Predictors of Elementary Students' Intentions to Continue in Music when Entering Middle or Junior High School

The purpose of this study was to determine those variables that best predict a student’s intention to continue in a music class when entering middle or junior high school. This study utilized the theory of planned behavior (TPB) as a framework to aide in examining student behavioral intentions regarding school music participation. The original TPB constructs of (a) attitude, (b) subjective norms, and (c) perceived behavioral control were utilized as independent variables. Additionally, two constructs related to parental involvement (parental attitudes towards music study and parental expectations for music study) and the variable of peer influence were included as additional independent variables. The participants in this study (N = 278) were students from six schools located in south Louisiana. All participants were enrolled in compulsory elementary general music classes during their final year of elementary school. Statistically significant correlations were found between all examined variables (p < .01), with the highest correlation being between the TPB construct of attitude and intention. A simultaneous multiple regression analysis revealed that all independent variables accounted for 68.1% of the variance in the dependent variable of intention. The overall multiple regression was statistically significant, R2 = .681, F(6, 271) = 96.52, p < .001. Further examination of the regression results revealed that three variables were statistically significant predictors of intention: TPB-attitude (p < .001), TPB-subjective norm (p < .001), and parental attitudes towards music study (p = .001). An analysis of the written responses to the open-ended statement that asked students to indicate possible reasons other students might not choose to continue in school music revealed that the highest cited category was attitude towards school music

One-step deposition of nano-to-micron-scalable, high-quality digital image correlation patterns for high-strain in-situ multi-microscopy testing

Digital Image Correlation (DIC) is of vital importance in the field of experimental mechanics, yet, producing suitable DIC patterns for demanding in-situ mechanical tests remains challenging, especially for ultra-fine patterns, despite the large number of patterning techniques in the literature. Therefore, we propose a simple, flexible, one-step technique (only requiring a conventional deposition machine) to obtain scalable, high-quality, robust DIC patterns, suitable for a range of microscopic techniques, by deposition of a low melting temperature solder alloy in so-called 'island growth' mode, without elevating the substrate temperature. Proof of principle is shown by (near-)room-temperature deposition of InSn patterns, yielding highly dense, homogeneous DIC patterns over large areas with a feature size that can be tuned from as small as 10nm to 2um and with control over the feature shape and density by changing the deposition parameters. Pattern optimization, in terms of feature size, density, and contrast, is demonstrated for imaging with atomic force microscopy, scanning electron microscopy (SEM), optical microscopy and profilometry. Moreover, the performance of the InSn DIC patterns and their robustness to large deformations is validated in two challenging case studies of in-situ micro-mechanical testing: (i) self-adaptive isogeometric digital height correlation of optical surface height profiles of a coarse, bimodal InSn pattern providing microscopic 3D deformation fields (illustrated for delamination of aluminum interconnects on a polyimide substrate) and (ii) DIC on SEM images of a much finer InSn pattern allowing quantification of high strains near fracture locations (illustrated for rupture of a Fe foil). As such, the high controllability, performance and scalability of the DIC patterns offers a promising step towards more routine DIC-based in-situ micro-mechanical testing.Comment: Accepted for publication in Strai