alignment between working memory capacity, spatial ability and inductive reasoning with fluid intelligence. Stemming from this, a discussion is presented discussing the potential for the translation of cognitive factors into STEM educational practices specifically focusing on technology education.
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