However, there is no direct connection between beat perception 4 and musical self-theories 8, 9. Openness to experience 16 is connected to the cluster of musical abilities and activities only indirectly via extraversion. If we assume that the variables in this chain are causally linked then we can apply Pearl's do-calculus Pearl, , for estimating the effect of the two theory of musicality variables onto academic achievement we used the function ida in the R package pcalg. Because from each of the two musical self-theory variables there are several possible routes to academic achievement as dependent variable, we obtain a multiset of effect sizes and the effect of theory of musicality on academic achievement is therefore described rather by a range of potential effect sizes which contains the true size.
For the variable Musical Goal Choice , the effect size is estimated to be in the range of 0. Similarly, for the variable Theory of Musicality , the effect size is estimated to lie between 0. The effects of Academic Self-Theories and Goals variables on academic achievement lie in a similar range. For Academic Goals the effect size is between 0. This study investigated how musical activities and abilities are related to intelligence, personality, self-concept and self-theories of musicality and intelligence as well as academic performance in a sample of female adolescents. The main result of this study is a network model generated by the application of the PC algorithm to the correlational data.
It does not provide any information about the directionality of causal effects but it demonstrates graphically which variables are directly or indirectly related to which other variables. As such the network model replicates some important findings form the existing literature. Among these are the association of intelligence with musical abilities directly and musical training indirectly , which has been found in a number of previous studies Schellenberg, , ; Ruthsatz et al. The developmental connection between age and intelligence was also replicated in the network model see Fry and Hale, and so did the association between intelligence and academic achievement that has been reported in previous studies e.
In addition to replicating results from previous studies the network model also contains a number of novel results and findings that partly differ from previous studies.
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One example is the relationship between musical and personality variables. Many previous studies have found openness to experience to be the personality dimension that is most strongly e. However, in our results extraversion is the only Big 5 personality dimension directly connected to a musical variable and openness only has an indirect connection to musical variables via extraversion. However, the result found in this study that extraversion separates musical variables from openness is novel.
It is possible that this is a result of the female-only sample of this study, taking into consideration that substantial gender differences with regards to the association of personality and musical variables have been reported before Werner et al. In addition, it is worth considering that personality is still malleable in adolescence Vecchione et al. In this network model the important role of age is evidenced by the connection between age and extraversion. An interesting hypothesis implied in these findings concerns the causal direction of the relationship between music and openness.
Instead of assuming openness as a stable trait to cause musical activity in adolescence see Corrigall et al. This hypothesis would be in line with the analysis presented by Hille and Schupp who report significant effects of musical training during adolescence on openness as well as conscientiousness. While it is not possible to test the directionality hypothesis of the cause-effect relationship between music and personality with the current data, it constitutes a question that can potentially be answered from data to be collected in the envisaged longitudinal study.
Another novel finding arising from the network model are the relationships of the cognitive and musical self-theories. The four variables relating to self-theories of intelligence and musicality form a closely connected cluster, supporting the hypotheses that these self-theories are conceptually related for the participants in our sample.
However, there is no direct connection between concurrent musical activities, musical training or beat perception ability and either of the musical self-theory variables. This seems to suggest that musical activities alone are not sufficient to influence or be influenced by musical self-theories, but that this relationship is mediated by at least one actual musical skill melodic memory.
Musik in der Medizin / Music in Medicine
Furthermore, the graph shows that there is a chain of connections from musical self-theories through theory of intelligence and conscientiousness to academic achievement. An incremental theory of intelligence is indirectly associated with academic achievement through conscientiousness and effort. This finding confirms earlier work suggesting that an incremental theory of intelligence, that is, a belief that intelligence is malleable, is directly related to the level of conscientiousness and effort a student adopts and that this in turn relates to academic achievement Diener and Dweck, One of the aims of this present study was to consider what factors might contribute to the individual differences in student's motivation toward academic and musical studies.
The analyses reveal that the beliefs about the nature of musicality and intelligence may relate to the level of conscientiousness. A similar finding is reported by Hille and Schupp who found a significant and positive effect of musical training during adolescence on conscientiousness, even after controlling for a large number of potentially confounding variables. In line with this, our network model suggests an interpretation where conscientiousness affects academic effort or motivation to work and that this in turn may have a bearing upon an adolescent's academic performance.
Making the corresponding causal assumptions and applying Pearls' do-calculus to the network structure we demonstrate that both subscales of the theory of musicality had small to moderate effects on academic achievement. The effect sizes lie between 0. Whether the causal assumptions are in fact justified and whether the effect of the self-beliefs about musicality are indeed in the order of about 0. One final outcome to mention is the network modeling methodology employed in this study, which makes use of the PC algorithm Pearl, , to identify a network of relationships that is consistent with the results of conditional independence tests, more specifically partial correlation tests.
This approach is exploratory and related to the burgeoning field of causal structure discovery, which has produced very promising results in other areas Park et al. Highly multivariate datasets can generate models that are purely constructed from data and that represent a plausible middle ground between two other common forms statistical representation, large bivariate correlation matrices and regression models.
The network model has the advantage that it is designed to handle correlations between variables in a principled way, thus illuminating relationships between potential confounders and the variables of main interest while avoiding strong a priori assumptions about the nature of dependent and independent variables in non-experimental datasets, as well as assumptions of homoscedasticity, and the absence of collinearity of regressors.
Network models can be exploited even further to suggest the directions of causal effects if either certain conditions are met in the data Pearl, , or if convincing causal assumptions can be made e. However, because of the limited sample size and the need to minimize the influence of sampling error on causal result, the perspective was not pursued in this study, but remains an option for the analysis of a larger sample of participants.
Finally, it is worth remembering that a severe limitation of this study is the fact the data was collected on a sample of female adolescents with a particular socio-economic background. It will be therefore necessary to extend the study on include male adolescents and students from other schools and social backgrounds in order to generalize results to the population of adolescents at least in the UK.
This is all the more important as gender effects with regards to musical training and instrument choice are well-documented in the literature Hallam et al.
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Taken together, this study provides a baseline for the exploration of the inter-relatedness of self-theories of intelligence and musicality, personality traits, and ability in both academic and musical domains. Future work needs to extend this approach to a larger sample including different genders and different social backgrounds. In addition, the planned longitudinal study as well as any potential interventions that deliberately intend to change musical self-theories will seek to broaden our understanding of the nature and development of personality and musical abilities through adolescence and how these relate to academic motivation, effort and achievement.
This seems like an ambitious endeavor at present, but has the potential to produce results that have important implications for the planning of academic curricula, the functional use of music education and the role that music plays in the development of personality and cognitive abilities in the formative period of adolescence.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. We thank the staff and children of Queen Anne's school, Caversham, as well as their parents for their participation in this study. We also thank Iris Mencke for her help with the preparation of the manuscript. Akiva-Kabiri, L. Memory for tonal pitches.
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