International Symposium on Performance Science
ISBN 978-90-9022484-8© The Author 2007, Published by the AEC
All rights reserved

Biographical predictors of music-related motorskills in children pianists
Hans-Christian Jabusch1, Raymond Yong2, and Eckart Altenmüller1
1 Institute of Music Physiology and Musicians’ Medicine,

Hanover University of Music and Drama, Germany
2 Faculty of Music, University of Melbourne, Australia

This study aimed to identify biographical predictors of children pianists’motor skills in a relevant musical context. Motor skills at the piano wereassessed in 30 piano-playing children by testing temporal evenness instandardized scale playing which is a basic element of piano technique.
Questionnaires were used to collect detailed information regarding thepractice habits and other biographical factors. Associations between
performance values and variables from the questionnaire wereinvestigated by multiple regression analysis. Besides the duration ofpiano education and the frequency of technical exercise, motivational
factors and parental supervision predicted children pianists’ motor skillsin the selected motor task, i.e. in a relevant musical context.
Keywords: sensorimotor learning; motor skills; practice; music performance; piano

Performing instrumental music is one of the most complex of humanaccomplishments. Musicians’ motor coordination is highly complex and takes
place at an extremely high level of spatiotemporal accuracy. Successful
strategies for the acquisition of motor coordination and musical abilities
required for this challenging task are of interest to both instrumental teachersand expertise researchers.
A number of publications have reported on research that related
biographical variables with musical performance achievement (for a review,see McPherson 2006). So far, little attention has been paid to the acquisitionof motor skills in children musicians and, in particular, of motor performancein relevant musical tasks. Objective quantification of motor performance in arelevant musical task was previously carried out in professional pianists while
they were playing standardized C major scales (Jabusch 2006). Scale playing

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is one fundamental aspect of piano technique. In C major scales played byprofessional pianists, a high degree of temporal evenness in the inter-onsetintervals was revealed using a Musical Instrument Digital Interface (MIDI)based analysis method. This method has been shown to be a valid and reliable
tool to investigate temporal evenness in scale playing of pianists (Jabusch etal. 2004).
In the present study, we examined children pianists’ motor performanceas measured by temporal evenness in scale playing, and investigated biographical factors and their association with motor performance. These biographical factors included the child’s history of practicing and learning thepiano, information regarding their everyday musical environment, theirattitudes towards music and practice, their subject preferences at school, andthe extent to which their parents supervised their practice.
METHOD
Participants
The subjects for the study comprised 30 school-aged children who weretaking piano lessons at the time of the study (22 girls and 8 boys, aged
between 8 and 17 years old, median age 13). Of the participants, 26 took their
piano lessons at the Hanover music school, while four subjects were taking
lessons at the Hanover University of Music and Drama. All subjects had beenlearning the piano for at least nine months prior to the study. The only
inclusion criterion was the ability to play C major scales with both hands.
Informed consent was obtained by all participants and their parents.
Materials
A questionnaire was developed that sought information on the general
pianistic and musical history of the subject, focusing on details of theirpractice amount and content (e.g. retrospective assessment of practicequantity, repertoire, frequency of practicing technical exercises), details of
piano lessons (e.g. content of lessons, number of piano teachers in the past),
their attitudes towards music and practice, and their involvement in othermusical activities. Subjects were asked about musical activities in the family
and how often a parent supervised them during their practice at home. A
series of questions asked the children to rate their enjoyment of five different
school subjects (music, mathematics, visual arts, sport, and language).
Subjective ratings (e.g. of frequencies or of enjoyment) were encoded oncorresponding 5-point scales. The questionnaire was completed with theINTERNATIONAL SYMPOSIUM ON PERFORMANCE SCIENCE

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assistance of a single researcher who was available to give clarifications when
uncertainties arose in the questions. Parents of the younger subjects wereasked to assist in the answering of questions.
Procedure
The procedure of scale playing and analysis of temporal evenness wasperformed according to a protocol published previously (Jabusch et al.
2004). Scales were performed on a digital piano that was connected to acomputer. For the test, sequences of 10 to 15 C major scales were played over
two octaves (range: C3-C5) in both directions, inward and outward, with eachhand separately. Participants were asked to play in legato-style. Fingering
was according to the regular C major fingering. The tempo was standardized
and paced by a metronome (80 beats per minute, two notes per beat). Interonset intervals for all individual notes of the scales were analyzed using a
researcher-developed software. Scale analysis was performed for each handand in both directions separately. Mean standard deviations of inter-onsetintervals (msdIOI) were calculated for all scales of each hand and playing
direction. The msdIOI parameter was previously shown to be a reliableindicator of temporal evenness in pianists’ scale playing (Jabusch et al.
2004). The median of the msdIOI values of both hands and playing directions(MIOI) indicated the overall temporal unevenness of note onsets for eachparticipant.
Pearson correlations were calculated to detect associations between
performance values and variables from the questionnaire. Stepwise multiple
regression analyses were used to assess predictability of performance results.
The two-tailed level of statistical significance was set at p<0.05.
RESULTS
Participants began to play piano between the age of 5 and 12 years (median=7years) and the duration of their piano education was between 9 months and12 years (median=5 years). The median daily practice time was 0.5 hours(range=0.2-3.5), and the median total life practice time was 559 hours(range=88-8700).
Results from the questionnaire regarding participants’ attitudes towards
music, performing, practice, and technical exercises, as well as the frequencyof parental supervision and technical practice are displayed in Figure 1.
In the performance test, all children were able to play the scales according tothe protocol. MIOI indicated the overall temporal unevenness of note onsets
for each participant. A low score for MIOI denotes a low level of un-366

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Figure 1. Distributions of results from the questionnaire. Frequencies are coded as 1=never, 2=rarely, 3=sometimes, 4=often, and 5=very often. In the displayed enjoyment
rating scales, 1 represented a negative enjoyment rating and 5 a positive enjoyment rating. In the rating of importance, 1 represented a low importance and 5 a high importance.

