Lateral signs and their interaction as a factor in the severity of mathematical abilities in adolescence - Nikita A. Khokhlov (Nacionalʹnyj Psihologičeskij Žurnal, 2016)
The paper studies the connection of the lateral features in the manual, auditory, visual fields, and their interaction with the mathematical abilities in adolescence.The research involved 92 healthy people including 17 males and 75 females aged 15 to 25 years (18,7 ± 2,2), who do not major in mathematics. To measure the components of mathematical ability the standardized math test MAAGS-2015 to reveal arithmetic, algebraic, geometric abilities was used. Diagnosis of hemispherical asymmetry was performed using self-reports of manual asymmetry, M.Annette standardized questionnaire modification, samples of «Interlocking fingers,» «Napoleon’s Pose», «Applause», «Aiming», Rosenbach’s test and dichotic listening. When comparing the features with lateral components of mathematical ability to incorporate asymmetries possible interaction of different analyzers was considered. The research results reveal that different lateral characteristics are significant predictors for the different components of mathematical abilities; some lateral symptoms are not related to mathematical ability. The greatest predictive power belongs to sensory asymmetries and their interaction. In general, the highest mathematical abilities are observed in patients with right and bilateral signs, left-sided symptoms often reveal negative predictors. The interaction asymmetries between different analyzers manifested in unequal due to the mathematical abilities indicators lateralization in the same field in different versions of lateralization in the other. Cross-lateralization in most cases is a negative predictor of mathematical abilities. The models based on the interaction between the lateral features allow to explain more than a quarter of the variability of the components of mathematical abilities. The predictive ability of these models is significantly higher than that of models with individual predictors.