Methodology for Violin Concerto Performance Skills Development Research Paper

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In order to measure performance skills, diverse tools have been employed. The most common instruments include neuroscience measurements, professional assessments, and self-efficacy reporting (Bishop et al., 2021; Volta et al., 2018). The focus can be on quantitative and qualitative data based on the purpose of the study. A combination of these methods can also be utilized, as in the study by Volta et al. (2018) that implied the focus on motion captured and analyzed with specific software. The choice of methodology depends on the goals to be attained and the topic to be researched. The aim of the present study is to analyze Mozart’s violin concerto performance skills, so a set of methods will be employed.

This study will incorporate the review of a professional musician and the self-assessment of the students. Early (2018) found certain correlations between objective and subjective assessment strategies, so it is possible to exploit a combination of the two to obtain accurate data. Performance recording and assessment have been seen as effective tools for analyzing musical performance (D’Amato et al., 2020). Twenty graduates of a musical school and three professional violinists will participate in the study. The involvement of three external reviewers will increase the reliability of the findings.

The participants will play Mozart’s Violin Concerto No.3, and their performance will be video-recorded. Prior to the beginning of the recording, students will be notified that motion will be measured in addition to their overall performance. Moreover, the variables of this study will be mentioned to make sure that students have a chance to exhibit their best skills. The performers will also have time to practice right before the recording. They will have up to fifteen minutes of practice, and after that, they will be invited to the recording site.

After the performance, students will receive questionnaires and go to another room to complete them. Each student will watch his or her performance and measure it based on the sound and motion. Students will first listen to their performance (without watching) and grade it with 5 as the highest score and 1 as the lowest score. The participants will also complete questionnaires giving similar scores to measure their performance in terms of bow angle, instrument angle, and bow distance. The professional violinists will complete similar questionnaires assessing the performance of all students. The same procedure will be implemented, and they will first listen to the musical piece and then watch the muted video recordings.

It is believed that motion plays an important role when performing a musical piece. It is possible to hypothesize that the students whose motion scores are the highest will receive the highest scores for the sound from professional violinists. At that, graduates’ self-assessments of visual and audial aspects are unlikely to correlate. Self-assessment can help shed light on students’ attitudes toward motion. Notably, the participant’s true attitude will be identified as their attention will be drawn to this aspect. Graduates may find no link between motion and overall performance. It is necessary to note that the provision of a subjective score for a musical piece can be regarded as a limitation. No particular measurements, such as pitch differentiation or rhythm accuracy, have been chosen because the focus is on the overall impression of the piece rather than technical aspects. The chosen methodology is relevant as it helps in addressing the hypothesis.

References

Bishop, L., Jensenius, A. R., & Laeng, B. (2021). . Frontiers in Psychology, 12, 1-18.

D’Amato, V., Volta, E., Oneto, L., Volpe, G., Camurri, A., & Anguita, D. (2020). . Cognitive Computation, 12(6), 1356-1369.

Early, P. H. (2018). Moderating performance assessment: Computer or connoisseur? Comparing objective and subjective measurements of violin proficiency. [Doctoral dissertation, University of Lincoln].

Volta, E., Mancini, M., Varni, G., & Volpe, G. (2018). Proceedings of the 5th International Conference on Movement and Computing, 1-4.

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