The Pedagogical Use of Visual Feedback for Enhancing Dynamics in Higher Education Piano Learning and Performance

Hamond, Luciana; Welch, Graham; Himonides, Evangelos

doi:10.20504/opus2019c2526

Cited by 11 publications

(12 citation statements)

References 35 publications

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“…In contrast with most part of the previous research that has studied the use of technology to provide different kinds of feedback to improve learning (Thorpe, 2002; Welch et al, 2004; Wilson et al, 2008; Van Der Linden et al, 2011; Wang et al, 2012; Leong and Cheng, 2014; Schlegel and Gregory Springer, 2018), we did not found statistical differences between the amount of improvement at the end of the task between the BF and the BNF group. However, behavioral differences found among the BF group could be the result of an increment of the conscious awareness of their own performance as suggested by Hamond (2017). It is important also to highlight that the demanded task and the feedback provided in this study differs widely compared with previous work which mainly studies pitch accuracy and uses real-time feedback.…”

Section: Discussionmentioning

confidence: 80%

“…The study reported improved pitch accuracy by using the system. Previous research has studied the effect of using different kinds of interfaces and different kinds of feedback in singing voice (Thorpe, 2002; Welch et al, 2004; Wilson et al, 2008; Leong and Cheng, 2014), trombone (Schlegel and Gregory Springer, 2018), piano (Hamond, 2017), and violin (Wang et al, 2012). Although there are differences in the way RTVF may improve performance, most of the previous studies reported beneficial effects of RTVF in learning.…”

Section: Introductionmentioning

confidence: 99%

“…Although there are differences in the way RTVF may improve performance, most of the previous studies reported beneficial effects of RTVF in learning. An extensive review on feedback and technology applied to music learning can be found in Hamond (2017). The same author also investigated the nature and application of combined visual-auditory feedback generated by technology systems in higher education piano learning and teaching contexts.…”

Section: Introductionmentioning

confidence: 99%

“…As related by one of those students: “Sometimes you know in your mind what you want to do, […] but sometimes you do not realize exactly what you're doing in practice[…]. So, when you hear, you can clearly see what you are doing and what you're not” (Hamond, 2017, p. 278).…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Evaluation of a Sound Quality Visual Feedback System for Bow Learning Technique in Violin Beginners: An EEG Study

Blanco

Ramírez

2019

Front. Psychol.

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Current music technologies can assist in the process of learning to play a musical instrument and provide objective measures for evaluating the improvement of music students in concrete music tasks. In this paper, we investigated the effects of a sound quality visual feedback system (SQVFS) in violin learning. In particular, we studied the EEG activity of a group of participants with no previous violin playing experience while they learned to produce a stable sound (regarding pitch, dynamics, and timbre) in order to find motor learning biomarkers in a music task. Eighteen subjects with no prior experience in violin playing were divided into two groups: participants in the first group (experimental group, N = 9) practiced with instructional videos and offline feedback from the SQVFS provided in alternation with their performance, while participants in a second group (control group, N = 9) practiced with the instructional videos only. A third group of violin experts (players with more than 6 years of experience) performed the same task for comparative purposes ( N = 7). All participants were asked to perform 20 trials (4 blocks of 5 trials) consisting of a violin bowing exercise while their EEG activity and their produced sound was recorded. Significant sound quality improvements along the session were found in all participants with the exception of participants in the expert group. In addition, participants in the experimental group showed increased interest in the learning process and significant improvement after the second block not present in the control group. A significant correlation between the levels of frontal gamma band power and the sound improvement along the task was found in both the experimental and control group. This result is consistent with the temporal binding model which associates gamma band power with the role of integrating (binding) information processed in distributed cortical areas. Task complexity demands more cognitive resources, more binding and thus, gamma band power enhancement, which may be reduced as the demanded task begins to be automated as it is likely to be the case in both beginners groups.

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Section: Discussionmentioning

confidence: 80%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Evaluation of a Sound Quality Visual Feedback System for Bow Learning Technique in Violin Beginners: An EEG Study

Blanco

Ramírez

2019

Front. Psychol.

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“…This makes parental companionship important throughout the course. Thus, parents and teachers should collaborate harmoniously, and teachers should innovate customized piano courses based on the educational psychology of children, thereby catering to the healthy development of their mentality (Hamond et al, 2019 ).…”

Section: Application Of DL In Piano Education Of Childrenmentioning

confidence: 99%

Piano Education of Children Using Musical Instrument Recognition and Deep Learning Technologies Under the Educational Psychology

2021

Front. Psychol.

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The objective of the study was to enhance quality education in the traditional pre-school piano education. Deep Learning (DL) technology is applied to piano education of children to improve their interest in learning music. Firstly, the problems of the traditional piano education of children were analyzed with the teaching patterns discussed under educational psychology, and a targeted music education plan was established. Secondly, musical instrument recognition technology was introduced, and the musical instrument recognition model was implemented based on DL. Thirdly, the proposed model was applied to the piano education of children to guide the music learning of students and improve their interest in piano learning. The feature recognition and acquisition of the proposed model were improved. Finally, the different teaching patterns were comparatively analyzed through the Questionnaire Survey (QS). The experimental results showed that the instrument recognition accuracy of Hybrid Neural Network (HNN) is 97.2%, and with the increase of iterations, the recognition error rate of the model decreases and stabilizes. Therefore, the proposed HNN based on DL for musical instrument recognition can accurately identify musical features. The QS results showed that the introduction of musical instrument recognition technology in the piano education of children can improve their interest in piano learning. Therefore, the establishment of the piano education patterns based on the piano education model can improve the effectiveness of teaching piano to students. This research provides a reference for the intelligentization of children's piano education.

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Effect of multimedia on student performance: the case of Chinese musical classes

Shaoyu

2022

Interactive Learning Environments

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The Pedagogical Use of Visual Feedback for Enhancing Dynamics in Higher Education Piano Learning and Performance

Abstract: The pedagogical use of technology-mediated feedback in a higher education piano studio: an exploratory action case study.

Cited by 11 publications

References 35 publications

Evaluation of a Sound Quality Visual Feedback System for Bow Learning Technique in Violin Beginners: An EEG Study

Evaluation of a Sound Quality Visual Feedback System for Bow Learning Technique in Violin Beginners: An EEG Study

Piano Education of Children Using Musical Instrument Recognition and Deep Learning Technologies Under the Educational Psychology

Effect of multimedia on student performance: the case of Chinese musical classes

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