Figure 2. Distribution of motor performance results. MIOI values indicate the individual overall temporal unevenness of note onsets in standardized scale playing for eachparticipant.

evenness in the scales (high temporal onset precision), while a high score for
MIOI denotes a high level of unevenness (low temporal onset precision).
Distribution of performance results is given in Figure 2.
A correlation was observed between the motor performance values MIOI
and the daily practice time (r=-0.45, p<0.05), the total life practice time (r=0.46, p<0.05) and the duration of piano education (r=-0.41, p<0.05).
Stepwise multiple regression analysis revealed a model predicting 68% of thevariance of MIOI values, with the following six items of the questionnaire aspredictors: duration of piano education (30%), enjoyment of practice (10%),frequency of practicing technical exercises (9%), enjoyment of the subject

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Table 1. Information on the model revealed by stepwise multiple regression analysis.
Regression equation

R2

R2 adjusted

MIOI = 44 - 0.97 (years piano) - 1.6 (joy practice)

0.76

0.68

- 1.2 (frequency exercises) + 2.9 (joy artrel)- 0.93 (parental supervision) - 1.6 (joy music)
Key. MIOI=individual overall temporal unevenness of note onsets (ms); years piano:
duration of piano education (years); joy practice=enjoyment rating of practice (highvalue represented a positive enjoyment rating); frequency exercises=frequency ofpracticing technical exercises (high value represented a high frequency); joy
artrel=enjoyment rating of visual arts at school, relative to enjoyment ratings of othersubjects (low value represented a high enjoyment); parental supervision=frequency ofparental supervision (high value represented a high frequency); joy music=enjoyment
rating of music (high value represented a positive enjoyment rating).

visual arts at school (7%), frequency of parentally supervised practice (6 %),and enjoyment of music (6%). Details are given in Table 1.
DISCUSSION
The aim of the study was to identify biographical predictors of children
pianists’ motor skills in a relevant musical context. According to expectations,variables that determined the amount of time children spent at theinstrument (daily practice time, total life practice time, and total years
playing the piano) were significantly correlated with temporal fine motorprecision. Moreover, the duration of piano education was a predictor for
temporal fine motor precision. These findings coincide with the principle
suggested by Ericsson et al. (1993) proposing 10 years and 10 000 hours ofdeliberate practice required for the acquisition of expertise. Our results are inkeeping with results of various studies that related the number of years ofpractice with instrumental achievement (e.g. Sloboda and Davidson 1996,
McPherson 2005). The frequency of technical practice, a predictor of fine
motor precision explaining 8% of the variance in the temporal onset
precision, can be classified as one type of deliberate practice according to thedefinitions described by Ericsson et al. (1993). External and internalmotivational factors were frequently described as influential factors formusical development. Sloboda and Davidson (1996) emphasized thepossibility and necessity of external motivation developing into internal selfmotivation by the early teenage years as a prerequisite to sustain thecommitment required to persist with musical instrument learning. In the368

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present study, the frequency of parentally supervised practicing represents anexternal motivational factor that turned out to be a predictor of temporal fine
motor precision. The predictors enjoyment of practice, enjoyment of music,
and enthusiasm for the subject visual arts at school may represent internalmotivational factors not only for making music but additionally for a further
artistic disposition. Taken together, predictors of motor skills in children
pianists cohered with factors previously found to influence musicalachievement at the instrument, even with the focus on a selected motor task
in a relevant musical context.
Acknowledgments
The authors would like to express their appreciation to all participating piano students
and to the piano faculty of the Musikschule Hannover for their kind support.
Address for correspondence
Eckart Altenmüller, Institute of Music Physiology and Musician’s Medicine, Hanover
University of Music and Drama, Hohenzollernstr. 47, 30162 Hanover, Germany;
Email:altenmueller@hmt-hmt-hannover.de
References
Ericsson K. A., Krampe R. T., and Tesch-Römer C. (1993). The role of deliberate practicein the acquisition of expert performance. Psychological Review, 100, pp. 363-406.
Jabusch H. C., Vauth H., and Altenmüller E. (2004). Quantification of focal dystonia in
pianists using scale analysis. Movement Disorders, 19, pp. 171-180.
Jabusch H. C. (2006). Movement analysis in pianists. In E. Altenmüller, J. Kesselring,and M. Wiesendanger (eds.), Music, Motor Control and the Brain (pp. 91-108).
Oxford: Oxford University Press.
McPherson G. E. (2005). From child to musician: Skill development during thebeginning stages of learning an instrument. Psychology of Music, 33, pp. 3-35
McPherson G. E. (ed.) (2006). The Child as Musician: A Handbook of MusicalDevelopment. Oxford: Oxford University Press.
Sloboda J. A. and Davidson J. W. (1996). The young performing musician. In I. Deliège,and J. A. Sloboda (eds.), Musical Beginnings: The Origins and Development ofMusical Competence. (pp. 171-190). Oxford: Oxford University Press.